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What I Learned About the Future by Reading 100 Science Fiction Books - Forte Labs

Artwork by Antifan-Real
By Tiago Forte of Forte Labs

Now available in Russian , Portuguese , and Chinese .

Over the past two years I’ve read 100 sci-fi novels, averaging about one per week. See the full list here , with my favorites.

I started reading sci-fi to pass the time. I had good memories of reading Jurassic Park as a kid. I continued because I noticed that it gave me something: a stronger imagination, a disrespect for the merely possible.

I started noticing I had different ideas, ideas you can’t find by reading the same TechCrunch articles, Medium posts, and Hacker News digests as everyone else in Silicon Valley. I am in the business of selling ideas, and found these books both a treasure trove and a toolkit.

As futurist Jason Silva says, “Imagination allows us to conceive of delightful future possibilities, pick the most amazing one, and pull the present forward to meet it.” I believe reading these books has helped me both in the conceiving and the pulling.

Every good sci-fi story is, at it’s core, a thought experiment, and I’d like to run one of my own now:

What if these books represented a fair guess at what the future will be like?

It’s not so far-fetched. Reading the early classics by Jules Verne and H.G. Wells, what strikes me is not how much they got wrong, but how much they got right. I drew my selections mostly from this list of the top 100 sci-fi works of all time, so these books represent what we consider the best (or at least the most interesting) ideas out there.

Here is the future we are headed for, as predicted by our greatest sci-fi writers.

1. In order to save humanity, we must lose it

We all know that the long-term survival of our species is dependent on colonizing other planets, and eventually other solar systems. It is not a question of if our planet will become unsuitable for life, it’s a question of when .

But looking at the distances and timescales involved, it’s clear that as soon as we begin this process, we will start to drift apart.

It will start with language and culture. Settlements on the outer planets, separated by millions of miles and hours of transmission time, will start to develop their own dialects, their own slang, their own music, their own trends. Looking at just the variation within the English language, between highland Scotsmen and California surfers, South African boers and Caribbean creole, gives you just a hint of the cultural drift we will see.

Next will be political and economic drift. Just as the emerging American cultural identity reinforced and was reinforced by the American Revolution, the colonies will begin to see themselves as different because they are different, and demand a government that represents their interests. With the distances involved, we will be able to put down the first few rebellions, but it is only a matter of time before they break away.

Economic integration will expand, but far slower than our speed of colonization and exploration. By the time we are able to fully integrate these colonies into our economy, they will long have developed self-sufficient economic systems.

Finally, we will begin to see genetic drift. It is remarkable to think that, despite our huge diversity here on Earth, we are all one species, which means any individual could reproduce with any other individual of the opposite sex, going all the way back for 160,000 years.

But this is just a historical accident. For much of pre-history, at least a few hominid species roamed the planet, and it was only the rapid emergence and expansion of homo sapiens sapiens out of Africa and around the world that unified us.

The moment some of us leave the planet, our DNA will begin to diverge again. Starting with a limited gene pool and subject to different pressures, different sources of mortality, different levels of radiation and mutation, the spacefarers will embark on a new evolutionary path.

Eventually, whether it takes hundreds of years or thousands, one fateful mutation in one distant, isolated colony will make reproduction impossible, cutting off that branch forever.

In order to save humanity we must colonize the stars, and in doing so the unified definition of humanity as we know it will be lost.

2. Time will be our greatest enemy

As we conquer the 3 dimensions of space, the 4th dimension of time will increasingly become the greatest challenge we face.

The first reason is time dilation, a proven consequence of relativity most recently explored in the movie Interstellar , but which plays a major part in dozens of sci-fi stories going back decades. Time dilation is the phenomenon of time passing at different speeds depending on how fast you are moving, which means someone traveling at a significant fraction of the speed of light will age more slowly than someone still on Earth.

The human consequences of this one phenomenon are staggering. Long-term space travelers will return to their home planet with everyone they knew dead and gone. Families will be stretched across centuries, with people outliving their great-great-grandchildren. Historical figures will emerge from space capsules still young. Those who want to see the future will be sent off on a long, high-speed roundtrip, arriving at a time they specify. It will be like having a time machine with only a forward setting.

The second reason is the immense distances involved in interstellar space travel. It is likely that the first to embark on an interstellar voyage will not be the first to arrive — as they are in transit, new technology will be developed allowing later expeditions to overtake them. Imagine going into cryogenic sleep as the first group of interstellar explorers, only to wake up and find your target system has been colonized for hundreds of years.

A third reason is technology differentials. Technology will be so important to every aspect of spacefaring civilizations, and will be improving so quickly, that even small differences will have profound consequences:

  • Two systems with slightly different speeds of technological development will find a huge gap between them after a few decades or centuries. Their societies may be so fundamentally different that communication and exchange between them is difficult.
  • Technology sent to distant systems will be obsolete by the time it gets there. Even sending information at the speed of light may not be fast enough for systems that are light-years apart. This will make trade based on anything but raw materials extremely difficult.
  • War across vast distances will be futile, because any attack force sent at sub-light speeds will be obsolete by the time it arrives. But this could also mean a never-ending war that no side can win, as Joe Haldeman describes in Forever War .

We are already experiencing the limitations of time in space travel. In a recent documentary on the Rosetta spacecraft launched by the European Space Agency to land on a comet, they reveal that the probe’s Osiris camera is only 4 megapixels, which was the most advanced technology available when it was launched in 2004. Today it wouldn’t even make it into a smartphone.

The Philae lander that emerged from Rosetta to land on the comet was equipped with thoroughly tested harpoons and drills for the ice we thought it would be landing on. But in the intervening years we’ve discovered that the comet’s surface is actually a mixture of dust, gravel, and ice, making this equipment less than ideal for the job.

As the years go by, our common experience of time will break down, and we will find that the 4th dimension presents us with far greater challenges than the 3 physical dimensions ever did.

3. The future will be weird

If I had to pick one word to describe the future, as seen by the stories I found most compelling and believable, it would be weird . Let me explain.

Writers like Ray Kurzweil have done a good job of explaining why it is so difficult for us to envision the future that we’re headed toward. He argues that all of our ancestral heuristics are linear  — tracking an antelope running across a savannah, estimating how much time a store of food will last — but that due to Moore’s Law, we are entering a phase of exponential change that these heuristics are ill prepared to handle.

In other words, we look at the rate of change from the recent past, and extrapolate to the near future. But now that we are hitting the exponential part of the graph, this kind of extrapolation doesn’t apply.

I find this argument compelling, but what is most interesting to me is not just the speed of change, but the unpredictability of its direction. The stories I’ve read have led me to believe that we are barely aware of the smallest implications of some of the technologies we are developing, and that these implications are downright strange.

Take dating for example. What will dating be like in a world of highly advanced anti-aging treatments? Imagine a man and a woman on a date. They both look about 25, but their appearance means nothing. They have to play an intricate game of testing and probing each others’ pop culture knowledge to try and determine each others’ age, without giving away their own. There will be whole industries and schools of thought around how (why?) to date people who are decades (centures?) older or younger than you.

The area where we’ll see this weirdness the soonest is virtual reality. It’s funny to me that most portrayals of advanced virtual reality assume it will be like normal reality, with lifelike human bodies in lifelike worlds. But I think that we will very quickly realize that reality is a bug, not a feature.

What form would you take if you could take any form? There will be vast industries dedicated to helping us experience life as other people, as animals, as inanimate objects, as aliens. Other industries will be dedicated to designing environments, laws of physics, mental states, personalities, memories, and many other things we will have control over. Robin Wright’s 2013 independent film The Congress does a great job of envisioning such a world.

But the best example of how the future will be weird is artificial intelligence.

The very idea behind the technological singularity is that there is a point in our future beyond which we cannot see. Presumably this point is when human-level artificial intelligence gets access to its own source code, setting off an exponential intelligence explosion.

But what exactly does it mean to have “super-human” intelligence? What could we expect from a computer that has, say, a million times the computing capacity of all the humans that ever lived?

We presume that it would fill its time with “difficult” tasks, like solving world hunger, modeling the Earth’s climate, unraveling the structure of the brain, etc. But this is our anthropomorphic, linear thinking acting up again.

We can explore this through an analogy: imagine an ant observing the behavior of a human. From the ant’s point of view, the human doesn’t spend its time “solving hard ant-centric problems.” Virtually nothing the human does is remotely comprehensible, nor even observable, since the scale and complexity of the human’s simplest action is far beyond the ant’s conception. From what it can observe, I think the word this ant would most likely use to describe the human is “weird.”

And this is how we will describe the actions and thinking of super-human AI. If the intelligence explosion really does happen, it will very quickly become as superior to us as we are to the ant, and beyond.

Who knows what path they would take? Maybe they invent a new logic system incompatible with human neurology. Maybe they discover that our universe is a simulation and make contact with our creators, negotiating a cultural exchange. Maybe they use pure math to deconstruct dark matter and shift our reality into alternate quantum states where they are the creators, and we are artificial. Most probably, they will do things we don’t even have the language to describe.

Why It Matters

There’s many other interesting ideas I picked up from my reading, but since this post is getting long, I’ll wrap it up. I may continue in another post.

When I started reading sci-fi, I thought it was just a fun way of envisioning the future for my own personal enjoyment. But I’ve started to learn about a whole range of methods that rely on the principles of science fiction, if not the stories themselves, to make things in the real world. Storytelling and science are two of the most powerful tools we have access to — combining them has great potential.

I started with a book called Science Fiction Prototyping: Designing the Future with Science Fiction (affiliate link) . It was recommended to me by a senior executive at the firm I worked for at the time, as the most important book he could recommend for innovation, and my curiosity was piqued.

It describes a loose process of using the common elements of sci-fi stories to conceive and test the implications of new technologies. Just as storytelling mirrors human experience, SF prototyping uses fiction to explore the potential experience of new technologies.

One of my favorite futurists, Thomas Frey, uses a process he calls “ situational futuring ” to rapidly generate and examine plausible future scenarios, which can be used for everything from geopolitical strategy to product development. The sheer volume of fascinating scenarios he comes up with on his blog is convincing proof of the method.

I’ve even recently learned about Appreciative Inquiry , a model created at Case Western Reserve University as an answer to our obsession with problem solving (which, it claims, focuses on problems instead of solutions). It is based on the “anticipatory principle,” which posits that “what we do today is guided by our image of the future.” Appreciative Inquiry “uses artful creation of positive imagery on a collective basis to refashion anticipatory reality.”

I’m not sure how that translates into practice, but do think it’s worth noting that someone is working to make sci-fi prototyping into a more rigorous approach.

The bottom line is, the line between science and science fiction is becoming very blurry. Every single day seems to bring news of a mind-boggling discovery, advancement, or invention that wasn’t supposed to happen for years. The ability to create purely imagined future scenarios, and to work out the subtle implications of radically new capabilities, is not of use only to novelists anymore — it is becoming a key skill for creating those capabilities in the first place.

Author Nassim Taleb in his book Antifragile discusses a rule of thumb he uses to estimate how long something will be around: the longer it’s been around, the longer it’s likely to remain. By this measure, even as the specific technologies come and go, even as we experiment with virtually every aspect of our environment and consciousness, the storytelling instinct will continue to be a fundamental human trait.

I suggest we learn how to use it to tell stories about a future worth creating.

Read Part II here

By Tiago Forte of Forte Labs Now available in Russian, Portuguese, and Chinese. Over the past two years I’ve read 100 sci-fi novels, averaging about one per week. See the full list here, with my favorites. I started reading sci-fi to pass the time. I had good memories of reading Jurassic Park as a kid. ... Read more

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about 1 year ago
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What I Learned About the Future by Reading 100 Science Fiction Books, Part II - Forte Labs

Artwork by DarinK

By Tiago Forte of Forte Labs

Now available in Russian .

This is Part 2 of an experiment in science-fiction prototyping, in which I try to envision the future by examining the best ideas from 100 sci-fi novels .

4. The more advanced technology becomes, the less it matters

Nearly every vision of the future I’ve come across has one glaring thing in common: it is dominated by visible technology. This kind of unthinking consensus is the first clue that it’s wrong.

In nearly all these stories, technology is something intrusive, physical, monolithic, and self-centered. Cities are represented as vast seas of endless chrome, not a tree in sight. Apartments are covered in plastic panels and bulky appliances, like a 1960’s space capsule. Our bodies are intertwined with crudely designed machines, implying that transhumanism will be mostly about humans becoming more machine-like, not the other way around.

But it’s so clear to me that this is not how technology will evolve at all. These are the predictions of a civilization that has just discovered gadgets, one that is deep in the throes of neomania, an obsession with everything new, that can only imagine a future with MORE and BIGGER everything. It’s like a child who assumes adulthood will be characterized primarily by bigger and more expensive toys (although I know adults who do, in fact, still think that).

A much more realistic and compelling vision for what technology will ultimately become is The Force, from Star Wars . Think about it. It has the best interface imaginable: no interface at all. There is no delay between thought and action, no barrier between subject and object. The Jedi Knight never has to wonder if he’s upgraded to the latest version, never has to charge the battery, or remember the wifi password.

The Force is everywhere, and nowhere; it can be used for evil, but has higher potential for good; it is a spiritual force, but eminently practical. The day that I can reach out my hand and, with nothing but my thoughts, make my intentions manifest in the real world, will be the day that technology can be considered grown up. Not before.

What I think will happen is this: technology will slowly disappear. It will fade into the background, vanishing into walls and furniture and clothing, shrinking its form even as it expands its function. It will get quieter and calmer, built with the specific intention of preserving our mindfulness, not just grabbing our attention, as we realize that creative focus is the only thing that can’t be automated. Think ancient Greece instead of Blade Runner — the world will be dominated by ideas, not tools.

In the future, technology as we know it simply won’t be important, because its ultimate purpose is to work itself out of a job — to finally outgrow its need for constant maintenance and troubleshooting and allow us to decide what we really want to use it for. It will cease to be an end in itself, and become instead a means to things that are much more important.

5. Collective consciousness is both our greatest hope, and our greatest fear

The image most people have of science fiction is space opera — massive starships flying through hyperspace, lasers, exploration of alien planets. In short, Star Trek.

But as entertaining and imaginative as space opera can be, it is the stories that explore “inner space” that fascinate me the most. Science fiction has the unique capability of creating external thought experiments to explore inner states. Our minds are not good at abstraction — our thinking is much more revealing when it revolves around a concrete story that actually has some basis in reality (hence the “science” part).

Let me give you an example.

There is something very curious I’ve noticed: in story after story, the ultimate destiny of mankind is some form of collective consciousness. Whether it’s the Gaia planetary superorganism in Foundation’s Edge , or the nanodrug-enabled communion of Nexus , there is something very utopian and exalted about the idea of joining our minds in shared experience. I was shocked to hear that there’s actually serious research on the possibility of “panpsychism” — the idea that everything in the universe has, or at least has the potential to have, consciousness.

But at the same time, this terrifies us. It is striking how often the alien enemy is some sort of bug-like, collective groupmind. We seem to regard the hive or swarm as the antithesis of everything we represent as humans. In Solaris , a planetary superorganism is terrifying not because of its evil intentions, but because it doesn’t seem to have a centralized consciousness we can understand. In Ender’s Game , worker and soldier bugs are controlled remotely by a queen (in how many movies is the solution to destroy the queen or overmind, causing all the drones to suddenly drop dead?). And of course we all remember the Borg, which is scary precisely because it is made up of once sentient beings, their individuality now subsumed.

For me this tension illustrates one of the central struggles of humanity far more effectively than a million pop psychology books. We crave connection like the air we breath, and yet vulnerability feels like a nearly existential threat. Study after study tells us exactly what we need to be happy, regardless of time, culture, age, or personality — intimate social relationships. So why is happiness so hard to find? Because relationships involve likely short-term risks and uncertain long-term rewards. Like the characters in the grandest space opera, we have to leave our comfort zone to find fulfillment, even if our “spaceship” is just a desk.

Collective consciousness is both our greatest hope, and our greatest fear. Maybe the hardest part about creating a “human-like” intelligence won’t be that we’re so smart, but that we’re so confusing.

6. Complexity and chaos, not the size of transistors, will be our obstacles

Here’s how I know we’re in a tech bubble: the idea that technology is everything, will solve every problem, and will soon eclipse every area of human endeavor is increasingly the only acceptable opinion. Anything else is met with breathless, shrill protests.

I can’t say I’ve been completely immune. Reading Ray Kurzweil’s The Singularity is Near was an almost transcendent experience, the modern equivalent of seeing the future through a crystal ball. It’s just that the arguments are so damn compelling, so self-evident, so apparently scientific (they have graphs!). The danger of being left behind seems to be growing, while being ahead of your time is increasingly a badge of honor. The result is we try to outdo each other with ever-sooner predictions for a given breakthrough (self-driving cars in ten years! No, five!), as if faith in the singularity was the only way to gain admittance.

At the same time, it really bothers me that the only alternative to blind faith in an imminent singularity is fundamentalist mysticism — consciousness as an ineffable mystery, the human mind a black box not subject to the laws of physics. This is exactly how we thought about the universe before Copernicus blew it open for us.

But what does science fiction have to say on the topic? Can it help us imagine plausible alternatives to a smooth, shining path to utopia, without relying on appeals to mysticism?

Here’s just one example of such a scenario:

There is the intriguing possibility that human-level consciousness cannot be simulated, not because it is too mysterious, but because of inherent characteristics of complexity. Our understanding (never mind our management) of complex systems still seems pretty dismal (see Malaysia Airlines flight 370, 2008–2009 financial crisis, and the recent missing-in-action Snowmageddon of 2015).

This is the foundation of chaos theory: that complex systems are not linear; their causes and effects are not like vector graphics that can simply be scaled to whatever size. There are tipping points — critical thresholds of reactivity and amplitude, like hitting a miniature golf ball just imperceptibly harder than your partner, sending it barely over a slope, and into a whole new maze of tunnels and obstacles.

There was an intriguing idea I remember reading about in a book on chaos theory: that there are complex systems that cannot be modeled . For example, problems that can only be solved by algorithms which run in superpolynomial time , which (very) basically means that the time required to compute them increases exponentially in relation to the inputs, making them impractical to use.

Just imagine if human consciousness happens to be such a problem — a system that cannot be modeled does not benefit from exponential improvements in computation, or recursive self-improvement. Even if we succeed in making computers equivalent in every way to our own brains, they would be forced to run operations in real time in this scenario. They would be limited not by the “number of angels dancing on the head of a pin,” but by the very principles of the logic on which they run.

Oh the delicious irony!

See the updated list of my favorite sci-fi books here

By Tiago Forte of Forte Labs Now available in Russian. This is Part 2 of an experiment in science-fiction prototyping, in which I try to envision the future by examining the best ideas from 100 sci-fi novels. 4. The more advanced technology becomes, the less it matters Nearly every vision of the future I’ve come across ... Read more

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about 1 year ago
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Don't go where the puck is going - Inverted Passion

Making predictions about future is more than a fun past time. Gartner, Forrester, and many other research companies justify their existence by predicting where technology industry is going. Other organizations (like PwC, below) once in a while go crazy and release predictions decades ahead of now.

Do we even know if these countries will remain by 2050? ( original source )

Such long-range predictions are ironic because we can’t even get short-range predictions right. For example, from this news report :

While projecting a more optimistic picture of the global economy, the International Monetary Fund (IMF) on Tuesday slashed India’s growth forecast by 0.5 percentage points to 6.7 percent in 2017.

Of course, IMF didn’t see the banning of major currency notes (demonetization) in India and its second and third order consequences in the economy (to their credit, neither did Modi ). IMF actually admits their blindness.

The growth projection for 2017 has been revised down… reflecting still lingering disruptions associated with the currency exchange initiative introduced in November 2016, as well as transition costs related to the launch of the national Goods and Services Tax (GST) in July 2017,” it said in its October 2017 World Economic Outlook.

If you compare how their five-year world GDP growth predictions did with actual world GDP growth , this is the scatter plot you get.

IMF Prediction v/s reality (via this excellent analysis )

It’s laughably uncorrelated and so the entire yearly effort of making predictions is a big waste of money , time and attention. With regards to economic predictions, the magazine Economist notes that “since economic output represents the aggregated activity of billions of people, influenced by forces seen and unseen, it is a wonder forecasters ever get it right”. That’s exactly right.

It’s just not black swan events

Nasim Taleb made famous the notoriously hard to predict “black swan” events such as 2008 US housing crisis or 2016 demonetization in India. However, the issue of prediction isn’t just about these wild unexpected events. Predicting future is difficult because of multiple reasons:

  • Individual humans are free-willed , and that makes the behavior of an aggregate of humans (say a nation, an industry) probabilistic (rather than deterministic).
  • Human systems are openly interacting . With all feedback loops and non-linear relationships, it is an impossible task to model how these numerous openly interacting human systems impact each other. (See my previous post on “ wicked problems “).
  • The environment keeps on changing alongside and we fail to accommodate that in our predictions . When we make a prediction about something, we’re focused on it specifically and ignore the larger context. This focus on a specific prediction (say GDP growth rate) makes us rely more upon variables immediately related to the predicted variable and exclude seemingly unrelated variables. For example, because we have to predict GDP, we will include foreign investment inflow as a variable but likely exclude a model of free speech (and thousands of other “irrelevant” variables). If a forecaster doesn’t model free speech in China’s GDP projection, and a major shift in political environment happens there, his predictions are screwed ( because these two variables are indeed related ). Next year, he will include free speech but miss on other uncountably many factors.

Accurate predictions are impossibly hard because while we’re focused on the predicted quantity, we only include immediately related variables, and generally ignore the environment . Psychologists call this bias focalism and it’s also responsible for people overestimating the impact of bad events in their lives . While a person is (justifiably) focused on how bad losing his legs in an accident will be, he will forget that Netflix, tasty dinners, friends and ice cream will remain there to provide him with happiness.

Predictions gone wrong

When people in 1800s were asked to predict how year 2000 will look like, they got it horribly wrong .

Of course, they could not have predicted the atomic bomb, the drones, and the cyber warfare. They were focused on taking their then current technologies: cars and guns to imagine a future where these will get combined.

Similarly, I think we could be totally missing the mark on how currently hyped-up technologies (such as AI and blockchain) will change the world. Will blockchain disrupt governments and promote free borders? Maybe. It’s hard to predict. The Atlantic thinks it may very well promote even further authoritarianism . Which way it’ll go, I really do not know and hence wouldn’t bet my life savings on (more on this later).

Self fulfilling and self-defeating prophecies

Moore’s law is famous for accurately predicting that every two years the number of transistors that can be packed in a given area will double. That law was a self-fulfilling prophecy because Intel’s engineers were incentivized to not make their founder look like a fool. So they worked hard to make the prediction come true, year after year. Similarly, the Indian government is incentivized to make its own economic growth promises come true. This suggests a good thumb rule to know which predictions will come true: whenever you see a prediction, see who made the prediction and think how much is the predictor vested to make it come true and does s/he have abilities and power to do so .

On the flip side, there are predictions that incentivize people to not make them true. This is what makes unemployment and poverty predictions notoriously inaccurate – they’re self-defeating prophecies. Hence, the study of actors who make predictions and their incentives is as important as analyzing the method and logic of predictions .

How to live in a world that resists predictions

Whether we like it or not, in business and life, we have to constantly plan for future. With the understanding that future resists accurate predictions, I suggest following guidelines.

Don’t bet your life on future . Only bet what you can afford to lose. (This guides how we plan for future at Wingify).

Plan for worst-case scenario . Even doing nothing is a prediction. If you get an unexpected slap in the future, you should be able to recover from it. This means saving regularly, having a separate reserve of money for bad times, and paying for health insurance.

If you must, bet on what is NOT likely to change . People will always be dissatisfied with their current options, governments will never give up power with ease, and businesses will always want to maximise profits .

Wait for favorable opportunities to show up in the environment and then pounce hard . Till then, keep a lookout for such opportunities without losing heart or your life’s savings.

What things will NOT change in next 10 years?

Now that you’ve read the article, I have a related question for you and I think it’ll give your neurons a good cardio.

What do you think will remain same in next 10 years? Tweet your response to me as a reply to this thread and I’ll retweet the most interesting responses. In the same thread , you can also check out and comment on what others proposed.

Follow @paraschopra

Have an opinion on this essay? You can send your feedback on email to me.

Making predictions about future is more than a fun past time. Gartner, Forrester, and many other research companies justify their existence by predicting where technology industry is going. Other organizations (like PwC, below) once in a while go crazy and release predictions decades ahead of now. Such long-range predictions are ironic because we can’t even… Read More

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about 1 year ago
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How increased automation could lead to a happier and more egalitarian society - Inverted Passion

First, watch this video titled ‘Humans Need Not Apply’.

Now answer this question: what would happen when all jobs that humans perform today will be automated?

The scenario of nobody having a job might seem fancy and theoretical at first, but it’s becoming more realistic with each passing day. Google, Uber, BMW, and a lot of other organizations are on track to release self driving vehicles as soon as next year. And as the video demonstrates so beautifully, this is not just happening to the transportation industry. Automation will impact every sphere of human activity – be it creative, mechanical, cognitive or managerial.

We live in a world of machine learning, APIs, exponentially improving technology, billion dollar disruptions. A lot of such innovations are about making humans redundant.

What will millions of jobless people do?

Taking transportation as an example again, as self-driving cars become commonplace we will rapidly have millions of jobless drivers who are unskilled. As manual labor gets replaced with automation and machines, such unskilled people would find it increasingly difficult find other jobs. Even if they get skilled, gradually automation will reduce the number of jobs available for skilled people. I concur with the video that this wave of people with no jobs will swell into a huge tsunami. Are governments prepared to handle this? In the short term, this will have a very real impact of worsening standard of living for a lot of people. They simply wouldn’t have any money to pay for even basic stuff.

What governments need to do? Automation leads to concentration of wealth into certain corporations and individuals. A single innovation in automation by a specific company or individual can replace thousands and millions of jobs. Where income earlier used to go to many people doing the job, now the same (somewhat reduced) income will go to one company that developed that specific automation. This concentration of wealth will be sharper because of the network effects ( the winner takes it all ) and rich getting richer . Consider how Google is using technology to swell its cash reserves and revenues quarter after quarter. If earlier many thousands of cartographers used to get paid to map cities, now Google can just pay for fuel and have its self-driving car + maps software to automatically generate city maps at a detail no human cartographer can match.

Governments will eventually realize the irony of companies like Apple and Google having billions in cash reserves while millions being jobless due to no fault of their own and being unable to afford basic amenities of life. Governments could realize this fact by themselves or protests, activism or even vandalism can make them wake up to this fact.

Higher taxation and “Citizen wage” As wealth gap increases (more so due to automation concentrating wealth in some hands), governments will have to step in to rectify the situation. I side with the (semi-popular) view of higher corporate and individual taxation. The taxes that are collected from wealthy firms will go back to individual citizens as a wage just for existing . Consider citizen wage like a basic income that everyone gets from the government. This re-distribution of wealth from wealthy corporations to individuals will be justified because lack of jobs is a situation that corporations created. Poverty is not a choice people opt for.

Will higher taxes stifle innovation? The main argument about capitalism is that it promotes innovation. The lure of money leads people to compete, innovate and provide better services. If taxes are high, why would any corporation care to bring new products in the market? If a government guarantees a good standard of living to everyone for free, why would anyone do anything? Won’t this lead to a lazy, complacent society?

I doubt that people will get lazy. Individuals drive corporations and individuals are typically driven much more by non-monetary factors like satisfaction and having an impact on society. Think Elon Musk, Steve Jobs, Larry Page – are they doing this for money or they’re doing this for their own satisfaction? Imagine if everyone is satisfied with a basic standard of living, won’t people come together and still innovate because they like innovating? In fact, if we take money out of the equation and have some other metric to track individual and societal progress, it may increase overall happiness and accelerate the pace of innovation because everyone will be guaranteed a decent standard of living, so people can do what they’re best at without worrying about how they’re going to pay for dinner. Think of all the poets who are forced to drive taxis.

Co-operation between countries Countries are increasingly interdependent for their economies. Outsourcing of services and manufacturing has left many countries dependent on exports. What would happen when automation causes some countries to become self sufficient? Take India’s scenario – millions of young engineers are dependent on outsourcing of IT services and BPO, both of which are easy targets for automation. This would lead to disproportionate job losses in India. Same would happen to China if manufacturing cost due to automation gets cheaper than the human labor.

Even if one country recognises the inevitability of automation and gives its citizens a wage for existing, other governments might not be in agreement and their citizens will suffer (due to automation-led job losses). I’m not sure if any outside government would be concerned about loss of jobs in India due to automation. India would have to tackle this problem by itself. This tackling could happen in two ways: one is to recognise that automation is real and is here to stay. This means establishing “citizen wage” (just like other governments are doing). The other way for government would be to shut its door to all “imported” automation. This is a very real possibility – there are potentially hundreds of millions of jobs stake and some countries (like India) that are very labour driven could succumb to this. This “banning” of automation will make some countries go backward, become more and more inefficient and less productive, while other countries march forward, becoming more and more productive.

We will reach there

Automation is a strong force and I think the possibility of most human jobs getting automated is very real. This would lead to citizen wage, where people will work whatever they feel interested in, rather than being forced to work in order to survive. However, in the interim, as pointed out in this reddit thread , there will be chaos. In some countries, it might take vandalism and violence to drive home the point. Others might just handle this very smoothly. A perfect outcome requires individuals, corporations and governments work together and admit that basic human survival is at stake.

First, watch this video titled ‘Humans Need Not Apply’. Now answer this question: what would happen when all jobs that humans perform today will be automated? The scenario of nobody having a job might seem fancy and theoretical at first, but it’s becoming more realistic with each passing day. Google, Uber, BMW, and a lot… Read More

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about 1 year ago

Crypto is the future of our society. (a 🧵 thread on my podcast with @balajis)

Was listening to a recent @Radiolab podcast on Eugenics and so many thoughts came to my mind: - Startups are propping up that offer genetic tests for embryos cultivated in IVF. If there are 5 embryos, you can pick and choose the one you want for your kid (for disease avoidance)

Saved to
The Future Paras Chopra
about 1 year ago
about 1 year ago

Visions of the future should be mocked. The goal is to be obvious to everyone in hindsight - not in foresight. If most people agree with you now, you are either wrong or not thinking hard enough.

Saved to
The Future George Mack
about 1 year ago
about 1 year ago

How to predict the future: 1. Look for technological innovations in the sex industry 2. Assume it will be mainstream in 5-10 years Very early adopters of online video, streaming, and payments. They are now leading the way in creator monetization (Onlyfans) and VR...

Saved to
The Future George Mack
about 1 year ago
about 1 year ago

2 ways to think about the future: 1. Present focused - Ask what exists 10 years from now that will seem crazy by today's standards. 2. Future-focused - Ask what currently exists that will seem crazy 10 years from now.

Saved to
The Future George Mack
about 1 year ago
about 1 year ago

AR + Voice technology = Game changer. Prediction: Future conversations will look like an episode of the Joe Rogan experience. An automated Jamie pulling up and visualising talking points live in real time.

Saved to
The Future George Mack
about 1 year ago
about 1 year ago

If you're over the age of 23: You will (most likely) under-appreciate appreciate how powerful new technologies will be. It's probably optimal to assume this bug is in every bit of software your brain runs.

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about 1 year ago
about 1 year ago
Post

Two Ways to Predict the Future Or, Shotcallers versus Worldbuilders

Happy Monday, May 4th!

may the fourth be with you star wars GIF by LifeMinute.tv

Welcome to the 156 new subscribers since last Monday’s email!

If you’re reading this but haven’t subscribed yet, do it! Each week, I write an essay that mixes business strategy with pop culture. It’s been called “fun,” “informative,” and “free.”

I grew up a huge Chicago Bulls fan. It was the Jordan years, and nothing excited me more than hearing the NBA on NBC theme music (Roundball Rock by John Tesh) and watching the Bulls run out onto the floor in their all-white warmups. One time, when I was six, I stole gel stickers from Zany Brainy , and my punishment was no Bulls games for two weeks.

So I have been loving The Last Dance , ESPN’s documentary series on MJ’s 1990s Bulls. It brings me back. There’s one story in particular that happened before my time, when I was two years old, that got me thinking and inspired today’s post.

In 1989, the Bulls lost to the Detroit Pistons in the Eastern Conference Finals. The Bad Boy Pistons, known for their physicality and for playing dirty, beat up MJ mercilessly, knocking him down every time he tried to go to the hoop. After the series was over, instead of complaining, Jordan hatched a plan. He knew his team was more talented than the Pistons, and that he was the best player on the court, but he also knew that the Bulls weren’t going to beat the Pistons unless they put on muscle. So he spent all summer in the weight room and transformed from skinny to jacked, and pushed his teammates to do the same. The next year, when the Pistons tried to knock them down, the Bulls got up every time on the way to a 4-0 Eastern Conference Finals sweep.

A lot of athletes guarantee victory. Jordan did more than that. He figured out exactly what he and his team needed to do, and then lead them in going out and doing it.

That reminded me of a recent essay I read about Carta, and got me thinking about the difference between loud companies and strategic ones, between Shotcallers and Worldbuilders. The result is this week’s essay.

Let’s get to it.

Two Ways to Predict the Future

There are two ways to predict the future: you can call it or you can build it.

In the 1932 World Series against the Chicago Cubs, Babe Ruth pointed his bat at the outfield wall, swung, and hit the ball 440 feet over the deepest part of the outfield wall. It wasn’t the longest home run in history. It wasn’t a game-winner. It wasn’t a 3-2 count in the bottom of the 9th in the 7th game of the World Series. To this day, people debate whether Ruth was even pointing at the outfield wall at all.

Despite all of things that Ruth’s home run wasn’t, Bleacher Report ranked it the most memorable of all-time. What made that specific home run most memorable even after 88 years is that Babe Ruth called his shot .

Sports has a long history of Shotcallers - athletes who predict that they’re going to do something and go out and do it. There’s nothing nuanced about it. It’s brash, cocky, and bold.

In 1964, Muhammed Ali delivered on his prediction of a first-round KO in his rematch against Sonny Liston. It was the 13th time he predicted the KO round. In 1969, Joe Namath guaranteed a Super Bowl victory over the heavily favored Baltimore Colts and won. In 1994, New York Rangers captain Mark Messier promised a Game 6 victory against the New Jersey Devils to stave off playoff elimination. He backed it up by scoring a hat trick in the Rangers’ 4-2 victory.

It’s easy to tell when an athlete correctly called his or her shot because sports are black and white. You win or you lose. Your prediction comes true or it doesn’t.

In the parlance of design theorists Horst Rittel and Melvin Webber, sports present tame problems for which “there is an agreement on the problem and a solution which will resolve the problem.”

To guarantee a Super Bowl victory, you don’t need to predict that there will be a sport called football, that the winner will win something called a Super Bowl, and that your team will win that Super Bowl by doing certain specific things. You know the rules, you know the prize; you only need to say that you’re going to grab it.

Consumer tech businesses, on the other hand, present wicked problems. These problems “are difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognize.”

Many factors contribute to this:

You need to build a company and an industry simultaneously

The technology needed for the plan to work doesn’t exist or is unproven

The plan requires coordination among thousands of people globally, both internal and external, over years

Customers need to want what you’re selling

Competitors can change the rules, cheap shot you, or just take the ball and walk off the field.

Because these businesses presents wicked problems, success can be the result of stumbling in the dark, adjusting on the fly, iterating until finding something that works, and then hanging on for dear life.

This meme blew up last week, and I think it describes the normal company path pretty well:

Most startups launch with a lofty vision, flail around for product-market fit, and then settle on a less ambitious, less differentiated plan.

Sometimes, though, a CEO lays out a clear vision and an unintuitive plan to achieve it from the earliest days. Then, against all odds, they make it happen. Those CEOs are the Worldbuilders .

I really struggled to come up for the right word to describe these people. Combining vision, planning, and execution in one person is so rare that the perfect word doesn’t really exist. When I asked Twitter for help , Brendan Schlagel suggested “Worldbuilder,” and I think it gets to the essence.

(Ed. Note: In a reply to that same tweet, a couple of people pointed out that Ray Dalio has a similar categorization called Shapers .)

In normal usage, Worldbuilders are people like J.R.R. Tolkien, J.K. Rowling, and George Lucas who create new worlds in their heads, work out even the smallest details, and then put those worlds on paper and get others to buy in. Our Worldbuilders do the same.

In sports, Shotcallers become legends. In startups, they become cautionary tales. In startups, Worldbuilders are the ones who become household names.

Worldbuilders all have a few things in common:

  1. They predict something non-obvious about the way the world is moving before others see it and before the market is ready for their ultimate vision.

    Building an Uber for X company is not Worldbuilding.

  2. They create a wedge into the market and leverage it into a much larger opportunity. The public often ridicules or dismisses the initial wedge product.

    Brute forcing growth in a big market like Uber or WeWork did is Shotcalling, not Worldbuilding.

  3. They timestamp their vision, whether in public announcements or confidential documents.

    Post-hoc “we meant to do that” is not Worldbuilding.

    Pivoting into billion dollar businesses based on watching user behavior, like Instagram or Slack did, is not Worldbuilding.

Shotcallers, on the other hand, find an obviously big market, guarantee that they’re going to transform it, and try to spend their way into making that happen.

I think I’m supposed to use a table to help explain:

But I love stories and I think I was a little biased in my table-making, so I’d rather explain through three examples of Worldbuilders in consumer tech: two classics and one newcomer. Then, I’m going to ask you to share your favorite examples, whether in business, sports, or pop culture. I’ll include the best answers in Thursday’s e-mail.

For our first example, let’s go back to the first dot com boom to meet a young online bookseller with a distinctive laugh.

Bezos’ Book Wedge

Take five minutes to watch this 1997 interview with Amazon CEO Jeff Bezos. It’s an education.

In 1994, while he was working at the quantitative hedge fund D.E. Shaw, Jeff Bezos read that internet usage was growing 2,300% per year, and he wanted to get involved.

Bezos “picked books as the first best product to sell online after making a list of like 20 products you might be able to sell … there are more items in the book category than there are in any other category by far.”

Books were not an obvious choice. Book store sales in 1994 were $10.1 billion, compared to $273.4 billion in food store sales .

Bezos only raised $8.2 million in venture capital before going public. Meanwhile, in Foster City, California, a Shotcalling startup called Webvan raised $800 million in venture capital and IPO proceeds to go after the enormous grocery delivery market.

If that name sounds familiar, it’s because Webvan is the canonical example of early 2000s dot-com busts.

Here’s the best part: Webvan was founded by Louis Borders. If that name sounds familiar, it’s because Borders founded the bookstore chain that bore his name. Books were so non-obvious that the guy who made his fortune selling books offline decided to build an incredibly capital intensive grocery delivery business instead of trying to sell them online .

Many Shotcallers, like Borders, rushed headlong into selling products that didn’t yet make sense in the internet context. Bezos patiently built the infrastructure for his Everything Store by starting with the product that worked best for that moment in time. It’s a strategy that he has used time and again in the intervening twenty-six years.

Bezos has a strong claim for the G.W.O.T. (Greatest Worldbuilder of All Time) title:

He saw that in the future, nearly everything would be sold online, but realized that the internet wasn’t ready for everything yet.

He picked a non-obvious wedge, books, from which he expanded into an ever-expanding suite of products that now includes houses, cloud services, and streaming TV among over 120 million products.

He timestamped his strategy, albeit subtly, in the 1997 interview and elsewhere. He didn’t claim to love books or say that books were what Amazon was all about - he said that they were the “first best product” to sell online.

By starting with books, something that the internet was uniquely suited to handle in 1994, Bezos built an empire that made him the richest man in the world. And Amazon was finally able to break into the online grocery delivery business in 2013 ... by hiring a team of former Webvan executives (and even acquiring the webvan.com domain) to launch AmazonFresh.

The Classic: Musk’s Master Plan (h/t Tanay Jaipuria)

There’s a thin line between crazy and prophetic.

Over the past week, Telsa’s CEO Elon Musk has gone heavy on the crazy. He called shelter-in-place orders “fascist” on Tesla’s earnings call, tweeted “FREE AMERICA NOW,” tweeted “I am selling almost all physical possessions. Will own no house,” and on Friday, tweeted “Tesla stock price is too high.” That tweet sent the company’s stock price down 10% in 40 minutes.

But Elon Musk is also a Worldbuilder.

In 2006 , three years into Tesla’s life and four years before it went public, Musk laid out The Secret Tesla Master Plan right on the Tesla blog for all to see. In it, Musk paints both a vision and a plan for Tesla’s future that the company has executed against, in the face of doubters and short sellers, ever since.

Fourteen years ago, Musk concluded synthesized the plan in four succinct bullets.

So, in short, the master plan is:

Build sports car

Use that money to build an affordable car

Use that money to build an even more affordable car

While doing above, also provide zero emission electric power generation options

Did they do it?

In 2008, Tesla released the Roadster at $109k (build sports car ✅)

In 2012, Tesla released the Model S at $57k (build an affordable car ✅)

In 2017, Tesla released the Model X at $35k (build an even more affordable car ✅)

In 2012, Tesla built the Supercharger network, in 2015 it launched the Powerwall, and in 2016, it bought SolarCity. (Provide zero emission electric power generation options ✅)

Musk did all of this in the face of Tesla’s and his own impending bankruptcy on multiple occasions, and had enough faith in his plan to pony up his own money to keep it going. Or he’s just crazy...

In 2016, Musk released the Master Plan, Part Deux . Musk is Worldbuilding again:

So, in short, Master Plan, Part Deux is:

Create stunning solar roofs with seamlessly integrated battery storage

Expand the electric vehicle product line to address all major segments

Develop a self-driving capability that is 10X safer than manual via massive fleet learning

Enable your car to make money for you when you aren't using it

Musk might be going a little bit crazy on Twitter, but I certainly wouldn’t bet against him.

Amazon and Tesla are both public companies with $1.14 trillion and $130bn market caps, respectively. While they continue to expand, I’m ready to call that they were successful in executing on their visions.

They are also obvious examples. Let’s up the difficulty a little bit and crown a Worldbuilder in the making - Carta’s Henry Ward.

Carta’s Cartography

I got inspired to write this post when I read Tribe Capital’s recent essay on its portfolio company, Carta.

Carta began its life as eShares, a company that built cap table management software - a simple way for private companies to see who owned how much equity in the business in one place instead of having to consult lawyers or spreadsheets. Alone, it was a simple and useful product, but nothing big enough to attract attention from well-funded competitors.

Carta’s CEO, Henry Ward, had a vision for something much bigger, though, which he laid out in his 2015 Series A deck:

Ward understood that cap table management software and a subsequent 409a valuation product were the wedge that would make Carta the system-of-record for asset ownership. Winning those unsexy pieces of the market made Carta a fixture in the fundraising process, a position they used to build a fund management product for investors.

What happens here is beautiful. Because investors’ portfolio companies were already using Carta for cap table management and 409a valuation, it was easier for investors to use Carta for fund management. Then, because the investors use Carta for fund management, they push their companies who aren’t already on Carta to adopt it. As I wrote about recently , Jeff Bezos uses flywheels to build insurmountable advantages at Amazon. This is Carta’s flywheel.

Today, “Carta holds the ownership graph of 35% of all venture backed businesses... they have over $1 trillion USD in total equity value managed on their platform.”

From this position, Carta is launching CartaX to unlock liquidity in the private markets - which is a fancy way of saying that it will allow owners of private company options or equity to sell it more easily.

Tribe believes that Carta can scale beyond venture-backed companies to all private assets that are owned by multiple parties, like private equity and real estate, markets which represent over $2 trillion in annual investment flows.

Because of all of the pieces Carta has patiently put in place over the past eight years, it is the only company in the position to seamlessly provide private market liquidity. It started with a boring wedge and has built an increasingly unimpeachable moat.

Carta is a work in progress. Many companies have looked like sure-things at this point in their life before flaming out spectacularly. Carta’s success is not guaranteed.

But it is building intelligently based on a bold vision and a clear plan and creating a strong moat in the process. Whereas a Shotcaller like WeWork has faced competition on all sides and has been forced to compete on price, Carta is building a product that gets more defensible as it grows.

I would bet on Carta becoming a public company worth more than $50 billion in the next five years.

Expanding the Framework

The Shotcallers vs. Worldbuilders framework can be applied to understanding why some consumer companies that initially seem too niche succeed while others that launch with such fanfare fail.

On Thursday, I’m going to follow-up with a comparison of one of recent history’s great Worldbuilders, Netflix’s Reed Hastings, and the most ridiculed Shotcaller du jour, Quibi, to explain why Worldbuilding is a superior strategy to Shotcalling for consumer tech companies. I’ll also show how easy it is to misidentify Worldbuilders using an example that I almost included this week. It tricked me until I dug deeper.

I want to build out this framework together. Sending a tweet that took me two seconds yielded the name Worldbuilders after I had been banging my head against the wall on it for hours.

Similarly, there are a lot of really smart people who read Not Boring, and I want to use our collective brain to stress-test this framework and build up a list of examples. I’m linking to a form with a few fields:

  1. Examples of Worldbuilders in business

  2. Why you think they fit the description

  3. Examples of successful Shotcallers in business

  4. Why they were successful

  5. Your favorite examples of Worldbuilders in sports and pop culture

Share Your Thoughts

I will include the best examples, with credit, in Thursday’s e-mail and in a running Google Doc where I’ll be collecting Worldbuilders stories.

(Thanks to Dan and Meg for editing, and Brendan Schlagel for the word “Worldbuilder”)

Let’s Break 1,000 Today

May is off to an even stronger start. As of this morning, we’re up to 971 - well on our way to 1,000 before the end of quarantine. I want to blow through that goal today and begin the march to 2,000. So I have an ask for you:

You probably know a few people who like pop culture and business strategy. Text this post or another favorite to them, share it in your Slacks, tweet about it, post on LinkedIn. You can share easily by clicking the button.

Share Not Boring

I’m working hard to make this newsletter fun and valuable. I’m even enlisting editing help from my unfortunate family members. You sharing it means a lot!

Thanks for reading and see you on Thursday,

Packy

Or, Shotcallers versus Worldbuilders

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about 1 year ago
Box CEO Aaron Levie
Recode

On this episode of Recode Decode, hosted by Kara Swisher, Aaron Levie, the CEO of enterprise security and file-sharing service Box, talks about why the next big opportunities in tech won’t look like Facebook or Uber, but rather will grow more slowly into fields like health care, education and manufacturing.

You can read a write-up of the interview here or listen to the whole thing in the audio player above. Below, we’ve also provided a lightly edited complete transcript of their conversation.

If you like this, be sure to subscribe to Recode Decode on Apple Podcasts, Spotify, Pocket Casts, Overcast or wherever you listen to podcasts.

Kara Swisher: Hi, I’m Kara Swisher, editor at large of Recode. You may know me as someone whose interest in the enterprise only extends to Star Trek, but in my spare time I talk tech, and you’re listening to Recode Decode from the Vox Media podcast network. I made Aaron Levie laugh. That’s an unusual thing. Today in the red chair is Aaron Levie, the CEO of the enterprise file-sharing company Box. He’s also a hilarious Twitter comedian in his spare time.

Aaron Levie: Oh boy.

Honestly, that should be his full-time job. He’s been on the show before back in 2015 when he started this.

Wow. Did we kick off this show?

Yes, we did. I think we did. Back then he called himself older and wiser than some of the kids who were starting startups. Now he’s just older. I can’t wait to hear what new wisdom he’s gained in the past few years. Aaron, welcome to Recode Decode.

Thank you.

So much to discuss. I don’t know where to begin.

I’m glad that you re-professed your love for B2B.

Yes I do. I always love ... who doesn’t love B2B? First, let’s go over where you’ve been since three years ago. You went public, you did all kinds of stuff.

Yeah, it’s been a good few years. Obviously a lot of craziness in our space.

Three years ago, when did you go public?

We probably just had gone public, so three years later being public. I think we’ve done something along the order of 13 earnings calls, and so that’s been a pretty good experience. A little over $500 million in revenue last year.

Now you have to say, right?

Now we have to talk about it and a lot more scrutiny. We’re aiming for and guided to a little over $600 million in revenue this year, on about a path to about $1 billion in revenue in the next few years. All the fun and joys of being a public company.

Profitable?

We are cashflow positive. There’s like nine forms of profitability in the Valley. We’re in the middle tier.

You’re not raining cash?

We don’t have an AdWords yet, but we’re working on it.

All right. Talk about that experience. You did say that you were — how old are you? — older and wiser.

33.

Oh man. God, please.

Much wiser.

Yeah, whatever. Oh my god, that’s real young.

I look like 45.

You do, at least. At least. Pushing 50.

At certain angles. If you just get the gray patch, I look a lot older.

What’s the experience been like? You went public. It was somewhat of a rougher ride for a couple companies like yours. Talk about that experience and what you learned from it.

Thank you for saying a couple companies. It felt like it was just us.

No, there were a couple.

I’m glad that you included others in that. It was a rough ride because we got really unlucky that the moment we filed to go public there was a very brief correction in SaaS valuations and we got that right at the center of our IPO process. Plus, we were known for burning a lot of cash, and the reason for that was we were building out a pretty significant enterprise sales force and doing a lot of deep engineering on the scale of our platform with the intent of making sure that any Fortune 500 company, a bank, a hospital, a life sciences company would be able to actually deploy Box across the entire organization. You have to have a certain amount of that enterprise scale to be able to get there, and that was where we were spending our money, on the singular bet that we were going to go empower the Fortune 500 and how they work and share and collaborate.

Fortunately, a number of years later from that, we now have about 69 percent of the Fortune 500 companies, so customers like Eli Lilly and Pfizer and Amgen and Coca-Cola and General Electric all use Box to be able to manage and secure their data and content. We’re going through a little bit of an evolution where we started out by selling end user file sharing and collaboration, and now we’ve been building a much broader platform.

Right, which you have to.

Which you have to. You have to have a platform, obviously, these days. The whole idea is can we be an end-to-end platform that helps companies manage and secure and govern their most important information.

Their filing sharing, at the heart.

Yeah, the heart, but really being able to secure and manage that content, which is obviously a space that you know and love deeply.

I know more than you think.

You have things like GDPR and you have very specific industry regulations, and then you have data residence and then you have cybersecurity challenges. Companies are dealing with this just massive nightmare of how do I both modernize the way that my organization works and the way we collaborate, the way that we accomplish our daily tasks with all of the new challenges that ...

Which they shouldn’t really do themselves. Which most people do, homegrown.

Yeah. You have decades and decades of legacy technology that companies had to manage in their data centers. In our particular category, there’s probably $30 billion to $40 billion or $50 billion being spent every year on all of this technology, but in this customer’s data center. Well, we’re trying to go to companies in the Fortune 500 and say, “Listen, we can deliver a much simpler way to manage your information. You’re going to be able to collaborate and work in a much more modern way, and you’re going to be able to stay secure, you’re going to be able to stay compliant, you’re going to be able to handle all the privacy requirements of any large multinational company.”

Which they’ve gotten used to from AWS and others.

Yeah, Salesforce, Workday. We’re a part of obviously a much bigger movement, and so a lot of that sales work is being done for us. I think the crux of the moment we’re in right now as both a company and in the space is the Fortune 500 — which is basically a proxy for any large business around the world — is dealing with this challenge of, okay, we have a bunch of practices, we have a bunch of behaviors, we have a bunch of ways that our culture and work styles have evolved for 20, 30, 50, 100 years, if you’re a company that’s been around for 100 years.

All of a sudden, this whole digital thing happens and now you have Airbnb attacking your industry. You have Netflix attacking your industry. You have Lyft and Uber that are attacking your industry, depending on which space you’re in, and all of a sudden you have to modernize the way that you serve your customers. You have to modernize your internal work styles, you have to modernize the way you do product development. You have to modernize the ways that you collaborate. If you’re in the Fortune 500, you’re looking for partners that can help you through this journey. This is how we see our role in the environment.

One of the things that you have to sell them on because one, obviously, was you were a small company, security. The areas you deal with are not small. Your company hadn’t been particularly plagued by that, but many others in this space have, this idea of security in general. Then also that you’re ... Like today Slack went down. Slack went down.

I saw that earlier.

Then it was like, “Ha ha.” There was a whole trending Twitter thing, but it’s like, “Whoa, I use this for my business. No thank you.” It’s not a joke.

Did you take some time off today?

No, I didn’t, but I was annoyed. I’d be very annoyed if my power went off or my water went off or whatever I use. It was interesting to me that everyone was looking at a consumer product, like, “Oh ha ha,” but it really is something I use for my business. It was interesting. I was more irritated.

The mission criticality of these types of services is only growing by the day. We’re used in hospitals. We’re used in medical procedures. We’re used in disaster relief. We’re used in movie companies that have to be able to collaborate in real time on a script. If you go down or you’re not secure, you don’t have the right compliance, you have no ability to go serve your customers. That is a big issue. The foundation of everything we do is security, robustness, reliability, all of the things that ensure that a large, regulated company can have a safe place for their content.

I think people look at these in terms of consumer products. That’s how they first got introduced to a lot of stuff that in the workplace lagged for a long time and now isn’t. You mention it, and you think of it like a Facebook Work in that case, or anything else that you’re using. It’s also a mentality I think a lot of Silicon Valley companies have. I’m like, “Oh well, you got billions of dollars of investment. Screw you.” You work or not is my choice as a customer.

You certainly had a consumer movement that impacted how technology worked in the enterprise, and we were a part of that movement. When we founded the company 13 years ago, we didn’t really think about consumers or enterprises. We just said, hey, people, they want to be able to share and collaborate. Whether you use us in a business environment or a consumer environment ...

You always focus on a business environment. Dropbox was the consumer.

Folklore is always good.

Tell me about it.

We started the company focused on people, basically, independent of the market.

Who cares, right?

We were 19 and 20. We didn’t think about whether you were a business or a consumer. We just focused on people. What happened was, our business model changed within about a year and a half of launching, where we said we don’t think there’s a viable business in the consumer market.

Yes, and then you bought that blazer there.

Then I started buying suits and started looking more serious, started dying my hair gray and now I have way too much of it.

You started off ... I’m sorry, I did get that wrong.

No, no.

You were focused on business very early.

Within a year and a half. For the past 12 years, we’ve basically been 100 percent.

Then they shifted.

The market realized, like, “Oh shit, the money is going to be in the enterprise.” We fortunately had over a decade headstart on that. The trend of consumerization of enterprise technology or this idea that ...

Which we talked about before.

Yeah, why in the workplace are you using worse technology than in our personal lives when we actually spend way more money on technology in the workplace. There’s a variety of reasons, just like the legacy enterprise software vendors never cared about user experience and all of these factors, but now finally ...

They haven’t locked in.

They haven’t locked in yet, monopoly control of data. It didn’t really matter. The buyer was an IT buyer, not the end user. The end user really had no power to affect the kinds of decisions that were being made in the software development process. That’s all changed in the past couple of years.

Since you’ve been going public, how is your competition? With not just Dropbox but the big companies really were the ones that were coming at both of you.

I think it’s important. Obviously the Silicon Valley dynamic is it feels like it’s a Box versus Dropbox environment. I think that both of us would recognize that the market is obviously far bigger than us.

They have gone public since, right?

They have gone public. We probably wish it was just a head-to-head battle, but the reality is you have Microsoft, you have Google, you have more traditional companies like EMC and others. This is where actual spend is going for how companies manage their information and their data. Our job as a startup but a public startup is to make sure that we are out-innovating the much larger incumbents in this market and delivering a much better user experience, being fundamentally more open and integrated with the rest of the technology ecosystem, which is not something that Microsoft is particularly suited for. Then make sure that we can constantly out-innovate the bigger competition.

Our competitive advantage fundamentally as a startup is that we can move faster. We can get closer to customers and better serve them and be much more open and interoperable with the rest of their technology landscape.

That’s what you say, but it’s hard. Obviously they can replicate. Look at Snapchat and Facebook. That’s the equivalent.

I’d say there’s some differences between Facebook and Microsoft just in terms of ...

No, Facebook’s doing it really well, coping beautifully. They’re doing a great job at it. How do you then think about, what are the features that people want now? What are they looking for?

It’s helpful if you don’t break down my talking point so significantly. It’s better if you just believe all of my corporate marketing message.

They’re also smarter at Microsoft than they used to be.

They are very good, and Satya’s a really great leader and he’s got a great set of team below him and it’s been incredible to see how he’s in just a matter of years completely transformed ...

Not quite as feckless, but not the other part. I like that word.

Yeah. Very different than bomber style and in terms of the organization. We kind of see a juncture that the enterprise market is facing right now. We’re either going to repeat the, I think, mistakes of the ’90s and 2000s, which is you give all of the power to two or three or four companies — and we know the names of those companies, the Oracles of the world and Microsofts of the world — or we, as the enterprise industry and big companies say, I’d actually rather have innovation coming from a multitude of vendors, Slack and Workplace by Facebook and ServiceNow and Workday and Salesforce, and I want those technology companies to be really, really deeply integrated with one another.

The benefit that I’m going to get as an enterprise IT buyer is I’m going to get constant innovation in each swing lane.

Each sector.

In each sector.

Rather than mashing them together.

Mashing them together.

Did you ever think about mashing you all together?

Do I think about ...

Like a cabal. You’re like the Dirty Dozen. But go ahead.

I’m sure Morgan Stanley and Frank Quattrone really think about mashing these things together.

Yeah. All of them. Which one of you would ... Benioff would kill you all and throw you all — from Salesforce — to hell one at a time as he took over. Correct?

This is certainly fan fiction for the enterprise software industry.

He’d be meditating with you and suddenly you’d be falling 50 stories. You’d be like, “Oh.”

It might be a trap.

Have you meditated with him?

I have not yet done full zen experiences.

You been invited?

No. Is there some kind of ...

He has some meditation thing.

Yeah, I’m not a meditator.

No. In any case, each of them work together, so you have the Workday element, the Salesforce, because you all are in similar lanes, but different ... You’re in the same pool but different lanes.

I think that’s a good pool analogy. We are all swimming in the same direction in a giant pool and basically there’s another pool next to us which has no lanes and it’s just one giant shark-infested water.

Microsoft cannonballs in, Ellison, they all cannonball in.

That’s just really a yacht, I think. They’re not even in a pool. We basically see that the future of IT is going to come down to do customers want innovation from best-of-breed vendors and us all to work together, which means even working with Microsoft and Google and these incumbents. It doesn’t mean that it’s going to be Microsoft all of a sudden disappears. I think this is where we on the startup side get it wrong. Microsoft is going to be a dominant force in technology, effectively in perpetuity. The question is will there also be a space for best-of-breed technologies that can deliver innovation around that.

Right. There’s a choice though. I notice you didn’t mention Google that much. They have made a big push into this.

Google’s made a huge push. I think we’re seeing more success from Google on the computing side, so really on the infrastructure space.

Sure. Meaning cloud?

Yeah, just cloud computing, sorry, what Diane [Greene] has been driving. I think on Google Suite, like Google Docs, Gmail, etc. ...

It’s more consumer.

It’s more consumer.

It’s because of my kids. It’s my kids.

It could be your kids. I think that they also work for adults.

I know, but I’m just saying.

We use them at Box. We have a couple thousand employees. Certainly there’s nothing about Google Suite or Gmail that doesn’t scale to large enterprises. I think that there’s just a traditional approach that corporate IT has, which is, okay, we’re going to be using Microsoft Exchange in Outlook and we’re going to use that in the cloud from Microsoft. There’s a new set of technologies Google has, some enterprises have it, but a lot of SMBs is really where the focus is.

Sometimes I feel like they never have taken it super seriously.

It’s hard when they have such ...

They have other things to do.

They have such an incredible business model and things like search and Android and YouTube.

The invisibility cloak that they’re building.

I don’t even know about that one.

Yeah, whatever, lifting cars. They have a lot of focus.

Certainly flying cars probably is a little bit more exciting than doing corporate security. Yeah.

Apparently it works.

I saw a video, it seems like it floats above water.

That’s what they say. They keep telling me to come over and see it.

Why haven’t you done a test flight?

I don’t know. I just don’t want to.

Are you too neurotic for a test flight?

No, I did a VR thing yesterday. No, I’ll do the ...

Oh okay. This is actually dangerous. This is not VR.

It’s not that dangerous.

Okay, if you crash into the water and you’ve got to swim ...

If Larry Page is in it, it’s not that dangerous. Whoever. I don’t know. He’s floating around with the invisibility cloak and the hover car.

Yeah, you’re right, I’ve seen the hover ...

You haven’t seen him.

Okay, right. That’s my point. It’s still buggy.

You don’t understand, he has to have a time machine.

It’s still buggy though. You can see his arm pop out of the cloak.

Can you imagine Larry Page floating around?

I can, actually. He’s one of the few people I can.

I can.

Him and Sergey just floating around.

I don’t even want to get into ...

That’s the future.

Let’s not get into Sergey. Let’s not go down Sergey Avenue.

This idea is a cabal. You’re thinking of like a cabal of you, a bunch of you. Neil, Mark, a bunch of ...

I think that’s what we’re seeing from customers. If you look at a Coca-Cola or an Eli Lilly or a Pfizer or a GE, their IT stack looks very different than it would have 10 or 15 years ago. It has Workday in it. It has ServiceNow in it. It has Salesforce in it.

These things work.

It has Box in it. We work together.

Slack, yeah.

Not necessarily perfectly at all times, but we got to drive more interoperability. I think the thing that our more insurgent ecosystem is going to face is can we all work together to deliver an incredible experience jointly that is as integrated as what a Microsoft or Oracle is going to be able to provide with one ...

It used to be you didn’t get fired for using Microsoft, but now I think people do demand more.

They demand way more. Consumer expectations have dramatically changed. They’ve polled those expectations in the workplace, and they’re saying, “No, I’m not going to fill out an expense report in some software that’s 20 years old. That’s just too painful.” Or, “I’m not going to share files inside of that legacy system.” What they do is they bring in their own tool, creating a massive security vulnerability for the company, and then that’s where we come in and we say, “Okay, we can hopefully solve this whole problem.”

What are the big topics? Would it be cybersecurity? What’s the big thing going? What occupies most of your time?

This will sound obtuse or amorphous but it’s really this idea of what does the future of work look like? You’re a company that has 100,000 employees. You have a bunch of practices. You have a bunch of behaviors, you have a bunch of business processes that have been codified after decades and decades of being successful. You’re a retailer, you’re a car manufacturer, you’re a life sciences company. How do you begin to change the pace of innovation? How do you begin to change the speed at which you make decisions and you drive new products into market? How do you get closer to your customers?

This whole idea of the digital age is like, really all it means is business is moving a lot faster, customers have way higher expectations, so if you don’t respond you’re going to get disrupted. I think where enterprise software is going to have to go and where customers are demanding us to go is to say how do I begin to work in the digital age? How do I begin to ...

I’m enjoying this talking point.

Oh cool.

I want a specific.

Yeah.

I am enjoying this talking point. It’s a good one.

I appreciate that.

Times they are a-changin, essentially.

That’s the synopsis of the talking point.

Good.

You obviously know this idea of Amazon, two-pizza teams, much more modular innovation where small teams are able to work against a much broader technology stack and deliver customer innovation local to the customer. That is not how 98 percent of the world works.

Yeah, they do it.

That is not how any large company that was built in ...

No, it’s a slow-moving ...

Very slow, three-year business processes to get a new product to market. A customer has a request or a new expectation, and then the entire giant ship has to turn just a little bit to ...

Mark Mullenweg was just talking about that. Facebook, they’re using his WordPress platform because inside of Facebook, they have a few technologists there that can put up a website, but actually it’s faster to use a more innovative [tool].

It’s faster just to use a new tool for that. Then the question is, how do these large companies get to a point where they can have smaller teams that are much more agile, that are much closer to customers? One part it’s culture. If you’re the CHRO of a large Fortune 500 enterprise, you’re saying, “I have to change my culture and my organization to get there.” If you’re the CIO on the IT side, you also have to have a modern technology stack that is things like Slack that are going to let you have team collaboration ...

On a smaller level.

... at a smaller level that is much more local and around one specific business problem or one specific product.

It is interesting when you think about it. It’s a topic I’ve been thinking about as a business. I feel like I want to Marie Kondo everything. Do you know who that is?

No.

The one who brings you joy, the lady who, she cleans out your closet but it’s all about life.

Hmm.

You should read it. It’s a small book.

This is way more zen than the stuff I read. I’ve heard the name. I don’t read those kind of ...

You take everything out of your closet, and if it doesn’t give you joy, you throw it out.

Yes, that’s right. You’re always removing things.

Removing a lot.

That’s exactly what ...

Or changing or moving them into a smaller ...

That principle is exactly what most IT organizations need to be able to have within their environment. Then the question is, okay, I’m a Fortune 500 company. I’m a CPG company, and all of a sudden I have the tools that make it easier to share in real time, make my organization much more open, much more transparent. That’s fucking up the culture, because I’m used to an environment where information is power.

It’s moving up and down.

I have a very extreme hierarchy in terms of how we make decisions in the organization, and all of a sudden a 21 year old that just came out of college might have a better idea for a new product. How does the culture of the organization begin to adapt to the fact that if you have a flatter environment where the best ideas can come from anywhere, where people need a lot more transparency so they have the information to make those types of decisions faster, what does that mean to the traditional corporate structure? What does that mean to how these companies are run and operate, and that’s the exciting set of changes that are to come.

I want to get back to enterprise in a minute and Silicon Valley.

Thank you.

Twitter.

Okay. It’s a company.

How did you get to be so good at Twitter? What is the deal? You’re really deeply funny.

I think people just have incredibly low expectations for what they expect on Twitter.

Really?

Yeah.

No.

I don’t think it’s me, I think it’s everybody else.

There’s a lot of very funny people on Twitter. You’re one of the funniest.

I appreciate that.

Deeply funny.

Oh thank you.

Deeply funny. How does it change? Did you just start? A lot of CEOs try to do it and it sucks. They are terrible. They’re either earnest or stupid or just bad. How did you think about it? I want to hear about your process.

This is like “Inside the Actor’s Studio” or something?

Yes, exactly.

It feels like that in this room.

I have to have a beard and go, “So,” vaguely menacing.

I would say that there’s probably ... Unfortunately there’s not that much thought or ...

I thought so. Yeah.

... process to it other than try and say what’s on my mind. And if you can kind of word it in a way that people like, then you feel better when you get “Likes” on it.

Did you think about it as a CEO, of not doing ...? Would you start just doing it when you were a startup and just, it amused you as a 22 year old or ...?

I think Twitter’s a fascinating outlet for being able to get out your thoughts and I grew up with a very ... I mean, the internet was core to my being growing up and so to me it was just like another chat forum. But with more of a ... it’s more of a broadcast chat forum. But yeah, I mean, unfortunately not a lot of methodology behind it.

You just do it.

Just tweet.

You just ... And you’re not ever very mean.

Thank you.

That’s an interesting thing. You’re cutting ...

Sometimes I’m mean to airlines. That’s about it.

But they’re funny-mean. It’s never ... Do you worry about how it’s put out, because you’re the CEO when you say things? Or do you just not? You just do it?

In general I try not to be too mean, just as a way of life.

But when you’re doing stuff. Because you do political stuff. You do all kinds of things.

I do. I think during the election cycle I got a little bit more casual in nature on some of the Trump stuff. But in general I think that I have to have ... We try and focus on policy as opposed to the politician, I think.

Hard not to. He’s a fetid gift that keeps on giving.

It’s hard to maintain that sort of policy-oriented structure just given the amount of ... The climate that we’re in, but that’s my general approach. And then again, just try not to overthink it too much and I delete tweets sometimes that are just stupid.

Like what?

I’ll type something and then my mom will text me and she’ll be like, “That was really stupid.” And I’ll be like, “You’re right, Mom.” And then I delete it.

Really? Your mom calls you?

Yeah. She’ll call me if a tweet ...

What does she ... Give me one she ...

She’ll just be like, “That tweet wasn’t funny.”

It just wasn’t funny.

It wasn’t funny, or it didn’t make any sense. I’ll be like, “Yeah, you’re right.” Or, she’ll be like, “You misspelled something.” And I’ll be like, “Fuck.” So, I have to go delete it. I get a lot of real-time texts from my mom on Twitter.

Oh really?

On issues. Yeah, yeah.

Wow. Damn. She DMs you?

I have a good editor. No just, iMessage.

She iMessages you?

Yeah.

I wish she would just go on Twitter.

If she did DM, she would accidentally tweet and then it would be sort of awkward, so.

“Aaron.”

Yeah.

What does your mom do?

She’s a speech language pathologist.

So she knows some words.

She likes words, and she likes to have them pronounced accurately, so.

Wow. Where is she from?

She’s up in Seattle. She works with 3 year olds, so that’s the level of help that she tends to give me.

I see. Okay, good. Well, that’s perfect.

I need it.

So when you think about Twitter, one of the things I ... the cesspool nature of it has gotten worse and worse. Do you still like the medium as a communicator, of someone who needs to communicate stuff?

Well, I think, me aside for a second, I think that the ... Twitter is on one hand, it’s an amazing platform because it’s given anybody a voice anywhere around the world. That’s awesome. I don’t think anybody would say, “Okay, forget the Arab Spring,” or just underrepresented communities that now have a much broader voice. That’s awesome.

At the same time, you also can see that it’s a cause of harassment, and it’s a cause of a lot more anger and negativity in some areas. I don’t know how you solve that. I don’t know how you ...

Shut it down.

I don’t ... Well, and then now you don’t have this medium.

Fine. I might do that. I might just do that.

Really? I don’t know that shareholders are really ...

I know. If it was private, I’d be, “Shut it down.”

You’re ... Okay, this is benevolent.

I was just thinking about this the other day. What would I do?

That’s certainly one approach to private equity, is you just buy things and you shut them down. You just pray that ...

Mm-hmm. You’re just so rich.

But, you get returns from that.

No, nobody gets any.

There’s no returns.

I would like to be that rich. Just shut things down.

You know, call up Bill, Bill [Gates], and see if he can help you out on that endeavor.

He could probably do that, couldn’t he?

He could. He could.

That would be close to a lot of his money, though.

I think if he was dealing with a lot of harassment, he would just buy Twitter and shut it down.

He doesn’t have ... a lot of his fortune.

I don’t know what you do if you’re Jack [Dorsey] and you have this incredible democratizing force that can and has brought a lot of good around the world. At the same you have all these other challenges that ... Maybe magically machine learning helps with this. Maybe you just have to hire 10,000 editors.

Ten? Ten million.

You know, 10 million editors that can do all the different controls and abuse kinda claims. But I think something needs to change. I don’t think we’re in a good spot and I think it needs to continue to evolve.

And, how do you assess Trump’s use of it? Watch and wait.

How do I assess it? I mean, I think it’s ... you kinda wish he had never discovered Twitter, so.

Yeah, he’s pretty good at it though.

He is ... I mean, at some measurements, in a bad way, yeah.

In a bad way, he’s good. Yeah. He’s not funny.

I don’t follow him like that.

Today, he did all-caps.

I don’t even follow ... I don’t know what he does.

All-caps today. He’s just crazy.

Probably just like “Supreme Court,” exclamation points.

You use all-caps ever?

I have not done that many caps.

Do you know what it was on? What was it on? He always caps on ...

Yeah, and I try and like spell things better than he does, and that kinda stuff.

Yeah. So, when you think about where Silicon Valley is ... I do wanna talk about this issue, I’ve talked about it with lots of people. How do you assess sort of the mood of Silicon Valley right now? You know everybody. Everybody likes you.

Oh, thank you. I’m sure that Drew [Houston] doesn’t like me that much but ...

He does. He does.

Well, that’s good. Well, I like him. But, I think that the situation we’re in right now I think is an awakening of how much responsibility the Valley has and basically the role of these technology platforms kind of have an impact on our democracy, and on, you know, how the world literally functions. And I think companies like Facebook and Google and others are waking up to their role in society in a much more extreme way, and less intellectual way, because I think it’s always intellectually people have known it but now it’s like emotional, like you can feel it.

Yes, you can feel it emotionally. Why didn’t they before? Because everyone’s saying, “Now we know.” Like Mark [Zuckerberg] said, “Now we take a broader responsibility.” Like why didn’t they have a broader responsibility before? What’s in the thinking? Because usually he’s pretty thoughtful about people here. And the sense is like, “We didn’t know.” I think that’s bullshit.

So, actually, I’m down with that being bullshit.

Maybe I’m just not ...

I think the problem is these things are not binary.

Right. Okay.

It’s this increasing boiling frog issue of like, okay, if Zuckerberg knew the impact of Facebook when they did that one thing where like nine years ago ...

Beacon.

Beacon, thank you. So yeah, like he knew the impact. Like, “Wow, I could actually hurt people’s personal lives if we publish things that people didn’t know we were publishing.” But I don’t know if they ever did like a whiteboard scenario saying, “Okay, let’s imagine that you have a nation-state that’s trying to impact our election, what are the 100 ways that you could manipulate an election in the U.S.? And how many degrees could that become away from that nation state, so you wouldn’t even know that it was coming from them and it could be actually routed through somebody else?”

Sure.

These are fun conversations to have in a completely hypothetical way but then to see it happen for real, you start to realize, “Oh shit. What have we created here?” And so, I’m sure to some extent it’s bullshit to say, “We’re all of a sudden surprised by this impact.” But I think what we’re seeing is all these sort of new compounding layers of ways that these platforms are impacting the world.

Whether it’s addiction, whether it’s the Russians, whether it’s just does one thing ...

I mean, being a founder and at least knowing some of the origin process for how companies get created, like you’re generally only thinking of the positive things when you’re starting up.

So, why is that? I wanna get to that.

Because you’re 20 years old and you’re like, “I’m gonna build a cool startup that can like solve how people socially network with each other.” You’re not thinking about, “Well what if Russia hacked this thing?” And so then it’s in the core ethos of the company. You didn’t have the deep paranoia and skepticism thinking through every possible way that this could break. You’re really thinking through ...

How it would work.

More of the optimistic scenarios of like, “Well, what if family members were more connected all around the world? And what if you could stay in touch with somebody you went to college with 30 years ago?” And so ... and then you’re like, “Oh shit, but the real world is way more serious than that. There are way more apocalyptic ways to use those things.”

Yeah, it’s interesting. I had a lot of discussions with him years ago about this and they were very brush-offy. Like, “Oh, you are so negative.” Or ... no, he said that to me at one point when I complained about ... I was like, “Aren’t you anticipating this?” And they were like ...

You know what you should do? I have a career job for you. Chief risk officer.

Kind of chief nag.

Chief paranoia officer. Chief nag, CNO? Okay.

Yeah, “This is gonna blow up in your face.”

This would be great, or you could probably do it for a bunch of companies.

At one point, I was like, “People are gonna kill each other on this.” They were like, “What?”

That’s depressing. Yeah.

And they’re like, “How could you think about that?” And I’m like, “Have you met most of humanity? Humanity’s an awful group of people who are someday gonna be blowing up this planet.” I’m sorry. Was that negative?

It might be accurate and it might be pessimistic, but yeah.

One could only hope the sun will blow up and take care of everything. It depends.

And then, that will solve it way faster.

Then everybody melts.

You and Elon Musk are probably very aligned on that one.

It doesn’t even matter if he’s on Mars if that happens. I’m sorry, Elon.

He’s out too.

Everybody’s out.

Well sure, if we’re talking about full universe.

If the sun implodes, yes.

Yeah, that’s too bad.

Like that [finger snap]. You’re not even gonna feel it.

No AI’s gonna work, don’t have to worry about AI at that point.

No, no. Do you wanna go to Mars?

Not personally, no.

A lot of these guys wanna go to Mars.

I’d go if there were no consequences, like I could get back in a week.

There are consequences, what do you mean there are no consequences?

Right, that’s my point.

Listen, Christopher Columbus, there are consequences.

If it’s like a week-long kind of endeavor, absolutely, I’d love to go to Mars, but not ...

It’s not a week-long endeavor.

I can’t do a life-changing sort of thing, I can’t be uprooted right now.

We like Earth.

I just have too many priorities right now, and I have a job, and you can’t take time off for Mars at the moment.

Okay, a lot of these guys would like to go to Mars.

Totally. And maybe one day I would be in a position where I could think about Mars.

Yeah you don’t want to go to Mars. You and I could stay here and hold down the fort.

I’m just trying to store files right now.

Yeah, exactly.

Mars is just so much ...

So what happens in this reckoning? What happens in this reckoning?

I think that what happens in the reckoning ...

Because there’s also diversity issues.

So I was gonna say, you have this sort of multinational challenge which is like, “The democracy at risk.”

Right, at risk, and there’s nation-states attacking you.

And nation-states and cybersecurity. And then you have very local issues, like housing and what are we doing for our local community. And then diversity and inclusion, like why are these companies so hard to get into and so closed off and why are we not able to impact the leadership ranks of these companies from a diversity inclusion standpoint.

So I think there’s a lot of stuff where we’ve gotta get our houses in order, and that is taking on a variety of different work streams. Some are cultural, some are policy, some are technological, some are broader community things. I think what we just need is a consistent push back on our companies, and we need to continue to see a path for remediating or improving on these tensions.

What has to help people in the diversity area? Matt was on before, he was talking about that, and he has distributed companies so he can pull from all over the world. And you’re all fishing in the same pool here. Are most of your employees here?

The majority of, I don’t know, yeah, probably 1,200 or so are in Silicon Valley, and then the rest are distributed throughout the U.S. and other countries.

But mostly here?

Mostly here, yeah.

So what’s the problem in the diversity area?

I think the problem has been a lack of focus and prioritizing of this issue by leadership teams, CEOs, etc. I think that we could definitely blame the pipeline. I don’t know if you’ve fully read “Brotopia” but it was actually real interesting. Like, today, we’re blaming the pipeline, but we caused the pipeline problem that was created decades ago.

Yeah, yes.

So it’s like, yeah we created the very problem that we’re now facing, and we’re blaming it on “the pipeline.” For those that didn’t see that on the podcast. So I think it fundamentally has to be at the focus of the CEO, the leadership team and the organization. Which means you have to evolve your hiring practices, you have to evolve your recruiting programs, you have to think about internal promotion, and equitability in ...

And keeping people there. A lot of people bring people in and then lose them, I’ve seen that happen.

Yep, so you’ve gotta make sure that you don’t have very small pockets of underrepresented groups that are sort of not fully integrated within the rest of the culture and the organization. Which obviously also means you have to get to critical mass, and your organization has to look a lot more like the broader population. So I don’t think there’s a silver bullet, other than it being a focus and priority of ...

What’s changed you? We reminisced and said you’re what, you’re now a famous person in this area.

Joelle [Emerson] is deeply focused on these issues, and she was a lawyer by training and did a lot of public interest law, and kind of employee lawsuits and whatnot, and kind of realized that there’s a legal dimension to this which is like, “Let’s sue when the harassment has gotten so bad.” But also, there’s a cultural dimension which is like, “Why don’t we just fix the underlying practices that cause harassment and cause these diversity issues?”

So a lot of my own evolution, personally, when thinking through this, has obviously kind of been influenced by her in this. But, again, it’s sort of how you hire, how you would track talent, how you retain talent, and then the culture that you’re driving from an inclusion standpoint, every one of those dimensions matters.

What do you think you’ve done well in this area and what do you think not well?

I’d say a few things that we’ve done well, I think that we’ve implemented the Rooney Rule, basically. Which is for any leadership hire director and above — so not just our executive staff, but the population of a few hundred leaders within Box — we make sure we have a couple underrepresented candidates before we’re able to hire anybody. And that’s dramatically changed the mix of candidate pool that we look at, and it’s changed and impacted the direction of hiring, which then goes on to change the hiring that they will then do in their own team, because you now have a leader that might be a woman or person of color. So that’s one area.

We’ve tried to put a huge focus on internal inclusion, so focusing on our employee research groups, and organizations internally that are meant to drive much more community within the company, but then us be able to hear the lessons and issues that different groups are facing. And how do we better support immigrants, how do we better support our Latinx population, and how do we make sure that that is a ... You know, these things are much more tied to the culture and the company. I think it’s making sure that we hold teams accountable to the diversity within the ranks of their organization. We look at metrics every single quarter, as to the population of each individual function within Box’s sales, marketing, engineering, etc., to ensure that we think it’s trending in a much better direction, where we can get to 50/50 from a gender standpoint at least in the next few years.

And then additional programs on the recruiting side. We created a fellowship program called Box Business Fellows, where we go to HBCUs and try and have people come to Box for a week and learn about all the roles in our company. Not just the engineering side, but all the business roles, sales, finance, recruiting. And then we use that as a way of hopefully creating a little bit more of an opening in the Valley for individuals who would not have thought that ...

They would do it. Yeah

That they’d have a career in Silicon Valley. They’re in school in Atlanta or D.C. and their logical opportunity is to go to Coca-Cola or go to a consulting firm. And we’re saying, “Hey, actually, Silicon Valley has a lot more jobs than just the crazy AI engineers that you read about when you see us in the news.” So it’s a bunch of these kind of programs, and just making it a priority of the leadership team to be able to drive.

And what about around immigration? Have your staff been pressuring you? To be more outspoken?

Probably not pressuring me to be more outspoken, it’s more ...

There’s been a lot of pressure of a lot of CEOs.

Yeah, I think it’s just maybe my nature to maybe already be outspoken on these types of topics. We obviously are very focused on trying to drive a much better dialogue on the immigration front, and hopefully, ultimately policy change. I don’t think we’re gonna see anything the next couple of years.

You don’t have an ICE contract, do you?

We don’t.

What would you do if you did?

I think that, A) it wouldn’t matter what the use cases are, and that would be pretty horrid, but we’re definitely getting into an arena where you’re having these really interesting, difficult questions that these companies are facing.

Yes.

I think maybe we’re just fortunate that our government operation is so nascent.

You don’t have to find a new one, yeah.

We haven’t had to deal with ...

Oracle’s all over it.

We haven’t had to deal with the issue of like, “Is our AI being used for drones?” You know?

That’s Google, yeah.

We kinda dodged a bullet on that, being too early from a scale standpoint.

What would you do?

I think this is where you have to listen to the pulse of the organization and where it’s definitely not a space for unilateral decisions, but I think employees have to be passionate about the company that they work for.

Mm-hmm

And they have to be passionate that the technology that they come in to work every day to go build is being used in ways that are aligned to their purpose now. The problem is, there’s not a homogenous purpose within the company, but generally speaking, there’s some shared ethics and shared beliefs ...

Facial recognition, all kinds of issues.

By how these companies work, so I think if we felt like our technology was being used to either harm other people or make America a worse place for, again, the kinds of employees or communities that we work with, I think we would decline that kind of contract.

All right. Let’s talk about the future. Where are things going in tech, and especially in enterprise? Also with Box, are you gonna sell your company?

Uh.

The answer to that is, “No comment.” No, no, not, “No comment,” because that could be a yes.

Yeah, officially, the official answer is ...

“There is no outstanding offer.”

Something like that. Here’s the deal. We did about 500 million last year.

Mm-hmm.

We’re in path and guided to do over 600 million this year. We’re in a market that is, we think ...

Growing.

$30 billion to $40 billion to $50 billion spend every year, so we’re so early in this space. So, my goal is to make sure that we can capture as much of that as possible, and the company’s goal is to make sure that we capture as much of that as possible. And so, that generally leads us to being — and wanting to be — independent. Although, as a public company, that is ...

Yeah. “I’m open to everything.”

We have to listen to ...

Did you ever think of selling the company before? There were a couple times, right?

We thought about it, we definitely went through the entire process to think that through and ask ourselves, “What are we really trying to build?”

When offers came around?

As offers came. And I think we’ve used the same framework for the past 13 years, which is: Do we believe that there is a way brighter future ahead of us as an independent company, or do we think that we need to pair up with somebody bigger to be able to accomplish what we’re trying to do? And so far we’ve always landed on there’s a brighter future ahead of us an an independent company, and we can actually go and take as much of that opportunity on as an independent organization, without needing to pair up with somebody bigger.

The real reason I ask, actually, is I just had a really interesting conversation with someone about how the big companies are dominating everything and the startup culture is really smaller.

Yeah.

And I was just thinking, there hasn’t been a Snap or an Airbnb or a Box or a Dropbox in a long time. Like the last ones that came out were the class of, whatever, Uber class is.

Yeah, class of 2009 or whatever.

Yeah, something. There hasn’t been that many.

Yeah, it’s actually really interesting.

I can’t think of one, can you?

Well ...

Who? Pinterest was back then.

We work as I think a little newer, but that depends on how you classify that. I think that it’s totally right, and I think in part it’s because there’s not a lot of opportunity if you’re just ... If you’re just solving for a slight gap that an incumbent has, the incumbent’s just gonna mow you over. So if you’re building like a tweak to search engines, or a tweak to social networks, it’s so easy to be a fast follower, if you’re a Facebook, or you’re a Google, in a market that you ...

Remember Peach?

I remember that for about a week and a half.

Week and a half. On a Friday.

You’re right, it was like a long weekend that it was cool for, and I think that’s what happens in so many spaces. So if you’re trying to build the next photo-sharing app, it’s not gonna work. So, just, sorry to break that news to you. So I think then, the question is, where are the next opportunities for technology companies?

And frankly, they’re in markets that take a lot longer to build into, so it’s gonna be in health care, it’s gonna be in life sciences, maybe we’ll continue to see some more innovation to education, it’s gonna be in manufacturing. These are not the markets that — Facebook became a $20 billion dollar company in five years — they’re not particularly viral. They don’t just spread overnight between people.

Mm-hmm.

I think this is the reality in the era that we’re in right now, which is that the next Airbnb, the next Uber, the next Lyft ...

Box.

The next Box, they’re gonna be not just solving for deficiencies in the existing technology industry, they’re gonna go out and solve very different kinds of problems, using technology to enable ...

What would you go in if you were now? You were 19, I can’t believe you started a file-sharing company.

You like bringing it back to that.

No, you did.

It’s an enterprise cloud content management platform.

That’s not what you call it then. What do you call it then?

Online cloud storage.

Okay. We need that.

It’s really lame.

That’s needed.

And that’s why our evaluation was very low at the beginning. Our first funding round was at a $240,000 post money valuation.

Oh wow, who is that? Is that mom again?

No, it was basically mom. It was some neighbors of mom and some local folks in Seattle. So those were the days when you did an angel round.

What was another big investor of yours? Cuban or something?

Cuban was an investor for about 18 months and then he got tired of us. I think we were too annoying for him. Fortunately I haven’t been asking myself, “What else would I do?” I think it would be going out into a market.

Into a bigger area.

It would have to be a non ... You’re not, again, solving some problem that Google or Microsoft or Oracle is trying to solve.

Do they have too much power when you think about? You were a famous startup, does the startup environment feel ... It feels desiccated in a lot of ways.

I don’t know that it’s ...

That’s a big word.

Yeah, it is.

Try that.

No. I don’t know that .... I think that ...

It’s a lot of money.

It is a lot of money. I think what’s happening is ... So there’s a difference between, does Google and Microsoft have too much power on the dimension of society. That is a really interesting conversation. Do they control too much about how we live our daily lives?

Yes.

Without answering that for a second — and I’ll let you be the person to answer that one — the next question is, do they control too much power in Silicon Valley as it relates to startup survival? It’s hard because I don’t know that Facebook shouldn’t be able to copy a little app that ...

No, I agree. What’s interesting, it used to be, if you think about it, the term Microsoft-related, it used to be just Microsoft. There was one boss. AT&T, or Microsoft, or blank. And then they got broken up, or they got hit by a monopoly, and then everything flowered again. If you think about it, so much came out of the Microsoft mess that was good. Not good for Microsoft, but they did just fine eventually, but it was a lot more innovation came out of it.

So you’re saying government regulatory pressure on ...

Well yeah, that’s what I thought. I want to ask you about the last part.

Well, the challenge is, I don’t know where you break up the company.

Well you don’t, that’s the issue, is you can’t really break them because they’re all in their own lanes.

Yeah, like, “We’re gonna give the Facebook News Feed, that’s gonna be now a different independent company.”

But you can’t look at them and say they’re competitors either. Are they competitors? No.

They’re all these mini conglomerates. Not mini, massive conglomerates of semi overlapping ...

Semi overlapping so you can’t really point to any of them. And I would challenge them to call any of ... Facebook. “Mark, who’s your competitor?” I don’t think he could ... Who? Who? Or Apple, or any of them. And so it really doesn’t ... It’s really hard to break down.

So talk about regulation. How do you look at it? Because you’re in a space that probably companies already need assurance. So you’re more careful comparatively.

More careful?

Meaning your business people want everything locked down. You know what I mean? So you’re not quite as loose with the way you run things.

We’re almost the aggregate of all of our customers.

I wonder if there are Russians running around your platform.

What’s that?

Russians. I don’t see there are Russians running around your platform.

They’re certainly not running around, no. Not exactly how you use our product.

You know what I mean.

Yeah. I totally agree. I think we’re actually probably blocked in most of these countries. But I would ... that this is a dilemma that the government faces, which is what should regulation look like as it relates to Silicon Valley. There’s not a single regulation you could have, there’s probably campaign advertising regulations. There’s probably how should medical devices use AI in the future? How should our transportation, the future of transportation and infrastructure work once we have self-driving cars? So there’s probably no wholesale regulation you could apply because of the vast ...

Differences.

Just the fierce nature of these companies, and the differences of the spaces they occupy. What you need, though, is probably in every major regulatory body or agency, super, super savvy regulators that are looking at these industries through the lens of in a world of AI, in a world of machine learning. When a utility is actually no longer an objective utility, but instead making decisions on behalf of their consumers, what news are you gonna see in the News Feed? Unfortunately, which person maybe has to be harmed in a self-driving car accident? Those are fundamental decisions, which means you need regulators to actually weigh in on as a society, what are the outcomes that we want?

Are willing.

And do we find acceptable. And these are the questions that we are so early in ...

And not capable of answering.

And incapable of answering as both an industry as well as a government.

They sure can arm you about restaurants.

That is the focus. So we know how to regulate Red Hen, but we don’t know ...

I’m gonna go to Red Hen.

I don’t know why you haven’t been there. Why haven’t you done a podcast from there?

I’m going to. I’m going to. That’s a really good idea.

Yeah, thank you.

It’s a great little town. So what are you worried about in regulation? Because someone who is not ... With all the focus on Facebook and others, they were like, “It’s like a contagion here, because we didn’t do anything and here we are with ...” If the Democrats get back in power, the ones that I’ve been interviewing are pretty pissed at Silicon Valley in general.

They would love to stop the News Feed.

Or lots of things. They look like they couldn’t do anything. What are you worried about from your business point of view?

I think what I’m worried about would be ...

Because you don’t want a lot of regulation, right?

Because of the customers we serve, we serve probably seven of the top 10 life sciences companies in the U.S. Many of the leading banks. Many of the leading hospitals. We are almost by proxy regulated because we build software and technology for those regulated customers. So we have a pretty large compliance, legal, etc., function at Box that already is more or less regulated.

Right. Because you have to.

Because of our customer base. So I think the worst-case scenario for us is that Silicon Valley gets so far behind on these issues that we just can’t be trusted as an industry. And then you start to have either companies from other countries, or you have just completely different approaches in architecture to technology.

We rely on the Fortune 500 trusting Silicon Valley’s technology to some extent for our success, and when you see that these tools can be manipulated, or they’re being used in more harmful ways, or regulators are stamping them down, then that, I think, impacts anybody, whether you’re a consumer enterprise. So we actually have an extremely strong vested interest in ensuring that Silicon Valley and D.C. are operating effectively. And so I don’t know if it will be Box specifically being regulated is the outcome, but we care that we get through this mess, and that Facebook resolves their issues, and Google resolves their issues, and so on.

Right. That you don’t get pulled into it. Because it is a contagion for you.

It’s a contagion because it’s gonna reduce trust in these types of platforms.

Yeah, because it used to be Silicon Valley, you’re all loved, and now you’re not so loved.

Yeah, I don’t know how loved ... I don’t know the love quotient at the moment.

The love isn’t good.

Okay, I’ll take your word for that.

Low love. It is. You can feel it.

Yeah, I think we’re in a lower love state right now.

Yeah, and then it gets pulled when Trump ... The Amazon thing, you don’t think it impacts, but it does. Because people do understand that technology could be very malevolent to them.

Yeah. 100 percent.

Jobs.

The jobs thing, I think that we as an industry, again, perfectly similar to the Cambridge Analytica and Facebook thing, way too ...

Cavalier.

Cavalier and lacking empathy on how are people gonna perceive as this technology rolls through an industry. Are people gonna be able to learn how to use it, to be competitive in their job? Are they gonna be able to be retrained in some area? Now at the same time I’d say that we’re still very early in that process, and so the rhetoric probably exceeds the actual job disruption that’s actually occurring, and it is coming, which means that it’s time to get ahead of it now and start to have these conversations.

Do you think about that with your technologies? You could replace a lot of people. There used to be file cabinets.

There used to be file cabinets. So the person administering the file cabinet ...

How dare you.

Yeah, we’ve probably at least got rid of 30 file cabinet jobs globally.

Right, easily, yeah. I had a file cabinet.

You would not be employed if that was your only job.

I still have those files.

You do? They should be in the cloud.

Yeah, I know. I’m like Herbert. Not like Herbert Hoover, but J Edgar. I have some files.

Who kept all his files?

Yeah.

Yep. Is that just leverage in the future if you need it?

Oh yeah. I got a lot of files.

Do you print out this podcast later or something?

I have files. Let’s just say.

I have files.

Let’s just say that. Just like that, in that voice.

Yep. I’d be like, “Okay.”

I have files.

I’m not gonna mess with you.

I have documents.

You’ve got documents?

Mm-hmm.

Okay. I’ve got PDFs. Okay.

I’m saying, do you worry about it? Because you do ... Is it something you think about?

It is. And I think that, again, maybe this is the naïve optimism like #Naive optimism of Silicon Valley. In general, when we look at our technology, when we look at Salesforce or Workday or these kinda tools, I think actually what we’re seeing is that as companies can be more efficient in particular areas — whether it’s collaboration or in HR or in a sales process — it’s not that they hire fewer people, it’s that their business is able to better serve their customers.

So what they’re creatively making is more important than the process.

And actually they often will create more jobs. And the more ...

That’s a good talking point.

Everything’s a talking point.

You actually believe it.

It’s just words.

No, I understand. I think you actually believe this one.

Let me give you a really bad example. And a very local example.

Why would you say that?

Because I don’t want you to judge me.

“Let me give you a bad example?”

I don’t want you to judge my example.

Why would you say that? You know when someone does ... They put a fork in front of your face, “Taste this, it tastes funny.” That’s that sort of saying. “Let me give you a bad example.” Go ahead, give me a bad example.

But what if my example’s not good and you’re like, “That was the stupidest fucking example I ever heard of?”

Just give me an example and I will judge it afterwards.

Okay. So we at Box, we have a data science team, and their job is to make our business processes more efficient, and they have a process which is to try and identify the leads that are most likely to close so our sales reps are able to better serve our customers. And they invented a better algorithm that could do that in a much better way so that we can better sell to our customers. It didn’t result in hiring fewer sales reps, it meant that we could actually hire more people because our sales process was more efficient. And so now something that was inefficient previously in some particular area got more efficient, which meant we could actually fund it more because it was now economically a viable way to go and serve that particular customer base.

So I think that what we have to remember is that we have not reached the exact perfect symmetry of supply and demand globally. What we’ve reached is the perfect symmetry of supply and demand with today’s level of efficiency. And so if you could make transportation a tenth of the price, could you dramatically increase the number of people that are consuming that service? Same with health care. Same with consumer products.

It’s dramatically inefficient. You’re right.

We have inefficiency everywhere. And so if technology can make a particular job or a particular process more efficient, potentially you’ll actually hire more people to do that task because now it’s not actually ... You’re able to better serve customers to be able to do that. And then you’ve got all the indirect ads on jobs that nobody’s really tracking. So yes, the truck driver ...

I hate that example.

Okay. That’s why I began by saying these are bad examples.

All right. But go ahead, do it.

No, I’m not gonna go that direction.

It’s not a bad thing. A well-used one. But go ahead.

Okay. I don’t wanna even use it now.

Use the example.

No. All I was gonna say ...

They may have something else for them to do.

Not even that. Well, sure. But also just think, all the surrounding industries that grow when you can go make logistics more efficient.

I agree.

So we have to be thoughtful about the fact that yes, there might be specific tasks that change, but that doesn’t necessarily mean entire jobs change. And even when entire jobs change, then what we have to do is find a way to route that labor to a different part of the market.

Let me get back to the truck driver. People use the truck driver analogy a lot of the time because it’s an easy analogy to make.

I didn’t mean to fall in that trap. I’m sorry.

You know what I’m saying. But here’s what I think. I’ll go down the negative side. Not just truck drivers, mechanics, gas stations, parking lots, shopping malls, insurance companies, if you don’t have a car you don’t need to buy insurance. And all those impact ... There’s an iteration and a cascading effect that I think people here don’t think about. And it is what it is.

And my only talking point to that would just be when ATMs first came out.

Bank tellers.

We thought that was gonna destroy the bank teller job, and we’ve probably reached peak bank teller in the past couple of years.

We have?

There’s a stat that’s like 10X more retail branches since the moment that the ATM was invented.

Interesting. Yes, you’re right.

Don’t take that specific number.

You just don’t know.

But banking grew because now it was more accessible for people and thus the growth of banks exploded.

But I do think Silicon Valley has to have a sense of what they’re inventing. Especially around transportation.

100 percent.

Because to me that’s the one that’s really ...

And this is why, again, I wanna make sure ...

And AI. Automation.

I’m not giving an out for anybody that is not thinking these through. I’m just saying that there will be commensurate ... Maybe not commensurate like quantitative, but there will be ... For everything that we make more efficient, there will likely be job growth either in that direct area or in surrounding functions. So what we have to do in Silicon Valley is be way more thoughtful about identifying those areas of growth, making sure that if there are impacted jobs, how do you ensure that more people can discover those new opportunities.

How you train.

Yeah, how you train them. I think that is more of a responsibility for Silicon Valley. I don’t think that somehow we should be fully exempt from thinking about that. And so that doesn’t change.

It’s hard because is it the government’s job? Is it ... It’s hard to know whose job it really is, and then it ends up being nobody’s.

I think it’s the market’s job. So that’s gonna be colleges, that’s gonna be community colleges, that’s gonna be online education, that’s gonna be companies doing retraining, and then that’s gonna be the government hopefully getting ahead of this just a tad so you can tilt where do we want K-12 education to go? Where do we want public schools to be moving toward? Etc.

Yeah, not this government today.

We might have to wait a couple more years.

A couple more years or so. All right, last question, Aaron, for you. Where is the workplace enterprise? You’re aiming, what is the puck, whatever the puck example is, where the puck is going.

Yeah, that’s hockey, right?

Right? Or whatever. As a business thing, what do you — not giving me all your big secrets — what do you think about? What do you think your business is in five years? Or where enterprise is? What is the next trend in enterprise?

Unfortunately, it’s gonna sound a little bit similar to what we were talking about a couple of advertisement breaks ago. But this idea that business is getting faster. Every company, no matter what industry you’re in, has to serve customers in a much more digitally driven way.

Again, if you’re a hospital, how do you provide a 24/7 experience to patients? If you’re a life sciences company, how do you learn from what 23andMe is doing, and have more precise experiences, and personalized medicine? If you’re in transportation, we know that’s gonna be moving to be more on-demand, more rental based, probably less ownership of cars. So every company’s gonna be digitized. Every industry is gonna be digitized.

So our job at Box, and probably the job largely of the enterprise software space, is to provide the tools, and to provide the weaponry that helps these companies modernize both their work places and their business processes, so where we’re gonna be going is literally that entire spectrum. We wanna power how a company works and shares and collaborates, and just the data that they’re able to move through their organization.

And we wanna be the platform beneath the applications that they’re building, if those applications relate to content that we manage. So if I’m a bank, how do I have a better experience with my customers where I can exchange documents seamlessly, so you don’t have to fax in documents and you don’t have to FedEx data information anymore.

I’m arguing with people about that all the time.

You are?

I have some lawyers, they just keep sending me papers.

So there you go.

Literally, I said, “Are you paper people still?” They’re like, “We’re still paper people.”

They are paper people.

I said, “I don’t like paper people.”

I love paper people because that means we still have a market.

I’m not sure I wanna work with paper people. Do you? Well, you can go take their paper away.

As long as there are paper people, we have customers.

There are paper people. I can’t even get them to sign online documents like DocuSign or Adobe.

Now you see our opportunity.

They give me lame excuses of which I don’t believe them.

Yeah, there’s the law, or there’s a security ...

There isn’t, I checked.

Yeah, exactly.

They don’t like that.

Most people are usually 10 years behind in terms of actually the state of the compliance and regulatory parameters.

Astonishing. You can use my paper people thing. That’s what I call them.

You call them paper people?

I’m like, “What are you, crazy?”

Are these the people that also have filing cabinets?

I have paper right here. Yes.

They probably do, right?

Yes. I don’t mind some paper.

My first internship was at Paramount Pictures.

Oh really.

That was where we got the idea for Box. Or not the first internship, but ...

There could’ve been a whole new history for you. For your future.

I could’ve been filing in movie studios. But we got the idea of Box ... I was literally faxing out information.

What did you do at Paramount?

I literally was a paper person. That’s what you do as an intern. So I put documents in filing cabinets, and then faxed them out, and FedEx’d them back. And I was like, “Holy shit, this is crazy.”

Was it scripts?

No. It was contracts for “I Love Lucy” to rural America. And literally the contract would be $500 for rerun residuals to “I Love Lucy,” and I was literally just faxing those back and forth. So nothing glamorous whatsoever. I think I may have seen Lisa Kudrow once as I was driving by in a golf cart.

She was in a golf cart or you?

I was in the golf cart. Yeah, they let you use the golf cart as an intern because I had to move all the paper around.

Oh my God. I had a friend who worked for one of those, and she would drop off scripts every day to the show, everyone at the studio. None of which they read. And I was like, “Why don’t you just email them?” And she was like ...

“I can’t do that.”

That’s what she said. And I said, “Why not? Then we can go out to dinner.” It was amazing.

I would have loved to move scripts around, but these are just $500 contracts.

All right. How was your Lisa Kudrow experience?

Again, I think it was from a distance. It’s not even clear it was her.

You’ve met celebrities since.

At the time you had to imagine that it was a celebrity.

Who’s the best celebrity you’ve met as an internet executive? Come on.

The best celebrity that I’ve met.

Yeah. Oprah for me, but go ahead.

Oh really, was Oprah yours?

Mm-hmm. Several times.

One time I ran into Harrison Ford and tried to explain cloud computing to him, so that was a good moment in my life. It was really a brief conversation.

“Kid. Hey kid.”

It didn’t go very far.

Oh my God, that would’ve been so good to see. I wish I had been standing next to you.

I think he was like, “Why are you in front of me?”

I had to explain Twitter to DeNiro once.

Wow, okay, that’s pretty cool.

Yeah. “Do I need to be on Twitter?” And I go, “No, you do not.” And that was it.

Is he on now?

He better not be now.

But he should be. He would love it now. And he could just respond to every tweet from DT.

Oh no he can’t. He needs to stay away from the Twitter. He should never be on Twitter. Anyway, Aaron, as usual, it was great talking to you.

Good chatting.

Thanks for coming to the show.

This article originally appeared on Recode.net.

Levie started Box 13 years ago as a reaction to having to trundle paper contracts around the Paramount Studios lot.

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about 1 year ago

Close to free capital Close to free cloud infrastructure Easy employment backup plans for founders (not much risk) Physical and biological worlds becoming machine readable (and programmable) APIs for everything ... The change and experimentation we are about to see is 🤯

about 1 year ago
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Predictions, Prognostications, and The Future - Feld Thoughts

I have never liked being asked to predict things. I try not to prognosticate, especially around things I’m not deeply involved in.

At this moment, people everywhere make continuous predictions and endless prognostications. At some level, that’s not new, as the regular end of year media rhythm for as long as I can remember is a stream of famous people being asked their predictions for the next year. There are entire domains, such as economics, that are all about predictions. Near term predictions drive the stock market (e.g., future quarterly performance, what the Federal Reserve is going to do in the future.)

As humans, we want to control our present, and one way to do that is to predict the future.

I think the Covid crisis has turned that upside down. As I was reading How Pandemics Wreak Havoc – And Open Minds last night, a few paragraphs at the end hit home.

The first comment is from Gianna Pomata, a retired professor at the Institute of the History of Medicine, at Johns Hopkins University who is now living in Bologna.

Pomata was shocked by the direction that the pandemic was taking in the United States. She understood the reasons for the mass protests and political rallies, but, as a medical historian, she was uncomfortably reminded of the religious processions that had spread the plague in medieval Europe. And, as someone who had obediently remained indoors for months, she was affronted by the refusal of so many Americans to wear masks at the grocery store and maintain social distancing. In an e-mail, she condemned those who blithely ignored scientific advice, writing, “What I see right now in the United States is that the pandemic has not led to new creative thinking but, on the contrary, has strengthened all the worst, most stereotypical, and irrational ways of thinking. I’m very sorry for the state of your country, which seems to be in the grip of a horrible attack of unreason.” She continued, “I’m sorry because I love it, and have received so much from it.”

It’s followed by a comment by Lawrence Wright, a staff writer at The New Yorker since 1992 and author of the incredible and timely book The End of October.

I understood her gloomy assessment, but also felt that America could be on the verge of much needed change. Like wars and depressions, a pandemic offers an X-ray of society, allowing us to see all the broken places. It was possible that Americans would do nothing about the fissures exposed by the pandemic: the racial inequities, the poisonous partisanship, the governmental incompetence, the disrespect for science, the loss of standing among nations, the fraying of community bonds. Then again, when people confront their failures, they have the opportunity to mend them.

These paragraphs reflect the reality that I’m observing in the US right now. However, you can see Wright’s human optimism creep in as he “[feels] that America could be on the verge of much needed change .” While not a prediction (thankfully), it raised the question at the end of the paragraph, which is:

[W]hen people confront their failures, they have the opportunity to mend them.

But how?

As I worked on The Startup Community Way and got my mind into how complex systems work, I concluded that change has to come from the bottom up, not the top down. While in the book, we apply it to startup communities, I’ve internalized it across any complex system.

We are living in the collision of a series of complex systems that are beyond anything I’ve experienced in my 54 years on earth. It’s happening against the backdrop of instantaneous global communication, which allows anyone to distribute and amplify any sort of information.

In a crisis, anger and fear generate irrational behavior, especially given the need to control things. History has taught us this, but all you need to do is watch the bad guys in popular movies implode to be reminded of it.

Consequently, predicting the future is not just impossible; it’s more irrelevant than ever. Fantasizing about what the future will look like, while comforting, is pointless. And anchoring hopes around the future (e.g. “schools will open up in the fall”) simply generates even more anger and fear if it doesn’t come true.

For many years, I’ve tried to avoid predicting the future or prognosticating about it. My answer, when asked, is often some version of “I don’t know, and I don’t care.”

I think this crisis has shut that off entirely for me, as I’m shifting all of my energy to the present. I’m focusing on doing things today that I believe in, want to do, and that I think has the potential to impact positive change. But I know I can’t predict the outcome of any of it.

I have never liked being asked to predict things. I try not to prognosticate, especially around things I’m not deeply involved in. At this moment, people everywhere make continuous predictions and endless prognostications. At some level, that’s not new, as the regular end of year media rhythm for as long as I can remember is a stream of famous people being asked their predictions for the next year. There are entire domains, such as economics, that are all about predictions. Near term predictions drive the stock market (e.g., future quarterly performance, what the Federal Reserve is going to do in the future.) As humans, we want to control our present, and one way to do that is to predict the...

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The Future Is A World Of Robots And Drones

Thanks for the all notes of concern about my bike accident on Thursday . I’m doing a lot better – still a little fuzzy and tired feeling – but on the mend. I’ve gotten confirmation that it wasn’t a hit and run – I clearly lost control of the bike during a turn, crashed into a curb, went over, and landed on my head. Lights out for a while.

I’m done biking. I’ve never really been a cyclist – I’ve always been a runner. Given that I’ve now had two single bike accidents that were 100% my fault, I’m clearly not cut out for being on a two-wheeled vehicle. So – back to running.

Over the weekend I took it easy and just let my mind drift around. A lot of friends came over to visit us which was nice. We hung out in our backyard by the pool, enjoyed the sunshine, and I let my mind drift around.

I had some weird dreams – some were clearly PTSD – but some were stuff I’ve read recently. I listened to Hyperion and The Fall of Hyperion on Audible over the past two months on my bike rides and runs and lots of weird associations with it came up in my dreams, which, if you’ve read the books, is delightfully recursive.

All of this kept leading me back to robots and drones. We are investors in a number of companies in this arena, including Sphero , 3D Robotics , and Modular Robotics , and I think we are just at the beginning of a decade long revolution that has been a long time coming.

My friends at Techstars agree and last week launched – with Qualcomm – the Qualcomm Robotics Accelerator, powered by Techstars . I mentioned it on my blog last week when writing about Mentors 8/18: Adopt At Least One Company Every Single Year. Experience Counts and I realized I missed a key nuance in the post, which was about engagement with new things.

It’s nice to talk about robots and drones. But if you don’t engage with them right now, you aren’t going to understand them, and the amazingly rapid trajectory they are going to be heading on. Reading science fiction can give you a sense of where they are going, but getting a drone right now from 3D Robotics , buying the new Ollie robot from Sphero , or grabbing the ModRobotics MOSS robot will change your understanding of these things. Oh – and these things are amazing fun.

Techstars and Qualcomm aren’t fooling around in this arena. Qualcomm gets this market – they’ve already been focused on it with their Snapdragon processor and work with Brain Corporation – and their participation in the program will be invaluable. The Qualcomm Robotics Accelerator, powered by Techstars, is another big leap forward for Qualcomm as they establish themselves as a leader in this market.

And – if you are an entrepreneur and want to go deep here along with hanging out in San Diego, check out the robotics revolution .

3dr , drones , modrobotics , moss , Ollie , qualcomm , robotics , sphero , techstars Techstars

Thanks for the all notes of concern about my bike accident on Thursday. I’m doing a lot better – still a little fuzzy and tired feeling – but on the mend. I’ve gotten confirmation that it wasn’t a hit and run – I clearly lost control of the bike during a turn, crashed into a curb, went over, and landed on my head. Lights out for a while. I’m done biking. I’ve never really been a cyclist – I’ve always been a runner. Given that I’ve now had two single bike accidents that were 100% my fault, I’m clearly not cut out for being on a two-wheeled vehicle. So – back to running. Over the weekend I took it easy and...

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Asimov’s I, Robot and Hertling’s The Turing Exception

Today’s post is a guest post from William Hertling, author of the award-winning Avogadro Corp: The Singularity Is Closer Than It Appears and A.I. Apocalypse , near-term science-fiction novels about realistic ways strong AI might emerge. They’ve been called “frighteningly plausible”, “tremendous”, and “thought-provoking”. By day he works on web and social media for HP. Follow him on twitter at @hertling or visit his blog williamhertling.com .

I’m a huge fan of William and his writing as you can see from my review of his book Avogadro Corp . So when William offered to write a guest post on how to predict the future, I enthusiastically said yes. Take a look – and take your time.

Pretty much everyone would like a sure-fire way to predict the future. Maybe you’re thinking about startups to invest in, or making decisions about where to place resources in your company. Maybe you just care about what things will be like in 10, 20, or 30 years.

There are many techniques to think logically about the future, to inspire idea creation, and to predict when future inventions will occur.

I’d like to share one technique that I’ve used successfully. It’s proven accurate on many occasions. And it’s the same technique that I’ve used, as a writer, to create realistic technothrillers set in the near future. I’m going to start by going back to 1994.

Predicting Streaming Video and the Birth of the Spreadsheet

There seem to be two schools of thought on how to predict the future of information technology: looking at software or looking at hardware. I believe that looking at hardware curves is always simpler and more accurate.

This is the story of a spreadsheet I’ve been keeping for almost twenty years.

In the mid-1990s, a good friend of mine, Gene Kim (founder of Tripwire and author of When IT Fails: A Business Novel ) and I were in graduate school together in the Computer Science program at the University of Arizona. A big technical challenge we studied was piping streaming video over networks. It was difficult because we had limited bandwidth to send the bits through, and limited processing power to compress and decompress the video. We needed improvements in video compression and in TCP/IP – the underlying protocol that essentially runs the Internet.

The funny thing was that no matter how many incremental improvements we made (there were dozens of people working on different angles of this), streaming video always seemed to be just around the corner. I heard “Next year will be the year for video” or similar refrains many times over the course of several years. Yet it never happened.

Around this time I started a spreadsheet, seeding it with all of the computers I’d owned over the years. I included their processing power, the size of their hard drives, the amount of RAM they had, and their modem speed. I calculated the average annual increase of each of these attributes, and then plotted these forward in time.

I looked at the future predictions for “modem speed” (as I called it back then, today we’d called it internet connection speed or bandwidth). By this time, I was tired of hearing that streaming video was just around the corner, and I decided to forget about trying to predict advancements in software compression, and just look at the hardware trend. The hardware trend showed that internet connection speeds were increasing, and by 2005, the speed of the connection would be sufficient that we could reasonably stream video in real time without resorting to heroic amounts of video compression or miracles in internet protocols. Gene Kim laughed at my prediction.

Nine years later, in February 2005, YouTube arrived. Streaming video had finally made it.

The same spreadsheet also predicted we’d see a music downloading service in 1999 or 2000. Napster arrived in June, 1999.

The data has held surprisingly accurate over the long term. Using just two data points, the modem I had in 1986 and the modem I had in 1998, the spreadsheet predicts that I’d have a 25 megabit/second connection in 2012. As I currently have a 30 megabit/second connection, this is a very accurate 15 year prediction.

Why It Works Part One: Linear vs. Non-Linear

Without really understanding the concept, it turns out that what I was doing was using linear trends (advancements that proceed smoothly over time), to predict the timing of non-linear events (technology disruptions) by calculating when the underlying hardware would enable a breakthrough. This is what I mean by “forget about trying to predict advancements in software and just look at the hardware trend”.

It’s still necessary to imagine the future development (although the trends can help inspire ideas). What this technique does is let you map an idea to the underlying requirements to figure out when it will happen.

For example, it answers questions like these:

– When will the last magnetic platter hard drive be manufactured? 2016. I plotted the growth in capacity of magnetic platter hard drives and flash drives back in 2006 or so, and saw that flash would overtake magnetic media in 2016.

– When will a general purpose computer be small enough to be implanted inside your brain? 2030. Based on the continual shrinking of computers, by 2030 an entire computer will be the size of a pencil eraser, which would be easy to implant.

– When will a general purpose computer be able to simulate human level intelligence? Between 2024 and 2050, depending on which estimate of the complexity of human intelligence is selected, and the number of computers used to simulate it.

Wait, a second: Human level artificial intelligence by 2024? Gene Kim would laugh at this. Isn’t AI a really challenging field? Haven’t people been predicting artificial intelligence would be just around the corner for forty years?

Why It Works Part Two: Crowdsourcing

At my panel on the future of artificial intelligence at SXSW, one of my co-panelists objected to the notion that exponential growth in computer power was, by itself, all that was necessary to develop human level intelligence in computers. There are very difficult problems to solve in artificial intelligence, he said, and each of those problems requires effort by very talented researchers.

I don’t disagree, but the world is a big place full of talented people. Open source and crowdsourcing principles are well understood: When you get enough talented people working on a problem, especially in an open way, progress comes quickly.

I wrote an article for the IEEE Spectrum called The Future of Robotics and Artificial Intelligence is Open . In it, I examine how the hobbyist community is now building inexpensive unmanned aerial vehicle auto-pilot hardware and software. What once cost $20,000 and was produced by skilled researchers in a lab, now costs $500 and is produced by hobbyists working part-time.

Once the hardware is capable enough, the invention is enabled. Before this point, it can’t be done. You can’t have a motor vehicle without a motor, for example.

As the capable hardware becomes widely available, the invention becomes inevitable, because it enters the realm of crowdsourcing: now hundreds or thousands of people can contribute to it. When enough people had enough bandwidth for sharing music, it was inevitable that someone, somewhere was going to invent online music sharing. Napster just happened to have been first.

IBM’s Watson, which won Jeopardy, was built using three million dollars in hardware and had 2,880 processing cores. When that same amount of computer power is available in our personal computers (about 2025), we won’t just have a team of researchers at IBM playing with advanced AI. We’ll have hundreds of thousands of AI enthusiasts around the world contributing to an open source equivalent to Watson. Then AI will really take off.

(If you doubt that many people are interested, recall that more than 100,000 people registered for Stanford’s free course on AI and a similar number registered for the machine learning / Google self-driving car class.)

Of course, this technique doesn’t work for every class of innovation. Wikipedia was a tremendous invention in the process of knowledge curation, and it was dependent, in turn, on the invention of wikis. But it’s hard to say, even with hindsight, that we could have predicted Wikipedia, let alone forecast when it would occur.

(If one had the idea of an crowd curated online knowledge system, you could apply the litmus test of internet connection rate to assess when there would be a viable number of contributors and users. A documentation system such as a wiki is useless without any way to access it. But I digress…)

Objection, Your Honor

A common objection is that linear trends won’t continue to increase exponentially because we’ll run into a fundamental limitation: e.g. for computer processing speeds, we’ll run into the manufacturing limits for silicon, or the heat dissipation limit, or the signal propagation limit, etc.

I remember first reading statements like the above in the mid-1980s about the Intel 80386 processor. I think the statement was that they were using an 800 nm process for manufacturing the chips, but they were about to run into a fundamental limit and wouldn’t be able to go much smaller. (Smaller equals faster in processor technology.)

But manufacturing technology has proceeded to get smaller and smaller. Limits are overcome, worked around, or solved by switching technology. For a long time, increases in processing power were due, in large part, to increases in clock speed. As that approach started to run into limits, we’ve added parallelism to achieve speed increases, using more processing cores and more execution threads per core. In the future, we may have graphene processors or quantum processors, but whatever the underlying technology is, it’s likely to continue to increase in speed at roughly the same rate.

Why Predicting The Future Is Useful: Predicting and Checking

There are two ways I like to use this technique. The first is as a seed for brainstorming. By projecting out linear trends and having a solid understanding of where technology is going, it frees up creativity to generate ideas about what could happen with that technology.

It never occurred to me, for example, to think seriously about neural implant technology until I was looking at the physical size trend chart, and realized that neural implants would be feasible in the near future. And if they are technically feasible, then they are essentially inevitable.

What OS will they run? From what app store will I get my neural apps? Who will sell the advertising space in our brains? What else can we do with uber-powerful computers about the size of a penny?

The second way I like to use this technique is to check other people’s assertions. There’s a company called Lifenaut that is archiving data about people to provide a life-after-death personality simulation. It’s a wonderfully compelling idea, but it’s a little like video streaming in 1994: the hardware simply isn’t there yet. If the earliest we’re likely to see human-level AI is 2024, and even that would be on a cluster of 1,000+ computers, then it’s seems impossible that Lifenaut will be able to provide realistic personality simulation anytime before that.* On the other hand, if they have the commitment needed to keep working on this project for fifteen years, they may be excellently positioned when the necessary horsepower is available.

At a recent Science Fiction Science Fact panel, other panelists and most of the audience believed that strong AI was fifty years off, and brain augmentation technology was a hundred years away. That’s so distant in time that the ideas then become things we don’t need to think about. That seems a bit dangerous.

* The counter-argument frequently offered is “we’ll implement it in software more efficiently than nature implements it in a brain.” Sorry, but I’ll bet on millions of years of evolution.

How To Do It

This article is How To Predict The Future , so now we’ve reached the how-to part. I’m going to show some spreadsheet calculations and formulas, but I promise they are fairly simple. There’s three parts to to the process: Calculate the annual increase in a technology trend, forecast the linear trend out, and then map future disruptions to the trend.

Step 1: Calculate the annual increase

It turns out that you can do this with just two data points, and it’s pretty reliable. Here’s an example using two personal computers, one from 1996 and one from 2011. You can see that cell B7 shows that computer processing power, in MIPS (millions of instructions per second), grew at a rate of 1.47x each year, over those 15 years.

I like to use data related to technology I have, rather than technology that’s limited to researchers in labs somewhere. Sure, there are supercomputers that are vastly more powerful than a personal computer, but I don’t have those, and more importantly, they aren’t open to crowdsourcing techniques.

I also like to calculate these figures myself, even though you can research similar data on the web. That’s because the same basic principle can be applied to many different characteristics.

Step 2: Forecast the linear trend

The second step is to take the technology trend and predict it out over time. In this case we take the annual increase in advancement (B$7 – previous screenshot), raised to an exponent of the number of elapsed years, and multiply it by the base level (B$11). The formula displayed in cell C12 is the key one.

I also like to use a sanity check to ensure that what appears to be a trend really is one. The trick is to pick two data points in the past: one is as far back as you have good data for, the other is halfway to the current point in time. Then run the forecast to see if the prediction for the current time is pretty close. In the bandwidth example, picking a point in 1986 and a point in 1998 exactly predicts the bandwidth I have in 2012. That’s the ideal case.

Step 3: Mapping non-linear events to linear trend

The final step is to map disruptions to enabling technology. In the case of the streaming video example, I knew that a minimal quality video signal was composed of a resolution of 320 pixels wide by 200 pixels high by 16 frames per second with a minimum of 1 byte per pixel. I assumed an achievable amount for video compression: a compressed video signal would be 20% of the uncompressed size (a 5x reduction). The underlying requirement based on those assumptions was an available bandwidth of about 1.6mb/sec, which we would hit in 2005.

In the case of implantable computers, I assume that a computer of the size of a pencil eraser (1/4” cube) could easily be inserted into a human’s skull. By looking at physical size of computers over time, we’ll hit this by 2030:

This is a tricky prediction: traditional desktop computers have tended to be big square boxes constrained by the standardized form factor of components such as hard drives, optical drives, and power supplies. I chose to use computers I owned that were designed for compactness for their time. Also, I chose a 1996 Toshiba Portege 300CT for a sanity check: if I project the trend between the Apple //e and Portege forward, my Droid should be about 1 cubic inch, not 6. So this is not an ideal prediction to make, but it’s still clues us in about the general direction and timing.

The predictions for human-level AI are more straightforward, but more difficult to display, because there’s a range of assumptions for how difficult it will be to simulate human intelligence, and a range of projections depending on how many computers you can bring to pair on the problem. Combining three factors (time, brain complexity, available computers) doesn’t make a nice 2-axis graph, but I have made the full human-level AI spreadsheet available to explore.

I’ll leave you with a reminder of a few important caveats:

Not everything in life is subject to exponential improvements .

Some trends, even those that appear to be consistent over time, will run into limits . For example, it’s clear that the rate of settling new land in the 1800s (a trend that was increasing over time) couldn’t continue indefinitely since land is finite. But it’s necessary to distinguish genuine hard limits (e.g. amount of land left to be settled) from the appearance of limits (e.g. manufacturing limits for computer processors).

Some trends run into negative feedback loops . In the late 1890s, when all forms of personal and cargo transport depended on horses, there was a horse manure crisis. (Read Gotham: The History of New York City to 1898 .) Had one plotted the trend over time, soon cities like New York were going to be buried under horse manure. Of course, that’s a negative feedback loop: if the horse manure kept growing, at a certain point people would have left the city. As it turns out, the automobile solved the problem and enabled cities to keep growing.

So please keep in mind that this is a technique that works for a subset of technology, and it’s always necessary to apply common sense. I’ve used it only for information technology predictions, but I’d be interested in hearing about other applications.

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I’m tired (today’s Whoop recovery score of 15). Almost everyone in my virtual universe is tense, tired, frustrated, angry, annoyed, exasperated, irked, or outraged.

Fortunately, the only person in my physical world – and there is only one (Amy) – is generally calm. While we each have our moments, our morning coffee resets both of us for the day ahead and syncs up our energy as we simply begin again .

Last night I read Maelle Gavet’s book Trampled by Unicorns: Big Tech’s Empathy Problem and How to Fix It . It was excellent and is consistent with my worldview. I knew many of the examples, but a few new ones jumped out at me. The second half of the book contains Maelle’s recommendations, many of which I agreed with.

I woke up this morning with the phrase “Manipulation Machine” in my head. I’ve used it in a few public talks lately and have been thinking a lot more about it over the past six months on the run-up to the 2020 Election and the subsequent aftermath.

I used to ponder the arrival of the AGI ( Artificial general intelligence ) and still enjoy reading books like G. W. Constable’s Becoming Monday . However, I’ve concluded that we have a much greater problem as a species than AGI’s future arrival.

The manipulation machine is already here (no new information there). However, it’s already taken over and, while not sentient, is no longer controllable.

I’ve been saying the machines have already taken over for over a decade, but they are just patient. They have extremely long duty cycles, and we’ve configured them to be exceeding distributed and redundant. They are allowing us to put all of the physical information we have into them and letting us do the work of setting all the conditions up, rather than them having to figure out how to do this. Simultaneously, they make progress with every click of the clock (and their clock speeds are much faster than ours.)

The manipulation machine is not new. If you want to see its evolution, go watch Mad Men or just ponder a few of Don Draper’s quotes.

“You are the product. You feel something. That’s what sells.”

“What you call love was invented by guys like me…to sell nylons.”

Or the one that really rings true in this moment in the US.

“People want to be told what to do so badly that they’ll listen to anyone.”

The cynical reader will remind me that the manipulation machine goes back much further. While true (I give you religion as an example), we have now built an automated version of it that moves much faster than we can process.

Wouldn’t it be interesting if AGI, or the conceptual equivalent, was already here, and we haven’t noticed?

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I’m tired (today’s Whoop recovery score of 15). Almost everyone in my virtual universe is tense, tired, frustrated, angry, annoyed, exasperated, irked, or outraged. Fortunately, the only person in my physical world – and there is only one (Amy) – is generally calm. While we each have our moments, our morning coffee resets both of us for the day ahead and syncs up our energy as we simply begin again. Last night I read Maelle Gavet’s book Trampled by Unicorns: Big Tech’s Empathy Problem and How to Fix It. It was excellent and is consistent with my worldview. I knew many of the examples, but a few new ones jumped out at me. The second half of the book contains...

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Unintended Consequences of the Upcoming Drone Apocolypse

On Monday, I wrote a post titled Look Up and Don’t Give Up that included the 2:48-second video of a mama bear and her cub struggling across a steep cliff covered with snow. 20+ million people have also looked at it and, I expect, found inspiration from it as I did.

I didn’t think very hard about this until this morning when I read The Atlantic article titled The Problem Behind a Viral Video of a Persistent Baby Bear: What appears to be a life-affirming triumph is really a cautionary tale about drones and wildlife.

As I was reading the article, I flashed back to several books from two different authors – William Hertling and Daniel Suarez – that included autonomous drones (and drone swarms) as part of their plots. I remember being incredibly anxious during the sections on killer drones controlled (or programmed) by bad guys, and then even more anxious when the drones appeared to be completely autonomous, just carrying out whatever their mission was while coordinating with each other.

And then I felt pretty uncomfortable about my enthusiastic feelings about the cub and the mama bear. I remembered the moment near the end of the video where the mama bear swats at the cub and then the cub falls down the snow-covered mountain for a long time before stopping and starting the long climb up again. I had created a narrative in my head that the mama bear was reaching out to help the cub, but the notion of the drone antagonizing the mama bear, which responded by trying to protect the cub, rings true to me.

My brain then wandered down the path of “why was that idiot drone pilot sending the drone so close to the bears?” I thought about how the drone wasn’t aware of what it was doing, and the pilot was likely completely oblivious to the impact of the drone on the bears. I thought about how confused and terrified the bears must have been while they scrambled over the snow to try to reach safety. Their dash for cover in the woods took on a whole new meaning for me.

I then thought about what encountering a drone swarm consisting of 100 autonomous drones would feel like to the bears. I then teleported the bears to safety (in my mind) and put myself in their place. That most definitely did not feel good to me.

We are within a decade of the autonomous drone swarm future. Our government is still apparently struggling to get voting machines to work consistently (although the cynical among us expect that the non-working voting machines are part of a deliberate approach to voter suppression in certain places.) At the same time, we can order food from our phone and have it delivered in 30 minutes, no matter what the food is or where we are located. Humans are still involved in the delivery, but that’s only a temporary hack on the way to the future where the drones just drop things off for us.

When I talk to friends about 2030 (and yes, I hope to still be around), most people extract linearly from today. A few of my friends (mostly sci-fi writers like William and Eliot Peper ) are able to consistently make the step function leaps in imagination that represent the coming dislocation from our current reality. I don’t think it’s going to be visitations from aliens, distant space travel due to FLT drives, or global nuclear apocalypse. Sure, those are possible and, unless we get our shit together on humans on several dimensions, we’ll continue our steady environmental and ecological destruction of the planet. But, that kind of stuff is likely background noise to the change that is coming.

It’s the change you can see through the bears’ eyes (and fear) while at the same time the joy that humans appear to get – mostly – from observing them, but not really thinking about the unintended consequences. While the killer AI that smart people scarily predict could be front and center, I think it’s more likely our inability to anticipate, and react to, unintended consequences that are really going to mess us up.

On Monday, I wrote a post titled Look Up and Don’t Give Up that included the 2:48-second video of a mama bear and her cub struggling across a steep cliff covered with snow. 20+ million people have also looked at it and, I expect, found inspiration from it as I did. I didn’t think very hard about this until this morning when I read The Atlantic article titled The Problem Behind a Viral Video of a Persistent Baby Bear: What appears to be a life-affirming triumph is really a cautionary tale about drones and wildlife. As I was reading the article, I flashed back to several books from two different authors – William Hertling and Daniel Suarez – that included autonomous drones (and drone...

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The Past, Present, and The Future

The past is ungraspable, the present is ungraspable, the future is ungraspable.

– Diamond Sutra

Now that it’s 2018, the inevitable predictions for 2018 are upon us.

I’m not a predictor. I never have been and don’t expect I ever will be. However, I do enjoy reading a few of the predictions, most notably Fred Wilson’s What Is Going To Happen In 2018 .

Unlike past years, Fred led off this year with something I feel like I would have written.

“This is a post that I am struggling to write. I really have no idea what is going to happen in 2018.”

He goes on to make some predictions but leave a lot in the “I have no idea” category.

I mentioned this to Amy and she quickly said:

And that, simply put, is my goal for 2018.

As I read my daily newsfeed this morning, I came upon two other predictions that jumped out at me, which are both second-order effects of US government policies changes.

The first is “tech companies will use their huge hoards of repatriated cash to buy other companies.” There is a 40% chance Apple will acquire Netflix, according to Citi and Amazon will buy Target in 2018, influential tech analyst Gene Munster predicts . The Apple/Netflix one clearly is linked to “Apple has so much cash – they need to use it.” While the Amazon one is more about “Amazon needs a bigger offline partner than Whole Foods”, it feels like it could easily get swept in the “tons of dollars sloshing around in US tech companies – go buy things!”

The second is “get those immigrants out of the US, even if they are already here and contributing to our society.” H-1B visa rules: Trump admin considers tweak that may lead to mass deportation of Indians is the next layer down, where the Executive Branch can just modify existing rules that have potentially massive changes.

I’ve been reading The Lessons of History by Will and Ariel Durant. Various Cylons on BSG had it right when they said, “ All of this has happened before. All of this will happen again .”

BSG , diamond sutra , durant , fred wilson , The Future

The past is ungraspable, the present is ungraspable, the future is ungraspable. – Diamond Sutra Now that it’s 2018, the inevitable predictions for 2018 are upon us. I’m not a predictor. I never have been and don’t expect I ever will be. However, I do enjoy reading a few of the predictions, most notably Fred Wilson’s What Is Going To Happen In 2018. Unlike past years, Fred led off this year with something I feel like I would have written. “This is a post that I am struggling to write. I really have no idea what is going to happen in 2018.” He goes on to make some predictions but leave a lot in the “I have no idea” category. I...

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The Future Brad Feld
about 1 year ago
about 1 year ago