Understanding four trends that may shape the future of Silicon Valley is also a road map to some of the biggest technology-enabled opportunities of the next decades:
- Consumer internet entrepreneurs lack many of the skills needed for the life sciences revolution.
- Internet regulation is upon us.
- Climate response is capital intensive, and inherently local.
- The end of the betting economy.
…coronavirus pandemic, or something worse, had long been predicted, but it still caught the world unprepared, a better future not yet invented. Climate change too has been on the radar, not just for decades but for over a century, since Arrhenius’s 1896 paper on the greenhouse effect. And it has long been known that inequality and caste are corrosive to social stability and predict the fate of nations. Yet again and again the crisis finds us unprepared when it comes.
1. Consumer internet entrepreneurs lack many of the skills needed for the life sciences revolution.
…the inventions we most urgently need will take us in a very different direction than the consumer internet and social media revolution that is coming to an unsightly end.
We are starting to see the payoff of radically new approaches to biomedical innovation, and in particular, the way that machine learning is turbocharging research.
Prediction: The nexus of machine learning and medicine, biology, and materials science will be to the coming decades what Silicon Valley has been to the late 20th and early 21st century.
Why might this mark the end of Silicon Valley as we know it?
First, the required skills are different. …The hubs where that knowledge can be found are not the special province of Silicon Valley, suggesting that other regions may take the lead.
Second, many of the markets where fortunes will be made are regulated; navigating regulated markets also takes skills that are conspicuously missing in Silicon Valley.
Finally, …it is harder to sustain a hype balloon in a scientific enterprise than in many of the markets where Silicon Valley has prospered. Many Silicon Valley investors have been lucky rather than smart. They may not do so well in a world where capital must be directed toward solving hard problems rather than toward winning a popularity contest.
2. Internet regulation is upon us.
The opportunity of machine learning in scientific R&D is profound. But machine learning also challenges our current approach to science, which relies on human theorizing and experiments. A machine learning model may be able to make successful predictions but not to explain them. … As Judea Pearl has noted, excessive identification of correlations (i.e, “curve fitting”) makes the definition of authentic causal relationships more challenging. And “real science” needs causal relationships.
…without a better understanding of our machine helpers, we may set them down paths that take us to the edge of a cliff, much as we’ve done with social media and our fractured information landscape.
…internet pioneers expected freedom and the wisdom of crowds, not that we would all be under the thumb of giant corporations profiting from a market in disinformation. What we invented was not what we hoped for.
…The US theory of antitrust has largely been based on the question of consumer harm, which is difficult to prove in marketplaces where services are provided to consumers at zero cost and where the marginal cost of experimenting on those consumers is also close to zero.
The emerging European regulatory effort is properly focused on the role of dominant tech firms as “gatekeepers.”…the processes for assessing harms will most likely proceed more slowly than the harms themselves.
Markets are ecosystems, and like other ecosystems, there are hidden dependencies everywhere. The harm of Google abusing its monopoly position will not show up first in harm to consumers, but in depressed profits, decreased R&D investment, and lower wages at the web companies to whom Google once directed traffic. …because the pain is widely distributed and because the platforms are not required to report the information that would make it visible, the problem will not be obvious until much of the damage is irreversible.
…“superstar firms” ruthlessly compete with smaller firms that come up with fresh ideas, not only starving them of talent but often introducing copycat products and services, there is decreased innovation from the market as a whole. Cities are dominated by a new class of highly paid big-company employees driving up housing costs and forcing out lower wage workers; wages and working conditions of workers in less profitable industries are squeezed to drive the growth of the giants. Their very jobs are made contingent and disposable, with inequality baked in from the beginning of their employment. Governments are starved of revenue by giant companies that have mastered the art of tax avoidance. …
In the case of social media platforms, manipulation of users for profit has frayed the fabric of democracy and the respect for truth. …
Technology is far from the only offender. It is merely the most visible mirror of our values as a society. The extractive behavior the tech giants exhibit has been the norm for modern capitalism since Milton Friedman set its objective function in 1970: “The social responsibility of business is to increase its profits.” …generosity of open source software and the World Wide Web, the genius of algorithmically amplified collective intelligence are still there, pointing the way to the Next Economy, but it is an economy we must actively choose, rather than riding the rails of a system that is taking us in the wrong direction.
Prediction: Because platform businesses have failed to regulate themselves, they will have limits placed on their potential for good as well as harm.
It’s a sad time for Silicon Valley, because we are seeing not only the death of its youthful idealism but a missed opportunity. Paul Cohen, the former DARPA program manager for AI, made a powerful statement a few years ago at a meeting of the National Academy of Sciences that we both attended: “The opportunity of AI is to help humans model and manage complex interacting systems.”
That statement sums up so much of the potential that is squandered when firms like Google, Amazon, and Facebook fall prey to the Friedman doctrine rather than setting more ambitious goals for their algorithms.
I’m not talking about future breakthroughs in AI so much as I’m talking about the fundamental advances in market coordination that the internet gatekeepers have demonstrated. These powers can be used to better model and manage complex interacting systems for the good of all. Too often, though, they have been made subservient to the old extractive paradigm.
“The difference between theory and practice is always greater in practice than it is in theory,”
So many of the problems that antitrust actions and other regulations are now gearing up to address are, paradoxically, the result of the prime directive by which our economic and legal system governs its corporations: “Thou must maximize profits.”
…some formal experimentation on emotional contagion and reflection on its implications would have been a good idea. Instead, we continue to run global-scale unsupervised experiments on the power of social media to spread negative emotional contagion for profit, while any effort by the platforms to influence their users in positive directions is still considered by many to be inappropriate intervention, or is abandoned because it might reduce user activity and growth. …Facebook engineers reportedly trained a machine learning algorithm to recognize posts that their users would consider “bad for the world,” but the company found that showing fewer of them reduced the number of user sessions and thus, presumably revenue and profits. So they retrained the algorithm to find the point where “bad for the world” posts were reduced but not by so much that they impacted user sessions. …
“Shareholder value” is so ingrained in corporate governance that a special class of corporation has been defined to protect companies that are managed to take other considerations than profit into account. All “normal” companies are expected to treat employees, the environment, and society as costs to be minimized, avoided, or eliminated.
Silicon Valley can still lead in this effort. The big platforms must understand their social responsibility to create more value than they capture, focus their algorithmic systems on improving human welfare, find ways to measure and communicate the value that they create, and help our broader society to better “model and manage complex interacting systems.”
The danger of regulatory response that simply tries to turn back the clock and doesn’t take into account the ways technology done right could point the way forward is illustrated by the battle over California’s Proposition 22. …Traditional labor protections and benefits assumed a world in which individuals worked for a single employer. … The gig economy companies have made some small steps toward flexible benefits on their own, but they are a pale shadow of what they might have been if the companies and their gig workers and their customers, not to mention their regulators, had been working together to build systems that would allow benefits to be managed as dynamically as employment. …As I argued five years ago in “Workers in a World of Continuous Partial Employment,” we need a much more robust benefit system that is centered on the worker, not on the company.
3. Climate response is capital intensive, and inherently local.
The recent news that Elon Musk is one of the world’s richest people is also a harbinger of the biggest opportunity of the 21st century: to avert climate change. Electric vehicles are the tip of the iceberg. Heating and cooling, agriculture, raw materials and manufacturing—all need reinvention. Climate will reshape residential and office construction, insurance, finance, and where and how food is produced. Massive climate migrations have only just begun; tens or hundreds of millions of people will need to be resettled. Will we offer them shantytowns, or will we help them become settlers building a new, better world?
Prediction: There will be more climate billionaires created in the next two decades than in the internet boom.
With the exception of Musk, many of the already-minted climate billionaires are outside the US, highlighting the way that other countries already have the lead in these industries of the future. Bloomberg recently named a few: China’s Zeng Yuqun, Huang Shilin, Pei Zhenhua, and Li Ping (electric vehicle batteries), Li Zhenguo, Li Chunan, and Li Xiyan (solar panels and films), Lin Jianhua (solar panels and films), and Wang Chuanfu (electric vehicles); Germany’s Aloys Wobben (wind turbines); and Spain’s Jose Manuel Entrecanales (renewable power generation). …for the most part, Silicon Valley entrepreneurs and investors are not leaders in this sector.
There are five pillars to Rewiring America’s case for electrification as the answer to our urgent need to limit greenhouse gas emissions:
1. Electrifying everything requires only half as much energy as our current system.
2. We need to reconceive solar panels, batteries, electric cars, and electric appliances as part of our national energy infrastructure, even when they are on or in people’s homes, rather than thinking of infrastructure as something owned only by utilities or the government.
3. Markets won’t move fast enough without a World War II-style mobilization of private industry.
4. Electrifying the US will create jobs—lots of them.
5. Who gets the financial benefit of this massive investment—utilities, solar installers, or consumers—depends on interest rates.
Utilities already have access to low-cost loans. But consumers don’t, and if you want to create both jobs and cost savings for consumers, low-cost interest rates for home electrification are the best way to do it. Otherwise, the savings all get captured by middlemen, or by utilities, and adoption is much slower.
4. The end of the betting economy.
The final, and perhaps most important, reason why Silicon Valley as we know it may be over is that its current incarnation is a product of the extraordinarily cheap capital of the years since the global financial crisis of 2009.
There are two economies, often confused: the operating economy, in which companies make and sell products and services, and the betting economy, in which wealthy people bet on which companies will win and which will lose in the beauty contest that stock markets have become.
In the operating economy, the measure of success is, as Nick Hanauer and Eric Beinhocker memorably put it, “the solution to human problems.” Companies compete to solve those problems more effectively and earn a profit thereby. Along the way, they employ people productively, create valuable new goods and services, and contribute to their communities.
In the betting economy, the measure of success is stock price, the higher the better. Fueled by massive money creation by central banks, capital is abundant (for those who, by virtue of existing wealth, already have access to it), and traditional sources of return, such as interest on loans or ROI on investment in plants and equipment or employees, are dwarfed by the potential returns that can be achieved by playing on the madness of crowds. What can you call it but a bubble when the median valuation of this past year’s tech IPOs was 24 times trailing revenue, while tech IPOs during most of the past decade were only valued at about six times trailing revenue.
Capital markets do play an important role in our society. Bets on an unknown future are an important way to fund innovation and to build out infrastructure in advance of the prosperity that it will bring once that innovation has been widely deployed. But in today’s financialized economy, the returns on betting for its own sake have grown far faster than the returns on true operating investment.
…Intel’s stock market investors were making a rational bet that a world-changing technology would earn a huge stream of future profits. Palantir’s, Uber’s, and DoorDash’s investors were betting on how other investors might value their stocks, much as 16th century Dutch investors bet on the “value” of unique tulips or mid-19th century British investors bet on the prospects for railroads in distant countries, many of which were never built.
Were Gordon Moore and Robert Noyce, the founders of Intel, less motivated to build world-changing products because the proceeds were orders of magnitude less than they are for today’s Silicon Valley entrepreneurs? I suspect that it is the other way around. The easy profits from today’s financial betting markets encourage unproductive innovation.
John Maynard Keynes wrote in his General Theory during the depths of the Great Depression, “Speculators may do no harm as bubbles on a steady stream of enterprise. But the position is serious when enterprise becomes the bubble on a whirlpool of speculation. When the capital development of a country becomes a by-product of the activities of a casino, the job is likely to be ill-done.”
The problem is that money “invested” in the betting economy is not really invested. It is spent, just like money at the gaming table. When the WeWork bubble popped, the money SoftBank had spent propping up its valuation might just as well have gone up in smoke.
Prediction: When the bubble ends, greater opportunities will remain.
One of the gifts —if you can call it that— of crises like the pandemic and climate change is that they may teach us that we no longer have time for frivolity. We need our investment capital to flow back to the operating economy.
There is a robust strategy for investors and entrepreneurs: Work on stuff that matters. Invest in solving problems. Make a real difference in people’s lives. You will know you have done that when operating profits fairly earned, not stock market gains, are your measure of investment success.
Two of the big areas of innovation that I highlight in this essay —life sciences and climate change— require large amounts of real investment capital. Unlike money invested in internet companies that used it to buy unprofitable growth, money invested in Tesla was used to build factories, to manufacture cars and electric batteries, and to roll out national charging networks.
The path to high returns may take longer, but the need is real, and so is the value created.
Solving global crises requires the best of what we have to offer. If the best way to predict the future is to invent it, it’s time we got busy. Which world do we want to invent? It’s up to us.