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What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)

A three part lecture for the Institute for Innovation and Public Purpose at University College London. I talk about how the Silicon Valley growth model is leading from value creation to rent extraction, then about how public policy shapes our markets and what public policy students can learn from technology platforms (both what they do right and how they go wrong), and finally, I touch on some of the great mission-driven goals that could replace "increasing corporate profits" as the guiding objective of our economy.

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What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)

  1. 1 What’s Wrong with Silicon Valley’s Growth Model Tim O’Reilly Founder and CEO O’Reilly Media @timoreilly UCL MPA Lecture October 29, 2020
  2. You’ve Probably Seen Headlines Like These
  3. You’ve Probably Seen Headlines Like This Too
  4. What makes the difference? “In the short term, the market is a voting machine. In the long term, it’s a weighing machine.” -Benjamin Graham, The Intelligent Investor (1949)
  5. If you weren’t betting, which of these businesses would you rather own? Uber – Revenue $13B, lost $8.6B WeWork – Revenue $1.8B, lost $1.9 Billion Microsoft – Revenue $130B, profits $41B Apple - Revenue $259B, profits $55B Alphabet (Google) – Revenue $155B, profits $33B Amazon – Revenue $265B, profits $11B
  6. A Share of Stock is a Claim on Company Profits Uber – ??? No profits WeWork – ??? No profits Its price is a bet on what those profits will be. The Price/Earnings Ratio shows how many years of future profits are reflected in the price of a share Microsoft – 37.6 Apple – 34.99 Google – 35.16 Amazon – 123.20 S&P 500 avg – 31.24 S&P 500 in 1950 – 7.22 S&P 500 in 1929 – 17.17
  7. Why Jeff Bezos Is The Richest Man in the World There is an operating economy, where a dollar of profit is worth a dollar to a small business, and a “supermoney” betting economy where a dollar of profit is bid up to absurd heights A dollar of Amazon profits delivers $123 of stock market value – almost 4x what a dollar of Apple, Google, or Microsoft profit delivers, and 123x what a dollar of small business profit delivers. That is, people are betting on Jeff, big time. What are they betting on?
  8. What if you’d bought Apple shares at its IPO in 1980, Microsoft in 1986, Amazon in 1997, or Google in 2004? Or even better, Apple in 1997, when a share (split adjusted) cost about 60 cents vs $319 today? That’s where growth comes into play in the price. People are betting on the future.
  9. How Long Should It Take To Reach Profitability? Apple – $250,000 Microsoft – $1 million Google – $36 million Amazon – $108 million* Uber – $24 billion, and still not even on a path to profitability WeWork - $22.5 billion, and still not even on a path to profitability Total Capital Raised pre-IPO
  10. In 2018, 83% of IPOs were for companies with no profits
  11. Betting might not seem so bad if you can cash out before the business gets weighed… Uber founder Travis Kalanick WeWork founder Adam Neumann $2.7 billion $1 billion
  12. Many of today’s Silicon Valley startups are not really companies. They are financial instruments created and sold by VCs, much as Wall Street bankers created and sold collateralized debt obligations (CDOs) leading up to the 2009 crash.
  13. The goal is an “exit”, not an operating business
  14. How I tell if an entrepreneur or VC is bluffing Me: How’s your company doing? Entrepreneur or VC: “We just raised our D round!”
  15. The Venture Capital equivalent of fake news
  16. The big company equivalent of fake news
  17. This isn’t “investing” – it’s extracting 85% of so-called investment no longer goes towards the creation of new capabilities, jobs, products, or services. It’s just money being traded for money, in the highest-stakes poker game in the world.
  18. “It wasn’t the way Steve Jobs would have done it…. Jobs focused relentlessly on creating irresistible life-changing products, and was confident the money would follow. By contrast, Cook pays close attention to the money and to increasingly sophisticated manipulations of money.” Rana Foroohar, Makers and Takers (2016)
  19. How dangerous is a bubble? “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.” John Maynard Keynes, General Theory of Employment, Interest, and Money (1936)
  20. “The lightning-fast path to building massively valuable companies.” Derived from the blitzkrieg or “lightning war” strategy of Nazi general Heinz Guderian Aims to “achieve massive scale at incredible speed” in order to seize the ground before competitors do. “Prioritizes speed over efficiency” Risks “potentially disastrous defeat in order to maximize speed and surprise.”
  21. Go for growth even if you don’t know how you are going to make money “I remember telling my old college friend and Paypal co-founder/CEO Peter Thiel, ‘Peter, if you and I were standing on the roof of our office and throwing stacks of hundred-dollar bills off the edge as fast as our arms could go, we still wouldn’t be losing money as quickly as we are right now.’” 22 Reid Hoffman, co-founder Paypal, LinkedIn
  22. Somehow morphed into a winner-takes-all philosophy “As you all know, first prize is a Cadillac Eldorado. Anyone wanna see second prize? Second prize is a set of steak knives. Third prize is you’re fired. Get the picture?” -Alec Baldwin, in Glengarry Glen Ross, quoted by Reid Hoffman in Blitzscaling 23
  23. What went wrong in the ride sharing market Sunil Paul, the visionary who’d patented the use of GPS for ride hailing back in 2000, launched Sidecar with the peer-to-peer driver model in 2011. Uber and Lyft, which had already been funded by VCs with more traditional models, jumped on the new innovation, and took in massive amounts of capital to “blitzscale” the market. Sidecar went out of business. By coincidence, Sidecar had raised $35 million, about the same amount it took to launch Google. But Uber and Lyft raised billions. Customers didn’t pick the winner, the VCs did
  24. Ride-hailing, a transformative innovation, was stunted by the false incentives of too much capital and the race for a profitless IPO
  25. Technological Revolutions & Financial Capital Published in 2002, Carlota Perez’s book placed the dotcom bust in the context of four previous fifty-year cycles: the industrial revolution, steel and railways, electricity and heavy engineering, and automobiles and mass production. All of these previous technological revolutions were accompanies by financial bubbles.
  26. Financial bubbles are a necessary stage “What is perhaps the crucial role of the financial bubble is to facilitate the unavoidable over- investment in the new infrastructures. The nature of these networks is such that they cannot provide enough service to be profitable unless they reach enough coverage for widespread usage. The bubble provides the necessary asset inflation for investors to expect capital gains, even if there are no profits or dividends yet.” Carlota Perez, Technological Revolutions and Financial Capital
  27. What new capacity are we building out today?
  28. From the by Nathan Benaich and Ian Hogarth
  29. Each cycle was characterized by four distinct periods divided into two parts
  30. What if we are entering the maturity phase? “The practical implication … is that the dominant companies in mobile and the cloud — Apple, Google, Microsoft, and Amazon — may have a long stretch of dominance in front of them.” - Ben Thompson, Stratechery
  31. Financial Capital vs Production Capital “Financial capital represents the criteria and behavior of those agents who possess wealth in the form of money or other paper assets…They will perform those actions that, in their understanding, are most likely to increase that wealth.” By contrast, the term ‘production capital’ embodies the motives and behaviors of those agents who generate new wealth by producing goods or performing services (including transport, trade and other enabling activities)…Their purpose as production capital is to produce in order to be able to produce more. They are essentially builders.” Carlota Perez, Technological Revolutions and Financial Capital (2002)
  32. Favor productive investment, not financial speculation Look for companies with revenues, profits, and positive cash flow Making their money from customers, not from venture capital infusions, stock buybacks, or other gimmicks to juice their financial valuation without improving the economics of their actual business
  33. Tesla: Production capital at work $820 million raised pre-IPO, plus $10.4B in post-IPO debt, $8.7B in post- IPO equity. Profitable ($16B on revenue of $182B) but still raising money.
  34. At OATV, when we invest in things that require a lot of capital, it is production capital Planet: launching and operating hundreds of microsatellites to image the entire surface of the earth every day.
  35. Technology and prosperity “Prosperity in human societies is best understood as the accumulation of solutions to human problems. We won’t run out of work until we run out of problems.” Nick Hanauer
  36. The current system corrupts even the winners “The relentless pressure to maintain Google’s growth, he said, had come at a heavy cost to the company’s users. Useful search results were pushed down the page to squeeze in more advertisements, and privacy was sacrificed for online tracking tools to keep tabs on what ads people were seeing.”
  37. Here’s Google Search Up Till 2010
  38. But that began to change
  39. Google search today
  40. Google’s share of ad revenue over time O’Reilly Research
  41. An Amazon Search Result from 2004 “Most popular” was the default search This distinguished Amazon from B&N and Borders, which features sponsored products or their own competitive products No more
  42. Amazon today All but one of the items shown is sponsored Publishers must advertise their own products to be visible “Featured” is now the default. The old concept of collective intelligence picking the top products is mostly gone.
  43. Amazon Ad Revenue since 2016
  44. Amazon Retail Revenues vs “Services”
  45. Algorithmic rents
  46. Q&A
  47. We have to let go of the maps that are steering us wrong In 1625, people thought California was an island
  48. In 2020, it’s our maps of business and the economy that are wrong
  49. “Gradually, then suddenly” Ernest Hemingway
  50. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  51. “The hope is that, in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information- handling machines we know today.” - J.C.R. Licklider, Man-Machine Symbiosis,1960
  52. We are all living and working inside a machine
  53. It’s no longer just in the digital realm
  54. An Amazon warehouse is a human-machine hybrid
  55. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platforms
  56. The invisible hand at work
  57. What happens when there’s only one queue? And it’s personalized for you?
  59. And what happens when there’s only one price for everything?
  60. Algorithms decide “who gets what – and why” A better designed marketplace can have better outcomes.
  61. “Markets are outcomes.” Mariana Mazzucato
  62. Price signaling is no longer the primary coordinator
  63. Algorithms have become a battleground Attention: “That word does not mean what you think it means.”
  64. Managing an algorithmic marketplace
  65. Real Time Digital Regulatory Systems Google search quality Social media feed organization Email spam filtering Credit card fraud detection Risk management and hedging
  66. Governance in the age of algorithms Must focus on outcomes, not on rules. Must operate at the speed and scale of the systems it is trying to regulate. Must incorporate real-time data feedback loops. Must be robust in the face of failure and hostile attacks. Must address the incentives that lead to misbehavior. Must be constantly refined to meet ever-changing conditions.
  67. Algorithmic systems have an “objective function” Google: Relevance Facebook: Engagement Uber: Passenger pick up time Scheduling software used by McDonald’s, The Gap, or Walmart: Reduce employee costs and benefits Central banks: Control inflation? Employment? Interest rates?
  68. When platforms get their algorithms wrong, there can be serious consequences! When platforms get their objective function wrong, there can be serious consequences!
  69. Like the djinn of Arabian mythology, our digital djinni do exactly what we tell them to do
  70. The runaway objective function “Even robots with a seemingly benign task could indifferently harm us. ‘Let’s say you create a self-improving A.I. to pick strawberries,’ Musk said, ‘and it gets better and better at picking strawberries and picks more and more and it is self-improving, so all it really wants to do is pick strawberries. So then it would have all the world be strawberry fields. Strawberry fields forever.’ No room for human beings.” Elon Musk, quoted in Vanity Fair
  71. We’ve built one of these already
  72. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  73. Divergence of productivity and real median family income in the US
  74. Are the government’s economic “algorithms” having the intended effect? Have the goals of central banks been captured by the equivalent of spammers?
  75. Tax incentives as algorithmic economics
  76. Government and central bank statistics, economic modeling, and regulations are too slow for the pace and scale of the modern world “Would you cross the street with information that was five seconds old?” - Jeff Jonas, CEO of Senzing, Former IBM Fellow
  77. “Why is policy still educated guesswork with a feedback loop measured in years?” Tom Loosemore, Former Deputy Director, UK Government Digital Service
  78. Governance too must be reshaped by the digital “This isn’t just how we should be developing software. It’s how we should be developing policy.” Cecilia Muñoz, Former Director, White House Domestic Policy Council
  79. Nations fail for the same reason as tech platforms Inclusive economies outperform extractive economies. When inclusive economies fall prey to extractive elites, everyone is worse off.
  80. “The art of debugging is figuring out what you really told your program to do rather than what you thought you told it to do.” Andrew Singer Andrew Singer
  81. Q&A
  82. An alternative: “Doughnut Economics”? Kate Raworth
  83. Degrowth? Do we need to reduce our wants?
  84. We have new tools “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
  85. “Computational Sustainability is a new interdisciplinary research field, with the overarching goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future. Such problems are unique in scale, impact, complexity, and richness, often involving combinatorial decisions, in highly dynamic and uncertain environments, offering challenges but also opportunities for the advancement of the state-of-the-art of computer and information science. Work in Computational Sustainability integrates in a unique way various areas within computer science and applied mathematics, such as constraint reasoning, optimization, machine learning, and dynamical systems.” Carla Gomes
  86. The great opportunity of the 21st century is to use our newfound cognitive tools to build sustainable businesses and economies
  87. Can we build an economic flywheel that keeps us in the doughnut?
  88. “Create more value than you capture.” O’Reilly Media Providing technology learning for almost 40 years – books, events, online Trends pioneered – Commercial Internet, Open Source, ebooks, Web 2.0, Maker movement, big data 400+ employees, 5,000+ enterprise clients, 2.5m platform users globally Offices in US, Canada, UK, Japan, China Profitable, with hundreds of millions of dollars in revenue. Privately held, no venture capital, funded entirely by our customers.
  89. A marketplace in which we work to “create more value than we capture”
  90. Creating value for suppliers as well as customers
  91. “A platform is when the economic value of everybody that uses it exceeds the value of the company that creates it. Then it's a platform.” – Bill Gates
  92. Create more value than you capture “I’m a believer that capitalism can only survive if we have a world where surplus is getting created, and that surplus is more broadly getting distributed across all constituencies, versus narrowly….” “The creation myth of Microsoft is what should inspire us. One of the first things the company did, when Bill and Paul got together is that they built the BASIC interpreter for the ALTAIR. What does that tell us today, in 2017? It tells us that we should build technology so that others can build technology.” o-reilly/
  93. What Would Mission Driven Government Do? • Deal with climate change • Prepare for future pandemics Rebuild our infrastructure Feed the world End disease and provide healthcare for all Resettle refugees Educate the next generation Help citizens to care for one another and enjoy the fruits of shared prosperity
  94. Invest in the new beginnings, not the end The transition to a decarbonized economy Electrification Meat replacement and improved agriculture Demographic inversions Worker augmentation - including accelerated learning Healthcare Mass migrations and how to turn them into a net positive Big unknowns and hard problems
  95. Turn our greatest challenges into opportunity
  96. Q&A