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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
You’ve Probably Seen Headlines Like These
You’ve Probably Seen Headlines Like This Too
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)
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
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
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?
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.
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
In 2018, 83% of IPOs were for companies
with no profits
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
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.
The goal is an “exit”,
not an operating business
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!”
The Venture Capital equivalent of fake news
The big company equivalent of fake news
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.
“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)
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)
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
“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.”
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
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
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
Ride-hailing, a transformative innovation,
was stunted by the false incentives of too
much capital and the race for a profitless IPO
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.
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
What new capacity are we building out
today?
From the stateof.ai by Nathan Benaich and Ian Hogarth
Each cycle was characterized by four distinct periods divided
into two parts
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
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)
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
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.
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.
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
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.”
Here’s Google Search Up Till 2010
But that began to change
Google search today
Google’s share of ad revenue over time
O’Reilly Research
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
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.
Amazon Ad Revenue since 2016
Amazon Retail Revenues vs “Services”
Algorithmic rents
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Q&A
We have to let go of the maps that are steering us wrong
In 1625, people
thought
California was an
island
In 2020, it’s our maps of business
and the economy that are wrong
“Gradually, then suddenly”
Ernest Hemingway
Gradually, then suddenly
Artificial Intelligence and algorithmic systems are
everywhere, in new kinds of partnerships with humans
“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
We are all living and working inside a machine
It’s no longer just in the digital realm
An Amazon warehouse is a human-machine
hybrid
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Gradually, then suddenly
Large segments of the economy are governed not by
free markets but by centrally managed platforms
The invisible hand at work
What happens when there’s only one queue?
And it’s personalized for you?
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Amazon.com
And what happens when there’s
only one price for everything?
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Algorithms decide “who gets what – and why”
A better designed marketplace can
have better outcomes.
“Markets are outcomes.”
Mariana Mazzucato
Price signaling is no longer the primary
coordinator
Algorithms have become a battleground
Attention: “That word does
not mean what you think it
means.”
Managing an algorithmic marketplace
Real Time Digital Regulatory Systems
Google search quality
Social media feed organization
Email spam filtering
Credit card fraud detection
Risk management and hedging
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.
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?
When platforms get their algorithms wrong, there can be
serious consequences!
When platforms get
their objective
function wrong, there
can be serious
consequences!
Like the djinn of Arabian mythology, our
digital djinni do exactly what we tell them to do
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
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
https://www.vanityfair.com/news/2017/03/elon-musk-billion-dollar-crusade-to-stop-ai-space-x
We’ve built one of these already
What is the objective function of our
financial markets?
“The Social Responsibility of Business Is to
Increase Its Profits”
Milton Friedman, 1970
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Divergence of productivity
and real median family income in the US
Are the government’s economic
“algorithms” having the intended effect?
Have the goals of central banks been
captured by the equivalent of spammers?
Tax incentives as algorithmic economics
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
“Why is policy still
educated guesswork with
a feedback loop measured
in years?”
Tom Loosemore,
Former Deputy Director,
UK Government Digital Service
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
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
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.
“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
Q&A
An alternative: “Doughnut Economics”?
Kate Raworth
Degrowth?
Do we need to reduce
our wants?
We have new tools
“The opportunity for AI is to help humans
model and manage complex interacting
systems.”
Paul R. Cohen
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
“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
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
The great opportunity of the 21st century is to
use our newfound cognitive tools to build
sustainable businesses and economies
Can we build an economic flywheel
that keeps us in the doughnut?
“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.
A marketplace in which we work to
“create more value than we capture”
Creating value for suppliers
as well as customers
“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
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.”
https://www.linkedin.com/pulse/conversation-satya-nadella-his-new-book-hit-refresh-tim-
o-reilly/
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
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
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
What's Wrong with the Silicon Valley Growth Model (Extended UCL Lecture)
Turn our greatest challenges into opportunity
Q&A

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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)
  • 21. “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.”
  • 22. 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
  • 23. 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
  • 24. 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
  • 25. Ride-hailing, a transformative innovation, was stunted by the false incentives of too much capital and the race for a profitless IPO
  • 26. 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.
  • 27. 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
  • 28. What new capacity are we building out today?
  • 29. From the stateof.ai by Nathan Benaich and Ian Hogarth
  • 30. Each cycle was characterized by four distinct periods divided into two parts
  • 31. 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
  • 32. 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)
  • 33. 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
  • 34. 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.
  • 35. 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.
  • 36. 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
  • 37. 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.”
  • 38. Here’s Google Search Up Till 2010
  • 39. But that began to change
  • 41. Google’s share of ad revenue over time O’Reilly Research
  • 42. 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
  • 43. 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.
  • 44. Amazon Ad Revenue since 2016
  • 45. Amazon Retail Revenues vs “Services”
  • 49. Q&A
  • 50. We have to let go of the maps that are steering us wrong In 1625, people thought California was an island
  • 51. In 2020, it’s our maps of business and the economy that are wrong
  • 53. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  • 54. “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
  • 55. We are all living and working inside a machine
  • 56. It’s no longer just in the digital realm
  • 57. An Amazon warehouse is a human-machine hybrid
  • 59. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platforms
  • 61. What happens when there’s only one queue? And it’s personalized for you?
  • 65. And what happens when there’s only one price for everything?
  • 67. Algorithms decide “who gets what – and why” A better designed marketplace can have better outcomes.
  • 69. Price signaling is no longer the primary coordinator
  • 70. Algorithms have become a battleground Attention: “That word does not mean what you think it means.”
  • 71. Managing an algorithmic marketplace
  • 72. Real Time Digital Regulatory Systems Google search quality Social media feed organization Email spam filtering Credit card fraud detection Risk management and hedging
  • 73. 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.
  • 74. 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?
  • 75. When platforms get their algorithms wrong, there can be serious consequences! When platforms get their objective function wrong, there can be serious consequences!
  • 76. Like the djinn of Arabian mythology, our digital djinni do exactly what we tell them to do
  • 79. 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 https://www.vanityfair.com/news/2017/03/elon-musk-billion-dollar-crusade-to-stop-ai-space-x
  • 80. We’ve built one of these already
  • 81. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  • 83. Divergence of productivity and real median family income in the US
  • 84. Are the government’s economic “algorithms” having the intended effect? Have the goals of central banks been captured by the equivalent of spammers?
  • 85. Tax incentives as algorithmic economics
  • 86. 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
  • 87. “Why is policy still educated guesswork with a feedback loop measured in years?” Tom Loosemore, Former Deputy Director, UK Government Digital Service
  • 90. 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
  • 91. 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.
  • 92. “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
  • 93. Q&A
  • 94. An alternative: “Doughnut Economics”? Kate Raworth
  • 95. Degrowth? Do we need to reduce our wants?
  • 96. We have new tools “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
  • 98. “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
  • 100. The great opportunity of the 21st century is to use our newfound cognitive tools to build sustainable businesses and economies
  • 101. Can we build an economic flywheel that keeps us in the doughnut?
  • 102. “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.
  • 103. A marketplace in which we work to “create more value than we capture”
  • 104. Creating value for suppliers as well as customers
  • 105. “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
  • 106. 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.” https://www.linkedin.com/pulse/conversation-satya-nadella-his-new-book-hit-refresh-tim- o-reilly/
  • 108. 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
  • 109. 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
  • 111. Turn our greatest challenges into opportunity
  • 112. Q&A