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Mastering the Demons of
Our Own Design
Tim O’Reilly
Founder and CEO, O’Reilly Media
@timoreilly
Science and Democracy Lecture
Harvard
April 21, 2021
Giving credit where credit is due
“Stunning as such crises are, we tend to
see them as inevitable…. We take comfort
in ascribing the potential for fantastic losses
to the forces of nature and unavoidable
economic uncertainty. But that is not the
case. More often than not, crises aren’t the
result of sudden economic downturns or
natural disasters. Virtually all mishaps over
the past decades had their roots in the
complex structure of the markets
themselves.”
Markets are human creations
Tax policy, laws, and regulations shape the
economy in much the same way as the
algorithmic systems at Google, Amazon,
and Facebook shape their marketplaces.
The market is a designed artifact, not a
natural phenomenon. When Facebook’s
algorithms have gone wrong, we demand
that we change them. But we throw up our
hands about many self-inflicted economic
wounds, as if the rules of the market are
unchangeable.
Stability vs risk
“An ecosystem is stable not because it is secure
and protected but because it contains such
diversity that some of its many types of members
are bound to survive despite drastic
changes….Herbert adds, however, that the effort of
civilization to create and maintain security for its
individual members “necessarily creates the
conditions of crisis because it fails to deal with
change.”
“Gradually, then suddenly”
Ernest Hemingway
Gradually, then suddenly
Artificial Intelligence and algorithmic systems are
everywhere, in new kinds of partnerships with humans
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
Our financial markets are cut from the same cloth
Collective Intelligence and “Hybrid AI”
“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
Gradually, then suddenly
Large segments of the economy are governed not by
free markets but by centrally managed platforms
Algorithms decide “who gets what – and why”
By placement on the screen and algorithmic
priority, Google, Amazon, and app stores shape
which pages users click on and which products
they decide to buy. Facebook shapes what
ideas gets attention. Uber and Lyft – not a free
market of competing drivers – decide what to
charge passengers, and thus the allocation of
value between drivers and riders.
Algorithms decide “who gets what – and why”
A better designed marketplace can
have better outcomes.
Price signaling is no longer the primary
coordinator
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.
It’s a hard problem
Users post 7 billion pieces of
content to Facebook a day.
Expecting human fact checkers to
catch fake news is like asking
workers to build a modern city with
only picks and shovels.
At internet scale, we now rely
increasingly on algorithms to
manage what we see and believe.
Algorithms have become a battleground
The battle against bad actors
crosses platform boundaries.
Policing platforms becomes
a major activity, which is also
carried out by algorithmic
systems.
The incentives are wrong
Why haven’t these problems been solved yet?
Is it just that they are hard?
Is it that our political system gives mixed messages about what to do?
Is it that the leaders of the companies are bad people, concerned with
profit above all else?
Or is there something more at work?
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?
Like the djinn of Arabian mythology, our digital
djinni do exactly what we tell them to do
“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
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
What is the objective function of our
financial markets?
“The Social Responsibility of Business Is to
Increase Its Profits”
Milton Friedman, 1970
A system that turns idealists into monopolists
The “Don’t Be Evil” Age of Internet Idealism
“We want you to come to Google and quickly find what you want. Then we’re
happy to send you to the other sites. In fact, that’s the point. The portal
strategy tries to own all of the information…. Most portals show their own
content above content elsewhere on the web. We feel that’s a conflict of
interest, analogous to taking money for search results. Their search engine
doesn’t necessarily provide the best results; it provides the portal’s results.
Google conscientiously tries to stay away from that. We want to get you out of
Google and to the right place as fast as possible. It’s a very different model.”
“Our goal is to be earth's most customer-centric company.”
Larry Page in 2004
Jeff Bezos in 1998
Advertising and Mixed Motives
The Shift to Mobile
The shift to mobile and
the rise of social media
were an existential threat
to Google.
The pressure to grow is built into the system
“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
What happened to TripAdvisor
Google introduces
“Destinations” travel search
feature on mobile, starting in
March 2016, expands to
desktop search thereafter.
March 2018, Google retires
“Don’t be evil” statement
from corporate values.
Google’s share of ad revenue over time
O’Reilly Research
When there is no money to be made…
Google has added
“answerbox”
features that serve
user interests, and
mostly sends the
traffic onwards as
before.
Only about 6% of
Google search
results pages
contain advertising
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
customer collective
intelligence picking the top
products is mostly gone.
Amazon Ad Revenue 2014-2020
2014 $ 1.32
2015 $ 1.71
2016 $ 2.95
2017 $ 4.65
2018 $ 10.11
2019 $ 14.09
2020 $ 21.45
In this category, Google has no mixed motive
but Amazon does…
Algorithmic rents
Platforms use their power to decide who gets what and why to allocate
an additional share of the value created to themselves.
“Rents [accrue] from a mismatch between
value creation and value appropriation”
“The classical economists…[define] economic rent as
income extracted from the ownership of a scarce
asset (such as land or other natural resources) or
control over an activity required for economic
production in excess of the costs required to maintain
the asset or activity. This income accrues without the
creation of any additional value — what the classicals
called ‘unearned income’ — so it can be viewed as
‘value extraction’, since it reduces the income
available for productive investment, spending or
innovation.”
Mariana Mazzucato,
UCL Institute for Innovation
and Public Purpose
In the long run, rent extraction is bad for the
platforms themselves as well as their users
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.
Are the government’s economic
“algorithms” having the intended effect?
Divergence of productivity
and real median family income in the US
To paraphrase Bookstaber,
“We take comfort in
ascribing the problem to the
unavoidable forces of ‘the
market.’ But that is not the
case."
Goodhart’s Law
When a measure becomes a target,
it ceases to be a good measure.
As restated by Marilyn Strathern
Housing
Tax incentives as algorithmic economics
“Algorithmic” interventions can spur innovation
AI is a mirror, not a master
We have new tools
“The opportunity for AI is to help humans
model and manage complex interacting
systems.”
Paul R. Cohen
What Might Mission Driven Algorithms
Optimize For?
• Dealing with climate change
• Preparing for future pandemics
• Rebuilding our infrastructure
• Feeding the world
• Ending disease and provide healthcare for all
• Resettling refugees
• Educating the next generation
• Helping people to care for one another and to
enjoy the fruits of shared prosperity
Doughnut Economics
Kate Raworth
The great opportunity of the 21st century is to
use our newfound cognitive tools to build
sustainable businesses and economies

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Mastering the demons of our own design

  • 1. 1 Mastering the Demons of Our Own Design Tim O’Reilly Founder and CEO, O’Reilly Media @timoreilly Science and Democracy Lecture Harvard April 21, 2021
  • 2. Giving credit where credit is due “Stunning as such crises are, we tend to see them as inevitable…. We take comfort in ascribing the potential for fantastic losses to the forces of nature and unavoidable economic uncertainty. But that is not the case. More often than not, crises aren’t the result of sudden economic downturns or natural disasters. Virtually all mishaps over the past decades had their roots in the complex structure of the markets themselves.”
  • 3. Markets are human creations Tax policy, laws, and regulations shape the economy in much the same way as the algorithmic systems at Google, Amazon, and Facebook shape their marketplaces. The market is a designed artifact, not a natural phenomenon. When Facebook’s algorithms have gone wrong, we demand that we change them. But we throw up our hands about many self-inflicted economic wounds, as if the rules of the market are unchangeable.
  • 4. Stability vs risk “An ecosystem is stable not because it is secure and protected but because it contains such diversity that some of its many types of members are bound to survive despite drastic changes….Herbert adds, however, that the effort of civilization to create and maintain security for its individual members “necessarily creates the conditions of crisis because it fails to deal with change.”
  • 6. Gradually, then suddenly Artificial Intelligence and algorithmic systems are everywhere, in new kinds of partnerships with humans
  • 7. We are all living and working inside a machine
  • 8. It’s no longer just in the digital realm
  • 9. An Amazon warehouse is a human-machine hybrid
  • 10. Our financial markets are cut from the same cloth
  • 11. Collective Intelligence and “Hybrid AI” “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
  • 12. Gradually, then suddenly Large segments of the economy are governed not by free markets but by centrally managed platforms
  • 13. Algorithms decide “who gets what – and why” By placement on the screen and algorithmic priority, Google, Amazon, and app stores shape which pages users click on and which products they decide to buy. Facebook shapes what ideas gets attention. Uber and Lyft – not a free market of competing drivers – decide what to charge passengers, and thus the allocation of value between drivers and riders.
  • 14. Algorithms decide “who gets what – and why” A better designed marketplace can have better outcomes.
  • 15. Price signaling is no longer the primary coordinator
  • 16. Managing an algorithmic marketplace
  • 17. Real Time Digital Regulatory Systems Google search quality Social media feed organization Email spam filtering Credit card fraud detection Risk management and hedging
  • 18. 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.
  • 19. It’s a hard problem Users post 7 billion pieces of content to Facebook a day. Expecting human fact checkers to catch fake news is like asking workers to build a modern city with only picks and shovels. At internet scale, we now rely increasingly on algorithms to manage what we see and believe.
  • 20. Algorithms have become a battleground The battle against bad actors crosses platform boundaries. Policing platforms becomes a major activity, which is also carried out by algorithmic systems.
  • 22. Why haven’t these problems been solved yet? Is it just that they are hard? Is it that our political system gives mixed messages about what to do? Is it that the leaders of the companies are bad people, concerned with profit above all else? Or is there something more at work?
  • 23. 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?
  • 24. Like the djinn of Arabian mythology, our digital djinni do exactly what we tell them to do
  • 25.
  • 26.
  • 27. “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
  • 28. 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
  • 29. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  • 30. A system that turns idealists into monopolists
  • 31.
  • 32.
  • 33. The “Don’t Be Evil” Age of Internet Idealism “We want you to come to Google and quickly find what you want. Then we’re happy to send you to the other sites. In fact, that’s the point. The portal strategy tries to own all of the information…. Most portals show their own content above content elsewhere on the web. We feel that’s a conflict of interest, analogous to taking money for search results. Their search engine doesn’t necessarily provide the best results; it provides the portal’s results. Google conscientiously tries to stay away from that. We want to get you out of Google and to the right place as fast as possible. It’s a very different model.” “Our goal is to be earth's most customer-centric company.” Larry Page in 2004 Jeff Bezos in 1998
  • 35. The Shift to Mobile The shift to mobile and the rise of social media were an existential threat to Google.
  • 36. The pressure to grow is built into the system “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
  • 40. What happened to TripAdvisor Google introduces “Destinations” travel search feature on mobile, starting in March 2016, expands to desktop search thereafter. March 2018, Google retires “Don’t be evil” statement from corporate values.
  • 41. Google’s share of ad revenue over time O’Reilly Research
  • 42. When there is no money to be made… Google has added “answerbox” features that serve user interests, and mostly sends the traffic onwards as before. Only about 6% of Google search results pages contain advertising
  • 43. 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
  • 44. 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 customer collective intelligence picking the top products is mostly gone.
  • 45. Amazon Ad Revenue 2014-2020 2014 $ 1.32 2015 $ 1.71 2016 $ 2.95 2017 $ 4.65 2018 $ 10.11 2019 $ 14.09 2020 $ 21.45
  • 46. In this category, Google has no mixed motive but Amazon does…
  • 47. Algorithmic rents Platforms use their power to decide who gets what and why to allocate an additional share of the value created to themselves.
  • 48. “Rents [accrue] from a mismatch between value creation and value appropriation” “The classical economists…[define] economic rent as income extracted from the ownership of a scarce asset (such as land or other natural resources) or control over an activity required for economic production in excess of the costs required to maintain the asset or activity. This income accrues without the creation of any additional value — what the classicals called ‘unearned income’ — so it can be viewed as ‘value extraction’, since it reduces the income available for productive investment, spending or innovation.” Mariana Mazzucato, UCL Institute for Innovation and Public Purpose
  • 49. In the long run, rent extraction is bad for the platforms themselves as well as their users
  • 50.
  • 51.
  • 52.
  • 53. 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.
  • 54. Are the government’s economic “algorithms” having the intended effect?
  • 55.
  • 56.
  • 57. Divergence of productivity and real median family income in the US To paraphrase Bookstaber, “We take comfort in ascribing the problem to the unavoidable forces of ‘the market.’ But that is not the case."
  • 58. Goodhart’s Law When a measure becomes a target, it ceases to be a good measure. As restated by Marilyn Strathern
  • 60. Tax incentives as algorithmic economics
  • 62. AI is a mirror, not a master
  • 63. We have new tools “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
  • 64. What Might Mission Driven Algorithms Optimize For? • Dealing with climate change • Preparing for future pandemics • Rebuilding our infrastructure • Feeding the world • Ending disease and provide healthcare for all • Resettling refugees • Educating the next generation • Helping people to care for one another and to enjoy the fruits of shared prosperity
  • 66. The great opportunity of the 21st century is to use our newfound cognitive tools to build sustainable businesses and economies