We like to think that we still live in a free-market economy, but our world is increasingly ruled by vast networked platforms (from Google and Facebook to our financial markets) that are ruled by algorithms. It is those algorithms that decide who gets what and why. It's time to take a closer look at what it takes to manage these digital djinns, who promise to give us what we say we want, but parse our requests so precisely that it is often not what we really want. My talk to the National Association of Business Economists #TEC2018 Conference in San Francisco on October 30, 2018. Many of the slides are just pictures, so be sure to read the narrative in the speaker notes.

1. TIM O’REILLY
Founder + CEO
O’Reilly Media, Inc.
Twitter » @timoreilly
Rethinking Who Gets What and Why

2. How is work changing?
What does technology now make
possible that was previously
impossible?
What work needs doing?
How do we make the world
prosperous for all?
Why aren’t we doing it?
wtfeconomy.com

3. “My grandfather wouldn’t
recognize what I do as
work.”
Hal Varian,
Google Chief Economist

5. Many of today’s workers are programs.
Software developers are actually their managers.
Every day, they are inspecting the
performance of their workers and giving
them instruction (in the form of code)
about how to do a better job

6. Software has become a set of
ongoing business processes, not an artifact

7. New skillsets are needed
User Centered Design
Site Reliability Engineering
Data Science
Deep Learning
API Design
Economics
Market design

8. We have to let go of the maps that are steering us wrong
In 1625, we thought
California was an island

9. In 2018, it’s our maps of business
and the economy that are wrong

10. The invisible hand at work

11. What happens when there’s only one queue?
And it’s personalized for you?

14. Amazon.com

15. And what happens when there’s
only one price for everything?

17. Algorithms decide “who gets what – and why”
Markets are outcomes. A better designed
marketplace can have better outcomes.

18. Price signaling is no longer the primary coordinator

19. “Gradually, then suddenly”
Ernest Hemingway

20. Gradually, then suddenly
Large segments of the economy are
governed not by free markets but by
centrally managed platforms

22. “In an information-rich world, the wealth of
information means a dearth of something
else: a scarcity of whatever it is that
information consumes. What information
consumes is rather obvious: it consumes
the attention of its recipients. Hence a
wealth of information creates a poverty of
attention and a need to allocate that
attention efficiently.”
Herbert Simon

23. Algorithms have become a battleground
Security: “That word does not
mean what you think it means.”

24. 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.

25. Gradually, then suddenly
Artificial Intelligence and algorithmic
systems are everywhere, in new
kinds of partnerships with humans

26. “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

27. We are all living and working inside a machine

28. It’s no longer just in the digital realm

29. An Amazon warehouse is a human-machine hybrid

31. It makes things like this possible
68 million monthly users
440,000 employees
336 million monthly active users
~3400 employees

32. Managing an algorithmic marketplace

33. 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.

34. Real Time Digital Regulatory Systems
Google search quality
Social media feed organization
Email spam filtering
Credit card fraud detection
Risk management and hedging

35. 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

36. “Why is policy still educated
guesswork with a feedback
loop measured in years?”
Tom Loosemore,
Former Deputy Director,
UK Government Digital Service

39. 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

40. Algorithmic systems have an “objective function”
Google: Relevance
Facebook: Engagement
Uber and Lyft: 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?

41. When platforms get their algorithms wrong, there can be serious
consequences!
When platforms get
their objective function
wrong, there can be
serious
consequences!

42. Like the djinn of Arabian mythology, our digital djinni
do exactly what we tell them to do

45. Divergence of productivity
and real median family income in the US

46. “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

47. 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

48. We’ve built one of these already

49. What is the objective function of our financial markets?
“The Social Responsibility of Business Is to
Increase Its Profits”
Milton Friedman, 1970

50. Is there really
nothing left
for humans to
do?

52. Dealing with climate change
Rebuilding our infrastructure
Feeding the world
Ending disease
Resettling refugees
Caring for each other
Educating the next generation
Enjoying the fruits of shared prosperity

53. This is what technology wants
“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

54. “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

55. Once a platform stops creating more
value for others than it captures for
itself, people migrate elsewhere.

56. Microsoft crushed its ecosystem

57. How Industries Mature
1. Some new technology (the PC, the web, the smartphone) lowers the barriers to
participation and innovation.
2. The market explodes as “hackers” push the envelope of possibility, and
entrepreneurs make things easier for ordinary users.
3. The market stagnates as players become platforms, and raise barriers to entry.
Hackers and entrepreneurs move on, looking for new frontiers.
Or (rarely)
3. The industry builds a healthy ecosystem, in which hackers, entrepreneurs and
platform companies play a creative game of "leapfrog". No one gets complete lock in,
and everyone has to improve in order to stay competitive. Value is created for an
entire ecosystem.

58. Generosity takes us to the next peak
Tim Berners-Lee, 1990
The World Wide Web
Linus Torvalds, 1991
Linux
Big Data
and
AI
Tim Berners-Lee, 1990
The World Wide Web
Linus Torvalds, 1991
Linux

59. Google’s share of ad revenue over time
O’Reilly Research

60. Generous is also “Long-term greedy”

61. “Self-interest properly regarded”
A new inclusive
opportunity
ecosystem keeps
the game going

62. 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.

63. Growth goes on forever?
One of the key drivers of
corporate bad behavior is the
command given them by
financial markets that they
must constantly grow and
increase their profits

64. An alternative: “Doughnut Economics”
Kate Raworth

65. Oikonomia vs Chrematistike

66. O’Reilly Media
● Providing learning for almost 40 years
● Trends called – Open Source, Web
2.0, Maker Movement, Big Data
● 500 employees, thousands of
contributors
● 5,000+ enterprise clients, 2.3m
platform users globally
● 17 global technology events serving
20k individuals and 1,000 sponsor
companies

67. Change the world
by spreading the knowledge of innovators

71. “The opportunity for AI is to help humans model
and manage complex interacting systems.”
Paul R. Cohen

73. “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

74. The great opportunity of the 21st century is to use our
newfound cognitive tools to build
sustainable businesses and economies

75. Can we build an economic flywheel
that keeps us in the doughnut?

76. What’s the Future?
It’s Up To us
wtfeconomy.com

77. Tim O’Reilly
@timoreilly
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Founder & CEO, O’Reilly Media
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Board member, Code for America
Co-founder, Maker Media