My plenary talk to the California Workforce Association Conference in Monterey, CA, on September 5, 2018. I talked about the role of technology to augment people rather than replace them from my book WTF? What's the Future and Why It's Up to Us, and my ideas about AI and distributional economics, in the context of today's education and workforce development systems. I also summarize some of the work Code for America has been doing on the current state of the California Workforce Development ecosystem.

1. What’s the Future of Work With AI?
We Must Redraw The Map
California Workforce Association
September 5, 2018
TIM O’REILLY
Founder & CEO
O’Reilly Media, Inc.
Twitter: @timoreilly

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

4. In 2018, we believe that it is technology
that puts people out of work

5. “…47 percent of jobs are “at
risk” of being automated in the
next 20 years.”
Carl Frey and Michael Osborne, Oxford University
“The Future of Employment: How Susceptible
Are Jobs to Computerisation?”

6. Will there really be nothing left for people to do?
Is there really
nothing left for
humans to do?

8. 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

9. This is what technology is for
“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

10. What happened when Amazon added 45,000 robots

11. Jeff Bezos calls this “the flywheel”

12. This is the master design pattern
for applying technology: Do more.
Do things that were previously
unimaginable.

13. The March of Progress

14. It is machines that help us
to feed 7 billion

15. What happened when we made food abundant?

16. We found new ways to add value to food

17. Number of craft breweries in the US, 1994-2017

18. The Law of Conservation of Attractive Profits
“When attractive profits disappear at
one stage in the value chain because a
product becomes modular and
commoditized, the opportunity to earn
attractive profits with proprietary
products will usually emerge at an
adjacent stage.”
Clayton Christensen,
Harvard Business School

19. There’s plenty to go around.
It’s just not going around well enough!

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

21. “If total US household income of $8.495
trillion were shared by America’s 116
million households, each would earn
$73,000, enough for a decent middle-
class life.”
Brian Arthur

22. The fundamental economic question
is no longer how to incentivize production
but how to incentivize fair distribution
of the fruits of increased productivity
Brian Arthur

23. This is something digital systems are good at

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

25. We are all living and working inside a machine

26. Our digital systems enhance our capabilities to manage data
the way our physical systems use heavy equipment
 Every minute, there are 2.4
million searches on Google;
510,000 comments are posted
to Facebook, 293,000 statuses
are updated, and 136,000
photos are uploaded.
 At internet scale, we now rely
increasingly on algorithmic
systems to manage what we
see and consume.

27. Amazon.com

28. An Amazon warehouse is a human-machine hybrid

30. These apps teach us about some ways the world has changed
And about the mindset
required to redraw the
map

31. In 2000, we thought hailing a cab looked like this
Photo by Timothy Krause, Flickr

32. In 2005, we thought the connected taxicab looked like this
Hey, look, there’s a
video screen showing
ads, and a credit card
reader in the back of
the cab!

33. “Framing blindness”

35. Gradually, then suddenly
1. Artificial Intelligence and
algorithmic systems are
everywhere
2. The world is becoming infused
with the digital
3. We are creating new kinds of
partnerships between machines
and humans

36. Only a few years ago, this app seemed magical
Pull out your smartphone, summon a car to
wherever you are
Watch the driver’s progress towards you
Step outside to meet your car when it arrives
Call or text the driver if you need to
Step out of the car and walk away when you
get to your destination. Payment is
automatically charged to your credit card
Get a receipt emailed to you showing your
route, mileage, and cost

37. Where’s the magical app for workforce development
that makes everything
simple, beautiful, and easy to use?

38. In 2018, workforce development looks like this

39. There are so many possible paths,
it’s easy to get lost along the way.

40. Acronym Cheat Sheet
 WIA: Workforce Investment Act
 WIOA: Workforce Innovation and Opportunity Act
 DOL: Department of Labor
 ETA: Employment and Training Administration
 BLS: Bureau of Labor Statistics
 ODEP: Office of Disability Employment Policy
 CWDB: California Workforce Development Board
 WDB: Workforce Development Board (new name for WIB under WIOA)
 WIB: Workforce Investment Board
 SNAP E&T: Supplement Nutrition and Assistance Program, Employment and Training
 UI: unemployment insurance
 ETP: Eligible Training Provider
 ETPL: Eligible Training Provider List (this is a myth everyone talks about)
 AJCC: America’s Job Center of California
 AJC: American Job Center
 GeoSol: Geographic Solutions
 AEBG: Adult Education Block Grant (provided by the Dept. of Ed.)
 TANF: Temporary Association for Needy Families

41. Q2/Q3 Design
Prototypes

42. Uber … Google … Amazon
are not apps. They are systems.

43. Understanding the Landscape for Systems
Change
“This is not a system, it was built as separate universes.
There have been no incentives for any of these systems
to work together - policies trying to do so are unfunded
mandates. So it is not a ‘re-architecting’ issue; this is
rebuilding from the ground up.”
– Virginia Hamilton
Senior Lead, Design Thinking and Innovation at American Institutes for Research
Formerly Regional Administrator, US Dept. of Labor

44. “A business model is the way that
all of the parts of a business work
together to create competitive
advantage and customer value.”
- Dan and Meredith Beam

45. Jeff Bezos understands this deeply

46. A Business Model Map of Uber
 A magical app that lets
drivers and passengers find
each other in real time
 A networked marketplace of
drivers and passengers
 Augmented workers able to
join the market as and
when they wish
 Managed by algorithm

47. A algorithmic matching marketplace
of drivers and passengers

49. Gurley’s key questions
 Is the new experience better than the status quo?
 Are there economic advantages vs. the status quo?
 Is there an opportunity for technology to add value?
 Is there high fragmentation in the existing market?
 How much friction is there in supplier sign-up?
 How big is the market opportunity?
 Can you expand the market?
 How frequently do market participants transact?
 Are you part of the payment flow?
 Are there network effects?

50. Better matching puts people to work
Oxford Internet Institute study:
 50% more total hours worked
 Higher wages per hour
https://www.oxfordmartin.ox.ac.uk/downloads/academic/Uber_Drivers_of_Disruption.pdf

51. What might that look like for workforce development?

59. Platforms Decide Who Gets What – and Why
Good markets are the outcome of
good design decisions.
A better designed marketplace can
have better outcomes.

60. “The Uber app is the drivers’ workplace,
as much as the city where they’re driving
is. Each decision about its interface
structures drivers’ interactions with Uber
the company as well as Uber the
transportation marketplace.”
Alexis Madrigal, The Atlantic,
“Uber Drivers are About to Get a New Boss”

61. These programmers are not like factory workers

62. 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

63. When platforms get their
algorithms wrong, there can be
serious consequences!

67. The Equinix NY4 data center,
where trillions of dollars change hands

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

69. Values Alert: Structural Changes In the Economy
“In the 35 years between
their jobs as janitors,
corporations across
America have flocked to a
new management theory:
Focus on core competence
and outsource the rest.”

70. Bad Map Alert:
In 2018, we still believe that it’s only natural for
companies to maximize their profits, regardless
of the social, environmental and human
consequences

71. It doesn’t have to be that way
“We don’t hire
people to bake
brownies. We bake
brownies to hire
people.”
-Greyston Bakery,
Yonkers, NY

72. Big businesses are starting to wake up
“Society is demanding that companies, both
public and private, serve a social purpose. To
prosper over time, every company must not
only deliver financial performance, but also
show how it makes a positive contribution to
society. Companies must benefit all of their
stakeholders, including shareholders,
employees, customers, and the communities
in which they operate.”
Larry Fink,
CEO of Blackrock

73. “Doughnut Economics”
Kate Raworth,
Oxford

74. Boston Consulting Group: The Humanization of the Corporation

75. Your job will get a lot easier when businesses redraw the map
In the age of AI, we must
stop treating humans as
a cost to be eliminated!

76. What Does 21st Century Education Look Like?

77. “If the students we are training today are going to live to be
120 years old, and their careers are likely to span 90 years,
but their training will only make them competitive for 10
years, then we have a problem.”
Jeffrey Bleich,
Former US ambassador to Australia
Chair of the Fulbright scholarship board

78. On Demand Learning

79. A platform for people to teach each other

80. “Nanodegrees” targeted to the careers of the future

81. The Augmented Worker
Neo: “Can you fly that thing?”
Trinity: “Not yet.”

82. Performance Adjacent Learning

85. Work, not Jobs

86. In 2018, we are still trying to revive the old
economy, rather than inventing the future that is
possible now

87. The Law of Conservation of Attractive Profits
“When attractive profits disappear at
one stage in the value chain because a
product becomes modular and
commoditized, the opportunity to earn
attractive profits with proprietary
products will usually emerge at an
adjacent stage.”
Clayton Christensen,
Harvard Business School

88. New kinds of creative value

89. The great opportunity of the 21st century is to use our
newfound cognitive tools to solve previously unsolved
problems
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

90. “Biophilic work”
Natasha Iskander, NYU

91. A Social Investment Stipend?
We need “a new social contract, one that values and
rewards socially beneficial activities in the same way
that we currently reward economically productive
activities.”
- Kai Fu Lee, China’s most successful AI investor

93. A creative eldercare experiment in the Netherlands

94. Let the machines do as much of the work as
they can. Let humans get on with the real
work of the 21st century.

95. 50 experts in the workforce and employment ecosystem – including government
workforce agencies, community colleges, policy experts, labor, researchers,
nonprofits, funders gathered at the CfA Summit. Over the course of the two-hour
strategy session, we:
• Vetted and prioritized ideas in 5 opportunity areas on how Code for America
might help improve government service delivery
• Connected Code for America to potential partners/resources
• Built community and had fun!
Code for America Summit Strategy Workshop

96. CROSS-CUTTING THEMES
Several interrelated themes, desires and challenges, consistently surfaced over the course of the Strategy Session:
Siloed Gov’t
Systems
• Fragmentation of systems creates inefficiencies and limits user experience/outcomes, lack of incentives for
systems to change and lots of desire for more integrated approach and collaboration.
• Streamlining access, eligibility, and movement across multiple services and benefits (social and workforce)
for holistic person-centered approach
Data Quality and
Use
• Data interoperability challenge and desire for improvement – more data sharing, concerns about security/
privacy and data use/ethics. Data needs to be easy to aggregate and seen at the individual user level.
• Low data analysis capacity in government results in “bad” data-driven decisions.
Role of
Employers
• Need to increase employer engagement and commitment to train, hire, and advance “nontraditional” talent.
• No clear consensus on how to incentivize and develop relationships that flex with changes in the market.
Understanding
Users
• Hypothesis: People and funders will select high-performing skilling programs and outcomes will improve, if
performance data is accessible.
• Do we know if this is how jobseekers and employers make decisions?
Bias
• Lack of cultural competency in workforce systems.
• Employer/marketplace discrimination in hiring and advancement. Need training and tools to de-bias
systems and workplace culture.

97. Worker Advocate
(protects workers’ rights)
Talent Development Strategist
(serves as connector to skill
based training and employment)
Public/Private Convener
(catalyzes multi-sector efforts)
Data Scientist
(shares data to match
education, training, and good
jobs)
Employer
Funder
(encourages proven
community-based solutions)
Reimagining the Role of Gov’t in Workforce

98. Principles of delivery for CFA in workforce
1.Our focus should not be to support a broken ecosystem of services, but
supporting government to solve high impact problems.
2.Services should be centered around the jobseeker’s needs and
potential.
3.Implementation is a huge lever. Failure to implement better laws means
few actually benefit.
4.Without intelligent use of data to help diagnose problems, it is difficult
to know how to fix them.
5.Solutions should support workers to adapt to the future economy.

99. What if every Workforce Development
Board had a regional dashboard to
help them understand where to focus
their efforts?

100. What if every job seeker had easy access to the information
they need to make decisions about their career journey?

101. We’ve learned that we won’t know if any of these
potential solutions actually help people get and
keep quality jobs until we have better feedback
loops in the system.

102. We need to collaborate, deeply, to create
these feedback loops
We have to bring together data across the
workforce ecosystem, and pair that data with
user research to reimagine what workforce
services could look like.

103. We know that’s easier said than done, but we
have to be bold - the stakes are too high.
We need to join together in
a national movement to make this a reality.