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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
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
We have to let go of the maps that are steering us wrong
In 1625, we thought
California was an island
In 2018, we believe that it is technology
that puts people out of work
“…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?”
Will there really be nothing left for people to do?
Is there really
nothing left for
humans to do?
What's the Future of Work with AI?
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
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
What happened when Amazon added 45,000 robots
Jeff Bezos calls this “the flywheel”
This is the master design pattern
for applying technology: Do more.
Do things that were previously
unimaginable.
The March of Progress
It is machines that help us
to feed 7 billion
What happened when we made food abundant?
We found new ways to add value to food
Number of craft breweries in the US, 1994-2017
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
There’s plenty to go around.
It’s just not going around well enough!
Divergence of productivity
and real median family income in the US
“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
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
This is something digital systems are good at
“The opportunity for AI is to help humans model
and manage complex interacting systems.”
Paul R. Cohen
We are all living and working inside a machine
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.
Amazon.com
An Amazon warehouse is a human-machine hybrid
What's the Future of Work with AI?
These apps teach us about some ways the world has changed
And about the mindset
required to redraw the
map
In 2000, we thought hailing a cab looked like this
Photo by Timothy Krause, Flickr
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!
“Framing blindness”
What's the Future of Work with AI?
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
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
Where’s the magical app for workforce development
that makes everything
simple, beautiful, and easy to use?
In 2018, workforce development looks like this
There are so many possible paths,
it’s easy to get lost along the way.
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
Q2/Q3 Design
Prototypes
Uber … Google … Amazon
are not apps. They are systems.
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
“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
Jeff Bezos understands this deeply
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
A algorithmic matching marketplace
of drivers and passengers
What's the Future of Work with AI?
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?
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
What might that look like for workforce development?
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
Platforms Decide Who Gets What – and Why
Good markets are the outcome of
good design decisions.
A better designed marketplace can
have better outcomes.
“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”
These programmers are not like factory workers
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
When platforms get their
algorithms wrong, there can be
serious consequences!
What's the Future of Work with AI?
What's the Future of Work with AI?
What's the Future of Work with AI?
The Equinix NY4 data center,
where trillions of dollars change hands
What is the objective function of our financial markets?
“The Social Responsibility of Business Is to
Increase Its Profits”
Milton Friedman, 1970
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.”
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
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
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
“Doughnut Economics”
Kate Raworth,
Oxford
Boston Consulting Group: The Humanization of the Corporation
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!
What Does 21st Century Education Look Like?
“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
On Demand Learning
A platform for people to teach each other
“Nanodegrees” targeted to the careers of the future
The Augmented Worker
Neo: “Can you fly that thing?”
Trinity: “Not yet.”
Performance Adjacent Learning
What's the Future of Work with AI?
What's the Future of Work with AI?
Work, not Jobs
In 2018, we are still trying to revive the old
economy, rather than inventing the future that is
possible now
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
New kinds of creative value
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
“Biophilic work”
Natasha Iskander, NYU
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
What's the Future of Work with AI?
A creative eldercare experiment in the Netherlands
Let the machines do as much of the work as
they can. Let humans get on with the real
work of the 21st century.
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
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.
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
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.
What if every Workforce Development
Board had a regional dashboard to
help them understand where to focus
their efforts?
What if every job seeker had easy access to the information
they need to make decisions about their career journey?
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.
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.
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.
What's the Future of Work with AI?

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What's the Future of Work with AI?

  • 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.
  • 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!
  • 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
  • 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
  • 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
  • 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.”
  • 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
  • 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.