O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.

What's the Future of Work with AI?

10.137 visualizações

Publicada em

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.

Publicada em: Tecnologia
  • Login to see the comments

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?
  7. 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
  8. 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
  9. What happened when Amazon added 45,000 robots
  10. Jeff Bezos calls this “the flywheel”
  11. This is the master design pattern for applying technology: Do more. Do things that were previously unimaginable.
  12. The March of Progress
  13. It is machines that help us to feed 7 billion
  14. What happened when we made food abundant?
  15. We found new ways to add value to food
  16. Number of craft breweries in the US, 1994-2017
  17. 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
  18. There’s plenty to go around. It’s just not going around well enough!
  19. Divergence of productivity and real median family income in the US
  20. “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
  21. 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
  22. This is something digital systems are good at
  23. “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
  24. We are all living and working inside a machine
  25. 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.
  26. Amazon.com
  27. An Amazon warehouse is a human-machine hybrid
  28. These apps teach us about some ways the world has changed And about the mindset required to redraw the map
  29. In 2000, we thought hailing a cab looked like this Photo by Timothy Krause, Flickr
  30. 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!
  31. “Framing blindness”
  32. 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
  33. 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
  34. Where’s the magical app for workforce development that makes everything simple, beautiful, and easy to use?
  35. In 2018, workforce development looks like this
  36. There are so many possible paths, it’s easy to get lost along the way.
  37. 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
  38. Q2/Q3 Design Prototypes
  39. Uber … Google … Amazon are not apps. They are systems.
  40. 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
  41. “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
  42. Jeff Bezos understands this deeply
  43. 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
  44. A algorithmic matching marketplace of drivers and passengers
  45. 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?
  46. 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
  47. What might that look like for workforce development?
  48. Platforms Decide Who Gets What – and Why Good markets are the outcome of good design decisions. A better designed marketplace can have better outcomes.
  49. “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”
  50. These programmers are not like factory workers
  51. 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
  52. When platforms get their algorithms wrong, there can be serious consequences!
  53. The Equinix NY4 data center, where trillions of dollars change hands
  54. What is the objective function of our financial markets? “The Social Responsibility of Business Is to Increase Its Profits” Milton Friedman, 1970
  55. 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.”
  56. 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
  57. 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
  58. 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
  59. “Doughnut Economics” Kate Raworth, Oxford
  60. Boston Consulting Group: The Humanization of the Corporation
  61. 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!
  62. What Does 21st Century Education Look Like?
  63. “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
  64. On Demand Learning
  65. A platform for people to teach each other
  66. “Nanodegrees” targeted to the careers of the future
  67. The Augmented Worker Neo: “Can you fly that thing?” Trinity: “Not yet.”
  68. Performance Adjacent Learning
  69. Work, not Jobs
  70. In 2018, we are still trying to revive the old economy, rather than inventing the future that is possible now
  71. 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
  72. New kinds of creative value
  73. 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
  74. “Biophilic work” Natasha Iskander, NYU
  75. 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
  76. A creative eldercare experiment in the Netherlands
  77. Let the machines do as much of the work as they can. Let humans get on with the real work of the 21st century.
  78. 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
  79. 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.
  80. 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
  81. 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.
  82. What if every Workforce Development Board had a regional dashboard to help them understand where to focus their efforts?
  83. What if every job seeker had easy access to the information they need to make decisions about their career journey?
  84. 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.
  85. 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.
  86. 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.