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The Future of AI and Work

The Future of AI and Work. Miles Brundage School for the Future of Innovation in Society Arizona State University. Overview. Overview of societal issues raised by AI Theories of technological unemployment AI as work improver AI as work reducer What to do?. Slide 2.

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The Future of AI and Work

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  1. The Future of AI and Work Miles Brundage School for the Future of Innovation in Society Arizona State University

  2. Overview • Overview of societal issues raised by AI • Theories of technological unemployment • AI as work improver • AI as work reducer • What to do? Slide 2

  3. The range of AI/society issues • Today: • Lethal autonomous weapons • Responsibility (e.g. for autonomous cars) • Impact on work • Privacy and bias issues in commercial systems • AI as problem solver (but which problems?) Increasing uncertainty… Slide 3

  4. The range of AI/society issues • Medium term: • Impacts on relationships (sex bots, preference for robot companionship) • Much more impact on work Increasing uncertainty… Slide 4

  5. The range of AI/society issues Increasing uncertainty… • Long term: • The control problem (Bostrom 2014) • Leisure society introduces new issues Slide 5

  6. Theories of technological unemployment • “Economic Possibilities for our Grandchildren” – John Maynard Keynes, 1930 • Major debate in 30’s, 60’s, 90’s, and to a lesser extent, today (Bix, 2000) • Is this time different? • Maybe, because of learning and broader range of abilities Slide 6

  7. Theories of job vulnerability • Murnane/Levy 2004: • Routine vs. non-routine • Frey and Osborne 2013: • Social intelligence • Creative intelligence • Perception and manipulation • Autor 2013: • Novelty of tasks • Brynjolfsson/McAfee 2014: • Creativity Frey and Osborne 2013 Slide 7

  8. Theories of job vulnerability: synthesis • The safest jobs seem to be non-routine, social, and creative, and involve perception, manipulation, and the performance of novel tasks. • Also, more highly paid jobs, all things being equal, can be more profitably automated, as can jobs done by many people. • Many international/regional implications… Slide 8

  9. AI as work improver • A common view (e.g. Brynjolfsson and McAfee 2014): • Robots and AI will do the dull, dirty, and dangerous tasks • Humans will do the challenging, novel, and safe tasks • Issues with this: • Technical issues • Incentive issues • Identity issues Slide 9

  10. AI as work reducer • End of work as threat… ….and opportunity Jerger, 1931 Slide 10

  11. AI as work reducer • How soon might substantial impacts occur? • Technical considerations • Commercialization and human capital considerations • Consumer preference considerations • Policy considerations Slide 11

  12. What to do?Aim for robustness • Research on technology forecasting, understanding ethical/political/economic issues, AI safety/transparency, etc. • Targetedfundingfor grand challenges • Building expertise/capacity in governments at all levels • Development of codes of conduct (e.g. EPSRC principles in the UK, ongoing work by major technology companies and IEEE) • Gradually rising basic income as economic productivity increases to enable greater choice in work/leisure split, less pressure to take bad jobs Slide 12

  13. Thanks! Slide 13

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