Difference between revisions of "AI Research"
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[https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf Future of Employment: How susceptible are jobs to computerization] - 2013 - Oxford University <br> | [https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf Future of Employment: How susceptible are jobs to computerization] - 2013 - Oxford University <br> |
Revision as of 15:14, 2 February 2020
Future of Employment: How susceptible are jobs to computerization - 2013 - Oxford University
- Author's - Carl Benedikt Frey and Michael A Osborn
- 47 percent of U.S. jobs could be automated within the next decade or two
- occupation-based evaluation
- evaluated the likelihood that 71 occupations could be automated
- modeled the impact on 632 additional occupations
- they estimated what was technically possible
Risk of Automation for Jobs in OECD Countries: A Comparative Analysis (pdf) - 2016 - OECD
- task-based approach
- 9 percent of jobs in U.S. were at high risk for automation
- based on at least 70% of the jobs task could be automated
Will robots really steal our jobs? An international analysis of the potential long term impact of automation - 2017 - PWC
- 38 percent of jobs in the United States were at high risk of automation by the early 2030s.
- stated jobs that could be automated, yet actual losses will be mitigated by regulatory, legal and social dynamics
Harnessing automation for a future that works - 2017 - McKinsey
- 50 percent of work tasks around the world are already automatable
- 30 percent of work activities could be automated by 2030
- only 14 percent of workers would need to change occupations
2030: The Collision of Demographics, Automation and Inequality - Feb 2018 - Bain and Company
- employers will need 20 to 25 percent fewer employees by 2030
- that's equal to 30 to 40 million displaced workers in the United States
- 80 percent of all workers will be affected
Prediction Challenges
- many jobs have a mix of tasks - some can be automated and other cannot
- entirely new occupations
- enablement jobs
- speed of technology deployment - if it can be automated, it may not be done for many reasons
- demand from lowering the cost of goods and services production
- shift of spending to other goods and services if savings
- AI Startups find a whole new way to satisfy a human need