"Forecasts of AI and future jobs in 2030: Muddling through likely, with two alternative scenarios"
by Halal, William; Kolber, Jonathan; Davies, Owen; Global, T (2017)
Abstract
After decades of failed promises, artificial intelligence (AI) is now taking off. Yesterday’s doubters have been silenced, and the only current debate is about how deep and how fast intelligent machines will automate jobs, and whether the same technological forces will generate enough new work.Several forecasts suggest AI is likely to eliminate almost half of present jobs by 2025, resulting in massive unemployment (Rutkin, 2013). [...] This study addresses the looming issue of unemployment by forecasting the future distribution of jobs in categories across the occupational spectrum. We first summarize background data from the literature and present two alternative perspectives for consideration. Then results of a TechCast survey of experts concludes that a “Muddling Through” period of turmoil but relatively few net job losses is most likely. We also present two alternative scenarios.
Key Passage
Some new jobs may appear, but they will not last for long. Machines have begun to learn by observation, by trial and error, and even from other machines—as we do, but much faster. They are likely to master most new occupations before we humans ever have the chance. We face a time when humans will hop from one career to the next, struggling to stay ahead of automation. Saddled by debt and discouraged by a broken social contract, many may succumb to despair unless we find an alternative to endless retraining. (p.89)
Keywords
Machine Learning, Artificial Intelligence, Unemployment, The Future Of Work, Worker Replacement, Automation, TechnologyThemes
Future of Work, Unemployment, AI and Computerisation, AutomationLinks to Reference
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