Michael A Osborne - 12 May 2015 - Technology at Work: The Future of Innovation and Employment
Duration: 1 hour 48 mins
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For decades economists, technologists, policy-makers and politicians have argued about whether automation destroys or creates jobs. And up to now the general consensus has been that while some jobs are eliminated by automation, more new jobs have, in general, been created. But recently, advances in computing power, machine learning and AI, software, sensor technology and data analytics have brought the "automation" question to the fore again. People are asking if a radical disruption is under way. Are we heading into a "second machine age" in which advanced robotics and intelligent computing make occupational categories that were hitherto reserved for humans vulnerable to automation? One of the most penetrating attempts to answer this question was the research conducted by Oxford scholars Michael Osborne and Carl Frey which resulted in a path-breaking report arguing that 47 per cent of US job categories might be vulnerable to computerisation in the next two decades.
In this Seminar, the first in the new Technology & Democracy project's series, Michael Osborne discusses his research and its implications. Michael A Osborne is an expert in the development of machine intelligence in sympathy with societal needs. His work on robust and scalable inference algorithms in Machine Learning has been successfully applied in diverse and challenging contexts, from aiding the detection of planets in distant solar systems to enabling self-driving cars to determine when their maps may have changed due to roadworks. Dr Osborne also has deep interests in the broader societal consequences of machine learning and robotics, and has analysed how intelligent algorithms might soon substitute for human workers. Dr Osborne is an Associate Professor in Machine Learning, a co-director of the Oxford Martin programme on Technology and Employment, an Official Fellow of Exeter College, and a Faculty Member of the Oxford-Man Institute for Quantitative Finance, all at the University of Oxford. |
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| Created: | 2015-05-14 10:04 |
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| Collection: | Technology and Democracy |
| Publisher: | University of Cambridge |
| Copyright: | Glenn Jobson |
| Language: | eng (English) |
| Keywords: | Technology and Democracy; CRASSH; Michael A Osborne; |
| Abstract: | For decades economists, technologists, policy-makers and politicians have argued about whether automation destroys or creates jobs. And up to now the general consensus has been that while some jobs are eliminated by automation, more new jobs have, in general, been created. But recently, advances in computing power, machine learning and AI, software, sensor technology and data analytics have brought the "automation" question to the fore again. People are asking if a radical disruption is under way. Are we heading into a "second machine age" in which advanced robotics and intelligent computing make occupational categories that were hitherto reserved for humans vulnerable to automation? One of the most penetrating attempts to answer this question was the research conducted by Oxford scholars Michael Osborne and Carl Frey which resulted in a path-breaking report arguing that 47 per cent of US job categories might be vulnerable to computerisation in the next two decades.
In this Seminar, the first in the new Technology & Democracy project's series, Michael Osborne discusses his research and its implications. Michael A Osborne is an expert in the development of machine intelligence in sympathy with societal needs. His work on robust and scalable inference algorithms in Machine Learning has been successfully applied in diverse and challenging contexts, from aiding the detection of planets in distant solar systems to enabling self-driving cars to determine when their maps may have changed due to roadworks. Dr Osborne also has deep interests in the broader societal consequences of machine learning and robotics, and has analysed how intelligent algorithms might soon substitute for human workers. Dr Osborne is an Associate Professor in Machine Learning, a co-director of the Oxford Martin programme on Technology and Employment, an Official Fellow of Exeter College, and a Faculty Member of the Oxford-Man Institute for Quantitative Finance, all at the University of Oxford. |
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