{"id":4975,"date":"2017-10-26T09:39:31","date_gmt":"2017-10-26T09:39:31","guid":{"rendered":"https:\/\/dataethics.eu\/?p=4975"},"modified":"2017-10-26T09:41:50","modified_gmt":"2017-10-26T09:41:50","slug":"new-ai-report-4-risk-areas-10-recommendations","status":"publish","type":"post","link":"https:\/\/dataethics.eu\/da\/new-ai-report-4-risk-areas-10-recommendations\/","title":{"rendered":"New AI Report: 4 Risk Areas and 10 Recommendations"},"content":{"rendered":"

Research. AI does not exist in a vacuum and the promises of the tech companies behind are not enough. New report highlights four challenge areas and gives recommendations on how to proceed.
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Artificial intelligent (AI) systems are already integrated in everyday tech like smartphones and personal assistants, making predictions that personalize experiences, ads and content. And AI is being introduced into more critical areas like law, finance, policing and the workplace. AI companies promise that what they create can automate repetitive work, identify behavioral patterns and much more. However, the analysis and understanding of AI should not be limited to technical capabilities. The design and implementation of AI presents deep normative and ethical challenges for our existing social, economic and political relationships and institutions. We must ask if and how AI is widening inequality and intensification of concentrated power and populist political movements will shape and be shaped.<\/div>\n
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The AI Now 2017 Report identifies a range of challenges within AI:<\/div>\n
Labor and Automation<\/strong>, including Universal Basic Income and the balance of workplace power.<\/div>\n
Bias and Inclusion,<\/strong> including the risk of amplifying cultural assumptions and inequalities.<\/div>\n
Rights and Liberties<\/strong> when it comes to government and health institutions implemeting AI for sensitive tasks<\/div>\n
Ethics and Governance,<\/strong> including military use of AI.<\/div>\n
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The report, made by Alex Campolo, Madelyn Sanfilippo, Meredith Whittaker and Kate Crawford, all from New York University and the two latter both from AI Now and from respectively Google Open Research and Microsoft Research, has 10 recommendations. Among them are;<\/div>\n