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Future risks associated with machine learning explored in new report

A new study released by The Economist Intelligence Unit ran three econometric scenarios to 2030 on five countries — the United States, the United Kingdom, Australia, Japan—and developing Asia as a whole. In ‘Risks and rewards: Scenarios around the economic impact of machine learning’, commissioned by Google, two scenarios assumed greater human productivity through upskilling and greater investment in technology and access to open source data, while the third assumed insufficient policy support for structural changes in the economy.

The results showed that, although the fears of those pessimistic about the impact of machine learning, and artificial intelligence in general, may be overblown, the optimists’ claims are not entirely supported, either. The other area of the study, a look at the impact of machine learning on four industries, reaches a similar conclusion.

For firms both developing machine learning and those using it, the reports finds that communication between themselves, and with the public and policymakers, needs to improve. This includes doing better to manage expectations around the impact of machine learning, acknowledging the potential risks as well as the rewards, improving trust and transparency, and educating the public so that knowledge gaps are not filled with misinformation and distortion.

Read the report (PDF). 



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