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Royal Society Releases Report on Machine Learning

The Royal Society has published a 125-page report on machine learning, urging the government to invest in the technology and to foster its applications by making even larger datasets open and available to researchers and businesses.

The London-based science organisation engaged in dialogues with experts, investors and the general public —whose attitudes towards machine learning was probed in an attached Ipsos Mori survey—and eventually issued a series of recommendations ranging from the technical to the ethical-political.

One of the points the report hammers home is the need to embrace data sharing and open data schemes; data from the National Health Service is explicitly singled out as candidate for such schemes and called “one of the UK’s key data assets” .

The report also underlined the importance of educating citizens and professionals about machine learning as, over time, “these systems will become an important tool required by people of all ages and backgrounds.”

The Royal Society’s 15-member working group on machine learning advises policy-makers to create more PhD programmes in machine learning.

The report also tackled some of the paramount ethical and borderline political issues raised by the technology’s advances. The questions of privacy, security and “interpretability” —that is, how to understand why a machine learning system makes a certain decision of makes a given prediction—are duly highlighted as high-priority.

Some have taken exception with the report’s recommendations and conclusions. In particular, TechCrunch has featured a scathing diatribe pointing out how three members of the group that worked on the report are employees of some big technology corporations— Google DeepMind, Amazon and Uber— who would most stand to benefit from the open data approach suggested in the paper.


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