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Machine learning:Trends, perspectives, and prospects

Despite practical challenges, we are hopeful thatinformeddiscussionsamongpolicy-maker sandthepublic about data and the capabilities of machinelearning, will lead to insightful designs of programsand policies that can balance the goals of protectingprivacy and ensuring fairness with those of reapingthe benefits to scientific research and to individualand public health. Our commitments to privacy andfairness are evergreen, but our policy choices mustadapt to advance them, and support new tech-niques for deepening our AND NOTES1. M. De Choudhury, S. Counts, E. Horvitz, A. Hoff, inProceedingsof International Conference on Weblogs and Social Media[Association for the Advancement of Artificial Intelligence(AAAI), Palo Alto, CA, 2014].

The effect of ma-chine learning has also been felt broadly across computer science and across a range of indus-tries concerned with data-intensive issues, such as consumer services, the diagnosis of faults in complex systems, and the control of logistics chains. There has been a similarly broad range of

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