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The Frontiers of Machine Learning 2017 Raymond and Beverly Sackler U.S.-U.K. Scientific Forum (2018) / Chapter Skim
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3 The Future of Machine Learning
Pages 20-23

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From page 20...
... To push forward the boundar ies of machine learning, engineers, data scientists, and computer scientists can benefit from the following perspectives: • Sociologists could play important roles, including discussing the ethical and societal issues of the technology; • Psychologists and human factors experts could offer insight on the ways in which humans interact with technology; 20
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From page 21...
... ALGORITHM DEVELOPMENT AND MODEL CONSTRUCTION Advances in the technical abilities of machine learning algorithms have contributed to the recent success of the field. Algorithms are "encoded procedures for solving a problem by transforming input data into a desired output, based on specified calculations and procedures." 15 They perform specific tasks, and it is important to consider how they will be used and what will be the explicit trade-offs involved in each use case.
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From page 22...
... In the European Union, the General Data Protec tion Regulation, which is expected to take effect in May 2018, will address "automated individual decision making, including profiling" and notes that a person "shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her," and that, if such processing is necessary, the person will have "at least the right to obtain human intervention [...] to express his or her point of view and to contest the decision."17 Furthermore, the regulation re quires that if profiling is used, the person should have access to "meaningful information about the logic involved."18 16 Panel on the One Hundred Year Study on Artificial Intelligence, "Artificial Intelligence and Life in 2030." 17 DSB-MIT-SYSTEM, "Article 22 EU GDPR: Automated Individual Decision-making, Including Profiling," http://www.privacy-regulation.eu/en/22.htm, accessed June 16, 2017.
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From page 23...
... Research from different sec tors is often complementary, and providing access to data and real examples is crucial to ensure that learning and best practices spread quickly. Continued funding to support academic research and education in the field of machine learning and related areas can also help move the field forward.
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Key Terms

  • artificial intelligence
  • technical abilities
  • false negatives
  • information consistent
  • set standards

  • forming input
  • algorithm development
  • produces legal
  • determining acceptable
  • based solely

  • construction advances
  • protected personal
  • encouraging researchers
  • online learning
  • help shape

  • including profiling
  • findings publicly
  • policy highlight
  • encode social
  • governance approaches

  • specified calculations
  • approaches based
  • tially provide
  • legal effects
  • support academic

  • learning algorithms
  • targeted regulation
  • policy discussions
  • standards related
  • criteria based


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