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Responsible AI

A Facebook Live Series Sponsored by Hitachi

Artificial intelligence technologies are rapidly advancing and are becoming increasingly pervasive in many facets of everyday life. Technologies, such as facial recognition, machine learning, and natural language processing are all growing in their applications for private and public use, and as their utility increases, so do questions about their social implications.

The AAAS Responsible AI Series, with support from Hitachi, aims to explore artificial intelligence technologies, their current capabilities, their ethical and policy implications, and the responsibilities of the scientists and engineers developing the technologies. Join us as we interview leading AI experts to debunk the myths and set the record straight about where development of these technologies is and where it is going.

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Video Archive

Facial Recognition and Scientific Responsibility

September 10, 2019 | Original Announcement

Facial recognition is one type of artificial intelligence that is becoming ever more pervasive in our society. It can make our lives easier by accomplishing various tasks such as unlocking smartphones with just a glance, and automatically tagging our friends and family in photos on social media. However, many ethical, legal and human rights concerns exist about facial recognition, from inaccuracies in the technology to its application as a means of general surveillance. Given this, what are the responsibilities of developers and users to ensure facial recognition is transparently, ethically, and justly developed and applied?

AAAS Event Examines Readiness and Impact of Facial Recognition Technology on Society (AAAS News)

Children interact with toys designed with artificial intelligence-based technologies and are doing so in increasingly nuanced ways. Intelligent toys and other smart robots for children can deliver educational content, inspire emotional bonds, and even help children with autism build social skills. However, these devices also raise ethical, legal, and human rights concerns.

Additional Resources

  1. Executive Summary: Artificial Intelligence and Children's Rights (UNICEF Innovation and Human Rights Center, UC Berkeley, 2019)

Articles from the Science Family of Journals

  1. Improving social skills in children with ASD using a long-term, in-home social robot (Scassellati et al., 2018)
  2. Personalized machine learning for robot perception of affect and engagement in autism therapy (Rudovic et al., 2018)
  3. How artificial intelligence lets Barbie talk to children (DeMarco, 2015)
  4. Minds of their own (Service, 2014)

Opening the Medical "Black-Box"

January 23, 2020 | Original Announcement

Artificial intelligence (AI) promises to revolutionize the future of health care. New technologies have the potential to assist in the detection of strokes and prediction of seizures, the identification of individuals who are at higher risk of domestic violence, and even with the development of patient treatment plans. AI medical technologies may even help doctors provide greater access to care to remote individuals and communities. Parallel to this utopian vision of AI-driven health care is a dystopian future where health data collected through wearable devices are sold to third parties and used against patients by insurers, employers or even banks. As AI continues its integration into the offices and operating theatres of medical professions, what are the ethical and human rights issues that arise?

"Talking points" summary of the discussion

Articles from the Science Family of Journals

  1. Algorithms on regulatory lockdown in medicine (Babic et al., 2019)
  2. Artificial intelligence for global health (Hosny and Aerts, 2019)
  3. AI in resource-poor health care systems (Alderton, 2019)
  4. Medicine contends with how to use artificial intelligence (Couzin-Frankel, 2019)
  5. Adversarial attacks on medical machine learning (Finlayson et al., 2019)
  6. Regulation of predictive analytics in medicine (Parikh et al., 2019)
  7. Artificial intelligence could diagnose rare disorders using just a photo of a face (Schembri, 2019)
  8. Big data and black-box medical algorithms (Price, 2018)
  9. Health and societal implications of medical and technological advances (Dzau and Balatbat, 2018)
  10. Turning skin “check” into checkmate (Lev-Tov, 2017)

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