About this Talk: This panel explores the relationship between brain research and artificial intelligence advancements,
including the social and ethical implications of building machines that think like humans.
About the Speakers: Stephanie J. Bird, PhD (moderator) is a laboratory-trained neuroscientist whose professional interests
are two-fold: the ethical, legal and social policy implications of scientific research, especially neuroscience; and education
in the responsible conduct of research and the professional responsibilities of scientists and engineers. As an independent
consultant she works with institutions of higher learning, professional societies, government agencies, and law firms in the
United States and other countries. In addition, Dr. Bird is co-Editor-in-Chief of Science and Engineering Ethics, an international
publication that explores ethical issues of concern to scientists and engineers. Now in its 23rd year, the journal is widely
abstracted and indexed and has been cited by the National Academies as a leading resource for scholarly articles on research
integrity.
Dr. David Danks is the L.L. Thurstone Professor of Philosophy and Psychology and the head of the department of Philosophy
at Carnegie Mellon University. His research largely falls at the intersection of philosophy, cognitive science, and machine
learning, using ideas and frameworks from each to inform the others. His primary research in recent years has been in computational
cognitive science: developing fully-specified computational models to describe, predict, and most importantly, explain human
behavior. His other major research project, partly supported by an Andrew Carnegie Fellowship, has focused on the human impacts
when autonomy is introduced into a technological system. In particular, he has examined the relations of trust and identity
as they are affected by technologies such as self-driving vehicles, autonomous weapons systems, and autonomous cyber-systems.
Eleonore Pauwels is a writer and international science policy expert, who specializes in the governance of emerging and
converging technologies. At the Wilson Center, she is the Director of Biology Collectives, within the Science and Technology
Innovation Program. Her research focuses on the convergence of transformative technologies such as artificial intelligence,
genome-editing, digital bio-engineering and automation technologies. She analyzes the promises and perils that will likely
arise with the development of the Internet of Living Things and future networks of intelligent and connected bio-labs. Her
work also fosters the democratization of disruptive health technologies, including AI and genomics, and the inclusion of patients
and citizens through participatory health design (her Citizen Health Innovators Project). Eleonore regularly testifies before
U.S. and European authorities including the U.S. Department of State, NAS, NIH, NCI, FDA, the National Intelligence Council,
the European Commission and the UN. But she is also well-versed in communicating complex and novel scientific developments
for lay audiences (her TEDxCERN on CRISPR) and her writing has been featured in media outlets such as Nature, The New York
Times, The Guardian, Scientific American, Le Monde, Slate and The Miami Herald.
Dr. Michael Wolmetz is a Senior Scientist at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) Intelligent
Systems Center, where he leads several research teams integrating psychological and brain sciences with research and development
in machine learning, robotics, and human-machine interaction. His primary research focus is on how the mind and brain process
information during language comprehension and communication, and whether basic science in these areas can be translated into
applications to enhance defense, intelligence and clinical practices. He currently serves on the JHU Science of Learning Institute
steering committee, and his work is supported by the Intelligence Advanced Research Projects Activity (IARPA), the US Department
of Defense, Facebook, and others.
Recorded at the IEEE TechEthics Conference, held on 13 October 2017 at the National Academy of Sciences Building in Washington,
DC. The conference was made possible in part by a grant from the IEEE Foundation. Special thanks to the National Academy of
Engineering.