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Bias in AI: Impact, Challenges, and Opportunities

September 2021 Podcast
Carol J. Smith, Jonathan Spring

Carol Smith discusses with Jonathan Spring the hidden sources of bias in artificial intelligence (AI) systems and how systems developers can raise their awareness of bias, mitigate consequences, and reduce risks.

“How are they going to protect individuals? How are they going to protect the data that’s in the system and think through that? The systems don’t have rights and responsibilities. The people making the systems, the people operating the systems are the ones who have to be responsible for them.”

Publisher:

Software Engineering Institute

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Abstract

Carol Smith discusses with Jonathan Spring the hidden sources of bias in artificial intelligence (AI) systems and how systems developers can raise their awareness of bias, mitigate consequences, and reduce risks.

About the Speaker

Carol J. Smith

Carol J. Smith

Carol Smith is a senior research scientist in human-machine interaction with the Emerging Technology Center (ETC) Division at Carnegie Mellon University’s Software Engineering Institute (SEI). In this ...

Carol Smith is a senior research scientist in human-machine interaction with the Emerging Technology Center (ETC) Division at Carnegie Mellon University’s Software Engineering Institute (SEI). In this role Smith contributes to research and development focused on improving user experiences (UX) and interactions with the nation’s artificial intelligence (AI) systems, robotics, and other emerging technologies. Smith’s research includes human-computer interaction, cognitive psychology, ethics, and human-machine teaming. Smith is also an adjunct instructor for Carnegie Mellon University’s Human-Computer Interaction Institute where she has taught both bachelor and master’s level courses. Smith served two terms on the User Experience Professionals Association (UXPA) international board, is a contributor to the IEEE 7008 working group, and an editor for the Journal of Usability Studies. Prior to joining the SEI, Smith spent 19 years working in industry, conducting user experience research to improve human experiences and has been working to improve AI systems since 2015. Most recently as senior UX researcher for autonomous vehicle experiences at Uber ATG (now Aurora) and senior design manager and Discovery Tribe leader at IBM’s Watson. Smith holds a master’s degree in Human-Computer Interaction from DePaul University.

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Jonathan Spring

Jonathan Spring

Jonathan Spring is a senior member of the technical staff with the CERT division of the Software Engineering Institute (SEI) at Carnegie Mellon University. Spring began working at the SEI in 2009. ...

Jonathan Spring is a senior member of the technical staff with the CERT division of the Software Engineering Institute (SEI) at Carnegie Mellon University. Spring began working at the SEI in 2009. Prior posts include adjunct professor at the University of Pittsburgh’s School of Information Sciences and research fellow for the ICANN’s Security and Stability Advisory Committee (SSAC). At the SEI, Spring’s work focuses on producing reliable evidence for various levels of cybersecurity policies. Spring’s approach to work balances leading by example with reflecting on study design and other philosophical issues. Spring earned a doctoral degree in computer science from University College London.

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