Measuring the Trustworthiness of AI Systems
• Podcast
Publisher
Software Engineering Institute
DOI (Digital Object Identifier)
10.58012/pb35-9p06Topic or Tag
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Abstract
The ability of artificial intelligence (AI) to partner with the software engineer, doctor, or warfighter depends on whether these end users trust the AI system to partner effectively with them and deliver the outcome promised. To build appropriate levels of trust, expectations must be managed for what AI can realistically deliver. In this podcast from the SEI’s AI Division, Carol Smith, a senior research scientist specializing in human-machine interaction, joins design researchers Katie Robinson and Alex Steiner, to discuss how to measure the trustworthiness of an AI system as well as questions that organizations should ask before determining if it wants to employ a new AI technology.
About the Speaker
Katherine-Marie Robinson
Katherine-Marie Robinson is an assistant design researcher in the SEI’s AI Division. Since joining the SEI in September 2022, Robinson has worked on a wide variety of projects where she aims to bring a responsible AI (RAI) lens to the work at hand including researching and developing tools, curriculums, and …
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Carol J. Smith
Carol Smith is a principal research scientist in the Software Engineering Institute’s (SEI’s) Artificial Intelligence (AI) Division leading research and development focused on improving user experiences (UX) and interactions with the nation’s AI systems, robotics, and other complex and emerging technologies. Smith’s research encompasses human-computer interaction (HCI), cognitive psychology, UX, …
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Alexandrea Steiner
Alexandrea Steiner is an assistant design researcher in the Artificial Intelligence (AI) Division at the SEI. She began her SEI career as a multimedia designer on the Communication Design team. Her role as a design researcher focuses on collaborating with others to understand challenges and design solutions that meet research …
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