Evaluating Trustworthiness of AI Systems

AI system trustworthiness is dependent on end users’ confidence in the system’s ability to augment their needs. This confidence is gained through evidence of the system’s capabilities. Trustworthy systems are designed with an understanding of the context of use and careful attention to end-user needs. In this webcast, we’ll discuss how to evaluate trustworthiness of AI systems given their dynamic nature and the challenges of managing ongoing responsibility for maintaining trustworthiness.

What attendees will learn:

Basic understanding of what makes AI systems trustworthy
How to evaluate system outputs and confidence
How to evaluate trustworthiness to end users (and affected people/communities)

Speaker and Presenter Information

Carrie Gardner is a Technical Manager of the AI for Mission Center in the AI Division at the Software Engineering Institute. She is an accomplished technologist and strategist with extensive experience in advising government and business leaders on leveraging digital technologies to drive value and mitigate risk. She excels in collaborating with both public and private-sector sponsors, designing, prototyping, fielding, and scaling transformative and trustworthy digital solutions. Carrie's expertise spans various domains including AI, software development, privacy, and cybersecurity. She employs a wide range of methodologies such as rapid prototyping, engineering, qualitative and quantitative research, and management science to deliver impactful results.

Katherine-Marie Robinson is an Assistant Design Researcher in the AI Division at the Software Engineering Institute. She completed Bachelor of Science degrees in Biomedical Mechanical Engineering and Computing Technology at the University of Ottawa, Canada, in 2020. In the fourth year of her undergraduate degree, she became a member of the Canadian Robotics and Artificial Intelligence Ethical Design Lab (CRAiEDL) under the direction of Dr. Jason Millar, who is Canada’s Research Chair in Ethical Engineering of Robotics and AI. CRAiEDL’s mission is to connect ethics, engineering practice, and policy for responsible robotics and artificial intelligence (AI).

Carol Smith joined the SEI in 2019 and leads research in the AI Division to define AI engineering practices for human-centered and responsible AI and ML system development. She has been conducting human-computer interaction (HCI) and user experience (UX) research to improve the human experience with complex systems across industries for over 20 years. Since 2015 Smith has been advocating for AI ethics and responsible approaches for enabling human-machine teaming with AI systems, autonomous vehicles, and other emerging technologies.

Alex Steiner is an Associate Design Researcher in the AI Division at the Software Engineering Institute. She plans and implements forward-looking design research that supports current technical research work and strategic vision. She leverages the latest research and design practices to inform the design and development of AI systems, ensuring these systems are built to meet the needs of users and stakeholders.