The National Academies of Sciences, Engineering, Medicine (NASEM):

Assessing and improving AI trustworthiness presents a complicated set of challenges including robustness, accuracy, fairness, explainability, and privacy. Accounting for the trustworthiness of a given AI system involves a number of different performance measures and trade-offs. System designers, regulators, policymakers, and other stakeholders will each have to devise a set of tools to handle these challenges.

On March 3-4 from 12-5pm ET, the National Academies will convene Assessing and Improving AI Trustworthiness: Current Contexts, Potential Paths, a public workshop sponsored by the National Institute of Standards and Technology, to help think through the challenges associated with building trustworthy AI.

The workshop will feature leading voices from industry, such as Facebook Director of Applied Machine Learning Joaquin Quiñonero Candela, government officials such as Food and Drug Administration Director of Digital Health Bakul Patel, and academic experts such as Prof. Michael Kearns of the University of Pennsylvania. Attendees will hear about the real-world challenges and practices in designing trustworthy systems for areas such as finance, transportation, and health, and will relate these challenges to the latest research into AI trustworthiness and related issues such as fairness, robustness, and explainability. This workshop will work to produce initial ideas for activities and collaborations by academia, industry, and the public sector to improve the assessment of trustworthiness of AI systems.

Learn more about the event and download the preliminary agenda here.

Register here.