Enabling AI Adoption through Assurance

作者

  • Jaganmohan Chandrasekaran Virginia Tech
  • Feras A. Batarseh Virginia Tech
  • Laura Freeman Virginia Tech
  • Raghu Kacker NIST
  • M S Raunak NIST
  • Rick Kuhn NIST

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https://doi.org/10.32473/flairs.v35i.130726

关键词:

AI Assurance, Trustworthy AI, AI for Public Policy, AI Standards

摘要

With the broader adoption of AI-enabled software systems, it is necessary to provide assurance to the layman user that the AI system will behave as intended. This interactive tutorial will provide an overview of AI assurance, introduce a new set of assurance goals for AI systems, discuss the open challenges in AI assurance, and present recommendations to overcome its drawbacks.

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已出版

2022-05-04

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Chandrasekaran, J., Batarseh, F. A., Freeman, L., Kacker, R., Raunak, M. S., & Kuhn, R. (2022). Enabling AI Adoption through Assurance. The International FLAIRS Conference Proceedings, 35. https://doi.org/10.32473/flairs.v35i.130726

期

卷 35 (2022): Proceedings of FLAIRS-35

栏目

Tutorials

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