With AI already changing the way in which society addresses economic and national security challenges and opportunities, AI technologies must be developed and used in a trustworthy and responsible manner. That means they need to ensure accuracy, explainability and interpretability, reliability, robustness, security (resilience), privacy, safety, and that bias is mitigated. Trustworthy data, standards, and integration of ML/AI in applications is critical for the successful deployment of new technologies for climate research, genomics, materials, and more. Delivering these needed measurements, standards, and other tools is a primary focus for NIST’s portfolio of AI efforts. This session provides an overview of NIST Trustworthy AI program.
Seminar link: http://bit.ly/Elham-Tabassi
Speaker Biography
Elham Tabassi is the Chief of Staff in the Information Technology Laboratory (ITL) at the National Institute of Standards and Technology (NIST). ITL, one of six research Laboratories within NIST, supports NIST’s mission, to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life. She has been working on various machine learning and computer vision research projects with applications in biometrics evaluation and standards since 1999. She is the principal architect of NIST Fingerprint Image Quality (NFIQ) which is now an international standard for measuring fingerprint image quality and has been deployed in many large scale biometric applications worldwide. She is a senior member of IEEE, and member of AAAI.