When generative AI can offer tricks such as analyzing long documents in a flash, the promise of artificial intelligence is very appealing. Agencies everywhere are trying to unlock and leverage its power potential, but when it comes to requirements that Federal Research has to meet, will AI make the grade?

This week at Feds At the Edge, experts dive into the challenges of integrating AI in government work.

Quentin Kreilmann, Deputy Director for the Center for AI at Pacific Northwest National Laboratory, warns AI enthusiasts to proceed with caution when it comes to sensitive data. Ramesh Menon, CTO at DIA, provides us with the critical questions to ask in order to ensure fair and unbiased data.

We’ll also explore medical data security and the risks of backdoor attacks.

Tune in on your favorite podcasting platform today to take a deep dive into AI’s potential, pitfalls, and the importance of transparency and human oversight.

To view this webinar: AI Promises to Unlock Research Potential to Solve Big Challenges.

Featured Speakers:

Basia Sall, Director of Data, Information Management & Enterprise Government, Office of the Chief Information Officer, Nuclear Regulatory Commission

Basia Sall
Director of DIME, OCIO,
Nuclear Regulatory Commission
Quentin Kreilmann, Deputy Director for the Center for AI, Pacific Northwest National Laboratory

Quentin Kreilmann
Deputy Director for the Center for AI,
Pacific Northwest National Laboratory
Tanna Nelson, Ph.D, R.N., NI-BC, Clinical Research Informatic Specialist, Center for Biomedical Informatics & Information Technology, NCI

Tanna Nelson
Clinical Research Informatic Specialist,
Center for Biomedical Informatics & IT, NCI
Ramesh Menon, Chief Technology Officer, Defense Intelligence Agency

Ramesh Menon
Chief Technology Officer,
Defense Intelligence Agency
Chris Cyr, Chief Technology Officer, Sterling

Chris Cyr
Chief Technology Officer,
Sterling
John Breeden II, Moderator & Contributing Editor, FedInsider

John Breeden II
Contributing Editor,
FedInsider

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