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LLM Explainability with Umang Bhatt

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Manage episode 472049548 series 3587588
Content provided by Enzai. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Enzai or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

This episode of the AI Governance Podcast features Dr. Umang Bhatt. Umang is an Assistant Professor and Faculty Fellow at the Center for Data Science at New York University, a Senior Research Associate at the Alan Turing Institute and a leading researcher in the fields of AI explainability and transparency.

Umang joined Enzai’s Var Shankar to discuss:

  • How organizations might explain the workings of generative AI systems to end-users
  • Practical approaches to restricting access to generative AI systems, their outputs, and what they can be used for
  • Why it is important to close the loop on feedback from internal stakeholders
  • How AI can have a positive impact globally by personalizing education
  • How to promote responsible AI approaches from beyond North America, the EU and China
  continue reading

13 episodes

Artwork
iconShare
 
Manage episode 472049548 series 3587588
Content provided by Enzai. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Enzai or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

This episode of the AI Governance Podcast features Dr. Umang Bhatt. Umang is an Assistant Professor and Faculty Fellow at the Center for Data Science at New York University, a Senior Research Associate at the Alan Turing Institute and a leading researcher in the fields of AI explainability and transparency.

Umang joined Enzai’s Var Shankar to discuss:

  • How organizations might explain the workings of generative AI systems to end-users
  • Practical approaches to restricting access to generative AI systems, their outputs, and what they can be used for
  • Why it is important to close the loop on feedback from internal stakeholders
  • How AI can have a positive impact globally by personalizing education
  • How to promote responsible AI approaches from beyond North America, the EU and China
  continue reading

13 episodes

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