Sign up to save your podcasts
Or
Share 075 - Guest: Michael Hind, IBM AI Explainability Expert, part 2
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
075 - Guest: Michael Hind, IBM AI Explainability Expert, part 2
This and all episodes at: https://aiandyou.net/ .
Training an AI to render accurate decisions for important questions can be useless and dangerous if it cannot tell you why it made those decisions. Enter explainability, a term so new that it isn't in spellcheckers but is critical to the successful future of AI in critical applications.
Michael Hind is a Distinguished Research Staff Member in the IBM
Research AI department in Yorktown Heights, New York. His current
research passion is the area of Trusted AI, focusing on governance,
transparency, explainability, and fairness of AI systems. He helped launch several successful open source projects, such as
AI Fairness 360 and AI Explainability 360.
In part 2, we talk about the Teaching Explainable Decisions project, some of Michael’s experience with Watson, the difference between transparency and explainability, and a lot more.
All this plus our usual look at today's AI headlines.
Transcript and URLs referenced at HumanCusp Blog.
View all episodes
By aiandyou
5
1010 ratings
This and all episodes at: https://aiandyou.net/ .
Training an AI to render accurate decisions for important questions can be useless and dangerous if it cannot tell you why it made those decisions. Enter explainability, a term so new that it isn't in spellcheckers but is critical to the successful future of AI in critical applications.
Michael Hind is a Distinguished Research Staff Member in the IBM
Research AI department in Yorktown Heights, New York. His current
research passion is the area of Trusted AI, focusing on governance,
transparency, explainability, and fairness of AI systems. He helped launch several successful open source projects, such as
AI Fairness 360 and AI Explainability 360.
In part 2, we talk about the Teaching Explainable Decisions project, some of Michael’s experience with Watson, the difference between transparency and explainability, and a lot more.
All this plus our usual look at today's AI headlines.
Transcript and URLs referenced at HumanCusp Blog.
More shows like Artificial Intelligence and You
View all
Freakonomics Radio
32,092 Listeners
The Joe Rogan Experience
228,260 Listeners
StarTalk Radio
14,395 Listeners
This Week in Startups
1,289 Listeners
The AI in Business Podcast
169 Listeners
The Quanta Podcast
549 Listeners
NVIDIA AI Podcast
346 Listeners
All-In with Chamath, Jason, Sacks & Friedberg
10,182 Listeners
Dwarkesh Podcast
571 Listeners
Big Technology Podcast
505 Listeners
Hard Fork
5,529 Listeners
No Priors: Artificial Intelligence | Technology | Startups
144 Listeners
This Day in AI Podcast
228 Listeners
The AI Daily Brief: Artificial Intelligence News and Analysis
690 Listeners
AI Hustle: Make Money with AI
89 Listeners