Resources

58:37

58:37

Podcasts

Hype vs Reality & Building Responsibly at Every Stage of AI

Podcasts

1:00:00

1:00:00

Podcasts

Accelerate AI Risk Mitigation with XAI & Continuous Monitoring

Podcasts

43:00

43:00

Podcasts

Responsible AI with Maria Axente - "AI Ethics is a Team Sport"

Podcasts

47:00

47:00

Podcasts

The Past, Present, and Future States of Explainable AI

Podcasts

26:00

26:00

Videos

Achieving Responsible AI in Finance With Model Performance Management - Ai4 2021 Finance Summit

Videos

28:01

28:01

Videos

Innovating with Scott Amyx: Interview with Krishna Gade, CEO of Fiddler

Videos

35:18

35:18

Videos

The Future of Explainable AI: What is the Business Impact of XAI, Accountability, and Transparency?

Videos

Research

Unified Shapley Framework to Explain Prediction Drift

Aalok Shanbhag, Avijit Ghosh, Josh Rubin

Reports

AI Observability with Explainability

Reports

While monitoring by itself provides real-time issue visibility, it is often insufficient to identify the root cause of issues given the AI system’s complexity. Observability, a means to deduce internal state from its external outputs, is therefore critical to know the ‘why’ for a quick resolution. Explainable AI enables the deployment of high-risk AI solutions while AI Observability increases the success of these AI deployments.

6 videos

6 videos

Videos

AWS Howdy Partner: Meet Fiddler - Explainable AI for your MLOps

Videos

Research

Characterizing Intersectional Group Fairness with Worst-Case Comparisons

Avijit Ghosh, Lea Genuit, Mary Reagan

56:56

56:56

Videos

MLOps Meetup - How Explainable AI is Critical to Building Responsible AI

Videos