Article 27. Algorithmic System Integrity: Explainability (Part 4)

Spoken by a human version of this article.

TL;DR (TL;DL?)

• Explainability is necessary to build trust in AI systems.
• There is no universally accepted definition of explainability.
• So we focus on key considerations that don't require us to select any particular definition.

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About this podcast

A podcast for Financial Services leaders, where we discuss fairness and accuracy in the use of data, algorithms, and AI.

Hosted by Yusuf Moolla.
Produced by Risk Insights (riskinsights.com.au).