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

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

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

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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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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).

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