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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
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Article 27. Algorithmic System Integrity: Explainability (Part 4)
Manage episode 525185760 series 3594717
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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.
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).
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