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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
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Article 20. Algorithm Reviews: Public vs Private Reports
Manage episode 462005822 series 3594717
Вміст надано Risk Insights: Yusuf Moolla. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Risk Insights: Yusuf Moolla або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
Spoken (by a human) version of this article.
- Public AI audit reports aren't universally required; they mainly apply to high-risk applications and/or specific jurisdictions.
- The push for transparency primarily concerns independent audits, not internal reviews.
- Prepare by implementing ethical AI practices and conducting regular reviews.
Note: High-risk AI systems in banking and insurance are subject to specific requirements
Links
- AI and algorithm audit guidelines vary widely and are not universally applicable. We discussed this in a previous article, outlining how the appropriateness of audit guidance depends on your circumstances.
- Audit vs Review: we explored this topic in depth in a previous article.
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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