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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
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เนื้อหาจัดทำโดย Risk Insights: Yusuf Moolla เนื้อหาพอดแคสต์ทั้งหมด รวมถึงตอน กราฟิก และคำอธิบายพอดแคสต์ได้รับการอัปโหลดและจัดหาให้โดยตรงจาก Risk Insights: Yusuf Moolla หรือพันธมิตรแพลตฟอร์มพอดแคสต์ของพวกเขา หากคุณเชื่อว่ามีบุคคลอื่นใช้งานที่มีลิขสิทธิ์ของคุณโดยไม่ได้รับอนุญาต คุณสามารถปฏิบัติตามขั้นตอนที่แสดงไว้ที่นี่ https://th.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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