))
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
»
Article 23. Algorithmic System Integrity: Testing
Fetch error
Hmmm there seems to be a problem fetching this series right now.
Last successful fetch was on October 30, 2025 20:37 (
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 467744728 series 3594717
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.
TL;DR (TL;DL?)
- Testing is a core basic step for algorithmic integrity.
- Testing involves various stages, from developer self-checks to UAT. Where these happen will depend on whether the system is built in-house or bought.
- Testing needs to cover several integrity aspects, including accuracy, fairness, security, privacy, and performance.
- Continuous testing is needed for AI systems, differing from traditional testing due to the way these newer systems change (without code changes).
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).
27 ตอน
แบ่งปัน
