))
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
«
»
Article 16. Algorithmic System Accuracy Reviews – Choosing the Right Approach
Manage episode 453207773 series 3594717
Content provided by Risk Insights: Yusuf Moolla. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Risk Insights: Yusuf Moolla or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Spoken (by a human) version of this article.
- Outcome-focused accuracy reviews directly verify results, offering more robust assurance than process-focused methods.
- This approach can catch translation errors, unintended consequences, and edge cases that process reviews might miss.
- While more time-consuming and complex, outcome-focused reviews provide deeper insights into system reliability and accuracy.
This article explains why verifying outcomes is preferred over tracing through processes, and how it works.
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).
19 episodes
Share
