Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
«
»
Article 10. Fairness reviews: identifying essential attributes
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 445316882 series 3594717
Spoken (by a human) version of this article.
When we're checking for fairness in our algorithmic systems (incl. processes, models, rules), we often ask:
What are the personal characteristics or attributes that, if used, could lead to discrimination?
This article provides a basic framework for identifying and categorising these attributes.
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 эпизодов