))
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
«
»
Article 5. Equal vs Equitable: Algorithmic Fairness
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 439176132 series 3594717
A tartalmat a Risk Insights: Yusuf Moolla biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Risk Insights: Yusuf Moolla vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Spoken (by a human) version of this article.
Fairness in algorithmic systems is a multi-faceted, and developing, topic.
In episode 4, we explored ten key aspects to consider when scoping an algorithm integrity audit.
One aspect was fairness, with this in the description: "...The design ensures equitable treatment..."
This raises an important question. Shouldn't we aim for equal, rather than equitable treatment?
This episode aims to shed light on the distinctions between equal and equitable treatment in algorithmic systems, while acknowledging that our understanding of fairness is still developing and subject to ongoing debate.
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 epizódok
Megosztás
