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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
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Article 5. Equal vs Equitable: Algorithmic Fairness
Manage episode 439176132 series 3594717
المحتوى المقدم من Risk Insights: Yusuf Moolla. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Risk Insights: Yusuf Moolla أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.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).
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