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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
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محتوای ارائه شده توسط Risk Insights: Yusuf Moolla. تمام محتوای پادکست شامل قسمتها، گرافیکها و توضیحات پادکست مستقیماً توسط Risk Insights: Yusuf Moolla یا شریک پلتفرم پادکست آنها آپلود و ارائه میشوند. اگر فکر میکنید شخصی بدون اجازه شما از اثر دارای حق نسخهبرداری شما استفاده میکند، میتوانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.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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