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Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Risk Insights: Yusuf Moolla
29 episodes
2 weeks ago
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.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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Management
Business
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All content for Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing is the property of Risk Insights: Yusuf Moolla and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.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).
Show more...
Management
Business
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Article 17. Algorithm Integrity: Audit vs Review
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
9 minutes
1 year ago
Article 17. Algorithm Integrity: Audit vs Review
Spoken by a human version of this article. The terminology – “audit” vs “review” - is important, but clarity about deliverables is more important when commissioning algorithm integrity assessments. Audits are formal, with an opinion or conclusion that can often be shared externally. Reviews come in various forms and typically produce recommendations, for internal use. Regardless of the terminology you use, when commissioning an assessment, clearly define and document the expected deliverable...
Algorithm Integrity Matters: for Financial Services leaders, to enhance fairness and accuracy in data processing
Spoken by a human version of this article. TL;DR (TL;DL?) Complexity must be actively managed rather than passively accepted.Data relevance directly impacts both accuracy and explainability.Technical “visibility” techniques can be useful.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).