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Article 28. Algorithmic System Integrity: Explainability (Part 5) - Privacy and Confidentiality
Spoken by a human version of this article.
TL;DR (TL;DL?)
- Algorithmic systems create challenges in balancing explainability with privacy and confidentiality.
- Key challenges include protecting sensitive information, preserving proprietary algorithms, and securing fraud detection systems.
- Focusing on what audiences need, with a few specific considerations, can help address these.
To subscribe to the weekly articles: https://riskinsights.com.au/blog#subscribe
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).
View all episodes
By Risk Insights: Yusuf MoollaSpoken by a human version of this article.
TL;DR (TL;DL?)
- Algorithmic systems create challenges in balancing explainability with privacy and confidentiality.
- Key challenges include protecting sensitive information, preserving proprietary algorithms, and securing fraud detection systems.
- Focusing on what audiences need, with a few specific considerations, can help address these.
To subscribe to the weekly articles: https://riskinsights.com.au/blog#subscribe
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).