Spoken (by a human) version of this article.

With algorithmic systems, an change can trigger a cascade of unintended consequences, potentially compromising fairness, accountability, and public trust.

So, managing changes is important. But if you use the wrong framework, your change control process may tick the boxes, but be both ineffective and inefficient.

This article outlines a potential solution: a risk focused, principles-based approach to change control for algorithmic systems.

Resource mentioned in the article: ISA 315 guideline for general IT controls.

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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).