Show Notes

AI technology has now reached the point where it can potentially damage the reputation of an organisation, if improperly managed. As a result, many data scientists are now becoming very interested in understanding AI ethics and responsible AI.

In this episode of Value Driven Data Science, Chris Dolman joins Dr Genevieve Hayes to discuss strategies organisations and data scientists can apply to de-risk automated decisions, and in doing so, avoid an AI scandal.

Guest Bio

Chris Dolman is the Executive Manager, Data and Algorithmic Ethics at Insurance Australia Group, a Gradiant Institute Fellow and regularly contributes to external research on responsible AI and AI ethics. In 2022, he was named the Australian Actuaries Institute’s Actuary of the Year, in recognition of his work around data ethics, and was also included in Corinium Global Intelligence – Business of Data’s list of the Top 100 Innovators in Data and Analytics.

Talking Points

  • The risks associated with the use or design of AI-based decision-making tools.
  • How these risks might potentially be amplified in the case of new, cutting-edge algorithms, such as ChatGPT.
  • Why “boring” is sometimes better, when it comes to AI.
  • Examples of where things have gone wrong in the past.
  • Strategies for identifying and avoiding potential AI scandals before they occur.
  • The regulation and governance of AI, both now and in the future.


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Value Driven Data Science
Episode 17: How to Avoid an AI Scandal