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Episode 70: Uncovering AI Bias and Fairness - Starring Sue Black
  • Coffee Talk

#70 — Uncovering AI Bias and Fairness - Starring Sue Black

In this episode, Henrike von Platen sits down with Dr Sue Black OBE, a professor of computer science and technology evangelist at Durham University. They dive into the fascinating topic of bias in AI, discussing real-world examples and the implications of biased AI systems.

Welcome to another episode of Margret and Henrike's Coffee Talks!

Sue shares insights from her work and research, including a compelling story about facial recognition software and its limitations. They also explore how AI can impact fairness in the workplace and the importance of awareness and education in mitigating bias. Don't miss this engaging conversation!

Key Takeaways

  1. Bias in AI Systems: Sue Black shared real-world examples of bias in AI, such as facial recognition software failing to recognize people with darker skin tones because it was primarily trained on images of people with lighter skin.
  2. Impact of Bias: The discussion highlighted how biased AI systems can have significant implications, particularly in areas like workplace fairness and pay equity.
  3. Awareness and Education: Both Henrike and Sue emphasized the importance of being aware of bias in AI systems. Sue mentioned that while it might be impossible to completely eliminate bias, educating ourselves about it is crucial.
  4. Regulation and Human Oversight: Sue suggested that regulation is important, but equally important is the need for human oversight and continuous education to identify and mitigate bias in AI outputs.

Practical Steps: Henrike mentioned the idea of using prompts that ask for balanced responses based on different gender perspectives as a practical step to test and mitigate bias in AI-generated content.