159: Bias in AI with Lauren Maffeo

December 4th, 2019 · 58 mins 3 secs

About this Episode

02:26 - Lauren’s Superpower: Remembering Useful Yet Sentimental Facts About People

03:57 - Lauren’s Professional Background

07:35 - Bias in the Downsides of AI

11:15 - Media and AI/How the Media Affects People’s Perception of AI

14:32 - Concerns of Small and Midsize Businesses Pertaining to AI

18:37 - How to Mitigate Bias in AI

22:23 - Ethics in AI

25:39 - Defining Bias in AI

32:04 - Fairness vs. Accuracy in Algorithms

38:30 - Preventing Bias in AI Resources

41:00 - Working Remotely

  • Proactively Communicating
  • Setting Boundaries

50:45 - Diversity and Inclusion in the Workplace

Reflections:

John: Lauren talking about the work she’s doing to pre-educate people so they can prevent themselves from getting in trouble even before they build their models.

Chanté: It’s not enough to just be doing this internally. Bias happens in all shapes, sizes, and forms and it’s important to recognize that.

Jacob: In a biased society we can’t expect completely unbiased data; therefore we can’t train an algorithm on the theoretical equitable world that we want to create. There will always be a trace of the bias we have now.

Lauren: The first step is acknowledging the bias exists in the first place.

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