Rethinking Fairness in AI
Moustapha emphasizes that bias and fairness in AI extend beyond model design and data sets; they begin with the problems we choose to address. He advocates for a broader focus on issues that resonate globally, suggesting that this shift will lead to more equitable data and models. By prioritizing diverse and significant problems, the AI community can better tackle inherent biases.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Security and Safety in AI: Adversarial Examples, Bias and Trust with Moustapha Cissé - #108
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