In my talk, we will delve into the world of artificial intelligence (AI) decision-making, examining its profound influence on our lives, and the risks it poses when imbued with unchecked biases. As AI systems are increasingly entrusted with critical decisions, from creditworthiness assessments to employment screenings, it's paramount that these systems are fair, transparent, and accountable. Yet, bias and discrimination have emerged as significant challenges, chiefly because AI systems tend to reflect and amplify the biases in their training data. These biases can inadvertently lead to unfair outcomes, exacerbating existing inequalities. Furthermore, I will discuss potential solutions, regulatory measures, and practices that can be instituted to mitigate these biases. The goal of this presentation is not only to expose the dark side of AI decision-making but also to inspire and guide the development of more equitable and accountable AI systems.
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