From the course: Navigating AI Through an Intersectional DEI Lens
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Unveiling the tangle: Intersecting bias in AI systems
From the course: Navigating AI Through an Intersectional DEI Lens
Unveiling the tangle: Intersecting bias in AI systems
- Imagine a world where a driverless car misidentifies pedestrians due to their clothing choices, leading to potentially fatal accidents. The scenario reflects the collision of multiple biases in AI systems. Just as a maze has many paths, biases can intersect, resulting in unintended and harmful consequences. Let's delve into the intricate web of bias intersection within AI systems, and understand how different forms of bias can combine and compound, affecting technology's fairness and reliability. Bias intersection is the phenomenon where multiple forms of bias present in AI systems converge, potentially leading to amplify discriminatory outcomes. This occurs when different types of bias within AI systems interact, magnifying their impact. Consider a speech recognition system consistently misunderstanding female-sounding voices and non-native English accents. This reveals the intersection of gender and racial bias disproportionately affecting women of color. To mitigate this…
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