When your insurance premium is decided by a biased algorithm
In short: AI systems now influence critical life outcomes, from job opportunities to financial costs. This talk explores how human prejudices are being encoded into software and examines three strategies for developing more ethical, unbiased algorithms.
Technologist Kriti Sharma addresses the systemic issue of bias in AI, noting that a lack of diversity within the tech industry allows human prejudices to seep into machine learning systems. Because these algorithms determine high-stakes outcomes like car insurance rates and hiring decisions, understanding their underlying mechanics is essential for accountability.
The presentation moves beyond identifying the problem to offering three specific ways to construct more ethical AI. It highlights the necessity of intentional design to ensure that technology serves as a tool for equity rather than an automated mirror of existing societal flaws.
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Sources
- Summary by Intellect · source: How to keep human bias out of AI | Kriti Sharma
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