24 - Foucault, Power, and Bias in AI Systems

Описание: The provided text, drawing on concepts from Foucault, explores how artificial intelligence is not a neutral technology but is deeply embedded within existing power structures, leading to significant concerns regarding bias, transparency, and accountability. It highlights that AI systems often perpetuate societal biases due to issues in data and algorithm design, with examples ranging from facial recognition to hiring practices. The article also discusses the challenge of "black-box" AI models, which make it difficult to understand their decision-making processes, thereby reducing avenues for accountability. While acknowledging the importance of technical solutions for bias, the text emphasizes that true change requires integrating affected communities into AI development and moving beyond ineffective ethical principles towards sustained institutional oversight. Ultimately, the sources collectively argue that understanding the power dynamics within AI is crucial for addressing its societal implications.




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