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Artificial Intelligence: Systematic Prejudices. An Investigation into Bias Against Women and Girls in Large Language Models
The report examines how AI systems, specifically GPT-2, ChatGPT, and LLaMA 2, encode and reproduce gender bias. The study analyses gendered word associations, differences in sentiment, and cultural diversity in generated text, exposing systematic prejudices within algorithmic outputs. It underscores the need for transparency, inclusive datasets, and ethical frameworks to mitigate discrimination and ensure gender-responsive AI development and governance.
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D4D Access / European Commission