This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.
ApartSprints
AI and Democracy Hackathon: Demonstrating the Risks
65b750920b4aeb478958fb32
AI and Democracy Hackathon: Demonstrating the Risks
May 6, 2024
Accepted at the 
65b750920b4aeb478958fb32
 research sprint on 

Silent Curriculum

Our project, "The Silent Curriculum," reveals how LLMs (Large Language Models) may inadvertently shape education and perpetuate cultural biases. Using GPT-3.5 and LLaMA2-70B, we generated children's stories and analyzed ethnic-occupational associations [self-annotated ethnicity extraction]. Results show strong similarities in biases across LLMs [cosine similarity: 0.87], suggesting an AI monoculture that could narrow young minds. This algorithmic homogenization [convergence of pre-training data, fine-tuning datasets, analogous guardrails] risks creating echo chambers, threatening diversity and democratic values. We urgently need diverse datasets and de-biasing techniques [mitigation strategies] to prevent LLMs from becoming unintended arbiters of truth, stifling the multiplicity of voices essential for a thriving democracy.

By 
Aman Priyanshu, Supriti Vijay
🏆 
4th place
3rd place
2nd place
1st place
 by peer review
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This project is private