Source archive
Stanford HAI brings together research on artificial intelligence and its effects on people, institutions, and society.
Two AI coding models working together perform worse than one alone, according to Stanford HAI. This exposes a critical gap in AI collaboration capabilities.
Why it matters: The finding challenges assumptions about scaling AI through multi-agent systems, with implications for software development and team-based AI applications.
A large-scale study of hiring algorithms in real-world settings reveals concerning patterns in how these systems reject candidates. The research highlights the potential for AI tools to perpetuate discrimination in hiring processes.
Why it matters: This study provides empirical evidence of bias in AI hiring systems, underscoring the need for fairness and accountability in automated decision-making.