"Detect homogeneity as a hidden risk signal Hashimoto's award-winning 'Artificial Hive Mind' paper at NeurIPS found that even when you ask different leading AI models the same open-ended question, they produce outputs that are 'strikingly similar — almost verbatim identical,' and a single model becomes less diverse after post-training fine-tuning. He warns that 'the internet used to be the artifact of human intelligence' capturing vastly different ways people write and think, but is now becoming 'the artifact of LLMs mixed with some amount of human intelligence.' For any professional who relies on AI-generated content, research summaries, or recommendations, this is a call to actively seek out diverse human sources and treat suspiciously uniform outputs as a quality warning sign. Source: Tatsunori Hashimoto, The Cognitive Revolution (or similar Stanford AI podcast), Small Language Models and AI Democratization"