AI for science needs reasoning, not just more data
Researchers argue that current AI systems, which excel at pattern recognition from massive data, fall short for scientific discovery. A new perspective emphasizes the need for AI to perform causal reasoning and hypothesis generation, not just statistical correlation. This matters because scientific breakthroughs depend on understanding mechanisms, not only predicting outcomes.