Automating Science (scholar.social)

Recent discussions have highlighted the challenges of integrating large language models (LLMs) into scientific collaboration due to their high capital costs and the resulting need for verification of outputs. The reliance on trust networks complicates partnerships, as researchers using LLMs may necessitate additional effort from their peers to validate findings. The dialogue emphasizes the importance of ensuring reliability in scientific work that incorporates these advanced AI tools. The article argues for a transformation in the perception of science, advocating for "community science" — a model where scientific endeavors are closely tied to everyday life. This approach aims to empower laypeople to engage with and generate solutions for their own challenges, thereby reinforcing the role of experts as community facilitators. By fostering this social contract, science can become more accessible and responsive to the needs of society, ultimately promoting collaboration that respects both traditional methodologies and innovative AI advancements.