AI for Scientific Discovery is a Social Problem

arXiv 2025 29.8 theory

TLDR

Paper argues that social and institutional factors, not technical ones, are primary constraints for AI in scientific discovery.

Reasoning

Strengths: Identifies overlooked social challenges like community coordination and infrastructure inequities. Weaknesses: Lacks empirical evidence or real-world experiments; purely argumentative without supporting data.

Read-first score

Read-first score 29.8, weighted from topical fit, citation, graph, method, reproducibility, and recency signals. Original total remains 22.

Recency 8%

86.7

Uses a gentle age decay so recent papers surface without erasing older foundations. 2025

Methodology quality 25%

Screens visible abstract and analysis fields for experiment, dataset, baseline, metric, and limitation evidence. markers=benchmark

Reproducibility 25%

Screens links and visible text for paper, code, dataset, artifact, and repository signals. pdf=True; code=False; dataset=False; markers=none

Topical relevance 42%

18.3

Uses existing LLM keyword relevance scores normalized to 0-100. AI scientist,automated scientific discovery,autonomous research agent,automated research,literature review agent,survey generation,automated experimentation,experiment design agent,AI for scientific research,paper writing agent,research automation,scientific discovery agent

Field roles

Frontier

Rank sensitivity

Stability: volatile; rank range: 86.

Keyword Scores

AI for scientific research

automated scientific discovery

AI scientist

automated research

research automation

scientific discovery agent

autonomous research agent

literature review agent

survey generation

automated experimentation

experiment design agent

paper writing agent

Resources

Paper