arXiv:2602.20459v2 Announce Type: replace-cross Abstract: Can AI systems trained on the existing scientific record forecast the advances that will follow? We introduce PreScience, a dataset and benchmark for scientific forecasting built around 98K recent AI research papers, together with companion papers covering author publication histories and citation links, yielding 502K papers in total. The resulting paper records include titles, abstracts, disambiguated author identities, influential references, topic labels, citation trajectories, and metadata snapshotted to respect temporal cutoffs. We
The proliferation of AI research and the increased sophistication of AI models now allow for the development of tools to systematically analyze and predict scientific advancements. The dataset's temporal cutoffs highlight its real-time relevance.
This development allows for a more data-driven approach to understanding and potentially guiding scientific discovery, impacting resource allocation and strategic planning in research and development. It provides a benchmark for evaluating AI's capacity for scientific foresight.
The ability to systematically forecast scientific trends using AI means that funding bodies, research institutions, and national strategic planners can make more informed decisions about future investments. This shifts the paradigm from reactive observation to proactive prediction in science.
- · AI-driven research platforms
- · National science funding agencies
- · Large language model developers
- · Scientific research institutions
- · Traditional qualitative foresight consultancies
- · Research areas with low predictability
- · Academic fields resistant to data-driven analysis
AI systems will become increasingly adept at identifying emerging research areas and potential breakthroughs, guiding research efforts.
This predictive capability could lead to more efficient allocation of research funding, accelerating progress in fields with high forecasted impact.
The ability to forecast scientific advances might create a self-fulfilling prophecy, where predictable areas receive disproportionate investment, potentially stifling truly novel, unpredictable breakthroughs.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.CL