Towards a new paradigm of scientific discovery with socialized artificial intelligence
Abstract
Scientific discovery has advanced through successive transformations in the organization of knowledge. Observation and experimentation established the empirical foundations of science. Theory made it possible to derive general principles from particular phenomena. Computation extended inquiry into systems beyond direct observation, while data-intensive methods opened new spaces of pattern and prediction. Science now confronts a different frontier. The central challenge is no longer simply to produce more information, but to organize expanding knowledge, reasoning, and evidence into a coherent process of discovery. Here, we introduce Bridging Literature, Agents, and Zero-gap Experimentation (BLAZE), a paradigm of socialized scientific intelligence. BLAZE conceives AI not as an assistant for isolated research tasks, but as an organizational infrastructure for scientific discovery. It connects persistent knowledge, collective reasoning, empirical validation, and human judgment within a continuous research lifecycle, transforming fragmented activities into a cumulative process of inquiry, criticism, and revision. The central premise of BLAZE is that scientific intelligence does not arise from computation alone. It emerges from the sustained interaction among knowledge, hypotheses, experiments, and collective verification. By organizing humans and machines within a shared scientific process, BLAZE makes discovery more traceable, reproducible, and cumulative while preserving human creativity, judgment, and responsibility. Socialized scientific intelligence may provide a foundation for the next era of science. Its purpose is not to replace human discovery, but to extend the scale, depth, and continuity of collective scientific inquiry.
Keywords
Cite
@article{arxiv.2608.02775,
title = {Towards a new paradigm of scientific discovery with socialized artificial intelligence},
author = {Xinjie Yao and Xingxin Xu and Xiyuan Gao and Zhoupeng Guo and Kunlong Yang and Dengyu Zhao and Siqi Zhao and Zhihe Fan and Yichen Dong and Xin Li and Jiekang Feng and Jiahe Wu and Sen Wang and Beiming Yu and Kejia Zhao and Ruipu Zhao and Jiaqi Zhou and Heyang Li and Jianjun Chen and Anbo Dai and Xin Liu and Zhengtao Yu and Qinghua Hu and Pengfei Zhu},
journal= {arXiv preprint arXiv:2608.02775},
year = {2026}
}