Towards a new paradigm of scientific discovery with socialized artificial intelligence

迈向社会化人工智能驱动的科学发现新范式

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.

摘要： 科学发现的发展历经了知识组织方式的多次变革。观察与实验奠定了科学的经验基础；理论使从特定现象中推导出一般原则成为可能；计算将探究扩展到了超越直接观察的系统，而数据密集型方法则开辟了模式识别与预测的新空间。

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.

科学现在面临着一个不同的前沿领域。核心挑战不再仅仅是产生更多的信息，而是如何将不断扩展的知识、推理和证据组织成一个连贯的发现过程。在此，我们引入了“连接文献、智能体与零间隙实验”（Bridging Literature, Agents, and Zero-gap Experimentation, BLAZE），这是一种社会化科学智能范式。

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.

BLAZE 不将人工智能视为孤立研究任务的助手，而是将其视为科学发现的组织基础设施。它在持续的研究生命周期内连接了持久知识、集体推理、实证验证和人类判断，将碎片化的活动转化为一个探究、批判和修订的累积过程。

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.

BLAZE 的核心前提是：科学智能并非仅源于计算，而是产生于知识、假设、实验和集体验证之间的持续互动。通过将人类和机器组织在一个共享的科学流程中，BLAZE 在保留人类创造力、判断力和责任感的同时，使科学发现变得更具可追溯性、可重复性和累积性。

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.

社会化科学智能可能为科学的下一个时代提供基础。其目的不是取代人类的发现，而是扩展集体科学探究的规模、深度和连续性。