迈向可信自主科学：两年社区路线图
Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap
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中文总结 AI 辅助
该研究针对自主科学领域发展现状及问题，更新路线图围绕七个维度，评估原有里程碑并新增四个，规划两年发展路径，第一年聚焦接口等搭建验证框架，第二年针对联盟等，强调基层网络的互操作性。
中文摘要 AI 辅助
一年前，AISLE路线图指出自主实验室如孤岛运作，并围绕五个关键维度提出了基层网络。此后该领域发展迅速，但也遭遇逆流，如发现结果有误、基准测试显示智能体在开放式研究中表现不佳、顶级会议出现虚假引用等。现在产出候选发现不再难，验证才难，这种不对称限制了自主科学发展。此次更新路线图围绕七个维度，重新审视原五个维度，将信任、验证、可重复性以及安全、保障和治理提升到首要地位。评估了原有的里程碑，新增四个里程碑，并规划了两年的发展路径。第一年专注于接口、协议采用和验证框架搭建，第二年针对联盟、零信任协调和治理。始终将基层网络定位为让国家项目、国际倡议和商业平台连接而非重新孤立的互操作性架构。
英文摘要
One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The field has since moved faster than anticipated. Multi-agent systems have produced experimentally validated hypotheses, self-driving laboratories have grown more interoperable and orchestrated, reasoning-trained and domain foundation models have raised the capability ceiling, and the Genesis Mission has placed autonomous experimentation at the center of U.S. federal science strategy, with industry emerging as a primary actor. Progress has met a sobering counter-current, including a corrected flagship discovery result, benchmarks showing that agents which rival experts on closed-ended questions still complete only a fraction of open-ended research, and fabricated citations surfacing at leading venues. We read this as the defining tension of the field. Producing a candidate discovery is no longer the hard part, but verifying it is, and this asymmetry now limits autonomous science more than raw model capability. We update the roadmap around seven dimensions, revisiting the original five and elevating two former cross-cutting concerns, trust, verification, and reproducibility, and safety, security, and governance, to first-class status. We assess the original milestones (M1 through M14) as achieved, partially achieved, reframed, or open, add four new milestones (M15 through M18), and scope the path forward to a two-year horizon. The first year concentrates on interfaces, protocol adoption, and the scaffolding of verification, and the second targets federation, zero-trust coordination, and governance. Throughout, we position the grassroots network as the interoperability fabric that lets national programs, international initiatives, and commercial platforms connect rather than re-silo.
发表机构
- U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research（美国能源部科学办公室高级科学计算研究办公室）
机构由 AI 辅助整理，请以论文原文为准。
