Problem
Research questions and friction points this paper is trying to address.
scientific computing
artificial intelligence
socio-technical co-design
ecosystem transformation
workforce models
Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science
🤖 AI Summary
该报告讨论了如何通过社区、软件和AI协作来解决科学计算生态系统面临的挑战，提出了八个优先行动方向以构建可持续、可信的跨学科团队科学环境。
📝 Abstract
Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.
Innovation
Methods, ideas, or system contributions that make the work stand out.
socio-technical co-design
AI-enabled scientific discovery
human-AI teaming
🔎 Similar Papers
No similar papers found.
