NSF2026: EAGER: Involving the Public in the Discovery of Undiscovered Public Knowledge

科学文献不断增长，这创造了通过将公开的科学信息联系在一起来拼凑未被发现的公共知识的机会。NSF的一个Idea Machine想法瞄准了一个想法，即利用人工智能(AI)实现科学成果全球化，人工智能(AI)可以用来筛选大量的科学文献，并有可能合成新的科学结果。这个项目试图考察非研究人员是否能够在大量科学文献中建立联系，并合成与当前研究问题相关的新结果和新想法。这种方法类似于使用人工智能来完成相同的任务，并且考虑到当前的人工智能技术不允许完成这类任务，这种方法是及时的。通过评估非研究人员帮助研究人员进行学术文献审查的能力，该项目将在另外两个NSF Idea Machine主题上取得进展，即“创建可持续教育路径”和“重塑科学人才”。该项目将分两个阶段进行。第一个阶段是探索阶段，将寻求了解非研究人员群体和研究人员群体在完成文献审查任务方面的能力差异，确定非研究人员在不同科学主题中寻找信息的能力，评估培训方法，并评估创建在特定科学领域表现出希望的个人队列的效果。该项目将探索建立一支训练有素的工人队伍的可行性，他们可以进行高质量的科学文献搜索，可能是跨学科的。新科学知识的产生预计将在科学学科的交叉点产生。在第二阶段，即部署阶段，将使用实地研究来确定第一阶段中的发现在用于现实世界用例文献搜索时的效果如何。该项目将为公众提供一种参与科学研究的新手段，特别是针对在STEM历史上代表性不足的高中生和本科生。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Scientific literature is ever growing, and this creates the opportunity to piece together undiscovered public knowledge by making connections across publicly available science information. An idea targeted by one of NSF’s Idea Machine ideas is the “Globalization of Science Results with AI”, where artificial intelligence (AI) can be used to sift through large volumes of science literature and potentially synthesize new scientific results. This project seeks to examine whether non-researchers can make connections across a large body of scientific literature and synthesize new results and ideas that are relevant to current research questions. This method is analogous to using AI to do the same task and is timely given that current AI technology does not allow for the completion of this type of task. By assessing the ability of non-researchers to aid researchers in performing academic literature reviews, this project will make advances in two additional NSF Idea Machine topics, “Creating Sustainable Education Pathways” and “Reinventing Scientific Talent”.The project is to be conducted in two phases. The first is an exploratory phase that will seek to understand the differences in ability between groups of non-researchers and researchers to complete literature review tasks, determine the ability of non-researchers to find information among different scientific topics, assess training methods, and assess the effects of creating cohorts of individuals that show promise in a specific area of science. The project will explore the viability of creating a paid workforce of trained workers that can conduct quality scientific literature searches, potentially across disciplines. The generation of new scientific knowledge is expected to be generated at the intersections of scientific disciplines. In the second phase, deployment, a field study will be used to determine how well the findings in the first phase work when employed in real-world use case literature searches. This project will provide a novel means for the public to engage with scientific research, specifically targeting high school and undergraduate students who are historically underrepresented in STEM.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.