Spencer Foundation Initiative on AI and Education Research Grants

The Spencer Foundation has launched a dedicated Initiative on AI and Education to fund new research at the intersection of artificial intelligence, education, and learning that supports equitable educational use, development, and understanding of AI technologies.

The initiative channels additional designated funding for AI research through the foundation's existing grant programs, including Vision Grants, Large Research Grants, Small Research Grants, Racial Equity Program grants, and Research-Practice Partnership grants.

Research is organized around four key areas: (1) AI and Learning, covering tool development, pedagogy, and culturally relevant AI applications in PK-12 and higher education; (2) AI Policy, examining local, state, federal, and international AI education policy implementations; (3) AI Ethics and Justice, addressing data sovereignty, privacy, bias, representation, and digital literacy; and (4) AI's Impact on Educational Research, exploring new research methodologies and responsible AI practices in education research itself.

The Spencer Foundation is one of the leading private foundations dedicated to education research, making this initiative a significant new source of philanthropic funding for AI education scholarship. Unlike federal programs that emphasize deployment and workforce outcomes, Spencer funds fundamental research on how AI transforms learning, teaching, and educational equity.

Applications are accepted on a rolling basis through the foundation's standard grant programs, with dedicated AI funding allocated within each program cycle.

Spencer Initiative on AI and Education As widespread technological transformation poses both new opportunities for advancement and great risks for deepening inequities, the Spencer Foundation is launching a new initiative on AI and Education to re-envision possibilities for education and for learning across the lifespan.

The initiative, which grew out of a Spencer Convening on AI and Education held in Spring 2024, will support novel research on key, forward-leaning topics on AI, equity, and education. Ultimately, the initiative aims to offer evidence-based guidance that centers the needs of young people so that the technology solutions, systems, and policy directions we are utilizing and building contribute to the learning and thriving of all students.

Why focus on AI and Education? Artificial Intelligence (AI) is fundamentally reshaping the educational landscape, influencing how educators teach, how students learn, and how educational institutions from early childhood to higher education adapt to new technologies.

As AI-driven tools and applications continue to evolve, it is essential to foster responsible innovation and collaboration within educational settings to harness AI's potential for enhancing teaching and learning experiences. Within educational research, conversations about AI are wide-ranging.

There are very real concerns and open questions regarding how AI will impact learners, teachers, and system leaders in our most underserved communities. These concerns range from worries about a widening digital divide if students are “left out” to the harms that AI can propagate, such as algorithmically driven bias and discrimination as well as the energy and environmental costs of computationally demanding AI systems.

There is also significant excitement and support, with research beginning to explore the promise of AI-powered learning tools, and possibilities for technology to support teacher professional learning or reduce the administrative burden of classroom tasks for educators.

Rigorous research is necessary to properly weigh these concerns while remaining open to the potential for AI to positively transform educational systems from early childhood to higher education. We believe the education research community has a tremendous opportunity and responsibility to take a balanced approach to AI and education, rooted in evidence and data.

Towards these ends, our AI initiative focuses on leveraging the potential of artificial intelligence technologies for equitable teaching and learning, while attending seriously to the potential harms, privacy and data security risks, and potential adverse impacts on education systems. What will the initiative do?

The initiative will fund research on AI, education, and learning that supports equitable educational use, development, and understanding of AI technologies.

We will also work to cultivate dialogue between researchers, the tech industry, policymakers, and education practitioners to enrich the collaboration and work happening across scholarly and other communities and to enrich public understanding around how AI technologies can support (or hinder) our equity aims. We will fund new research through two existing grant programs: Our Vision Grant Program and our Racial Equity Program.

While these programs remain open to all topics, we have designated additional funds within each program for work focused on AI. We also welcome AI focused work across our entire portfolio of research grant programs, including our Small Research Grants on Education Program, our Large Research Grants on Education Program, and our Research-Practice Partnership Program.

The initiative will focus on three core activities: Advancing Cutting-Edge Research on AI and Education in Four Key Areas How AI Will Transform Educational Research Cultivating Connections and Collaboration Between Researchers, Tech Industry, Policymakers, and Practitioners Fostering collaborations that bridge gaps between the AI sector and educational institutions Building deeper networks for knowledge sharing and innovation in AI Enriching Public Discourse on AI and Education Working with journalists and policymakers to strengthen scientific insights in the public discourse on AI and education Deepening the equity lens in discussions about the role of AI in education Balancing conversations to consider both the opportunities and risks associated with AI technologies Funding Priorities for Scholarship How can AI tools be more culturally relevant, and how can we leverage recent advances in learning sciences to build more sophisticated tools for classrooms that are in line with what we know from cognitive science and learning sciences to better serve all students?

In PK-12 this might include tool and program development, but also studying existing products, and the pedagogical issues around teaching and learning with AI tools. In higher education, this might include learning products but also supports for student services, course enrollment and management, and advising supports.

This may also take the form of historical or philosophical inquiry into the theories of learning of AI and how these theories could be adapted to align with culturally relevant pedagogy and other advances in the learning sciences. Finally, in what ways might AI technologies be leveraged outside of school to enable learning for children and adults?

What are we learning from current local, state, federal and international policy implementations? What is the role of the federal government around AI policy and regulation in coming years? What might be the best regulatory practices when new AI technologies emerge for public use?

In PK-12, this might include research on the procurement of AI platform technologies in schools. In higher education, this might include studies of college and university policies, and the implications of state and local policy on uptake and use of AI in higher education settings.

While there has been significant attention to ethics in AI more generally, especially related to questions of fairness, accountability, transparency, and equity, there has been far less attention to these concerns in education. There are critical questions of data and data sovereignty, privacy, bias, representation, and digital literacy.

There are questions about how AI is and should/could be specifically impacting underserved students, families, and communities. How might current patterns of inequity be disrupted or reinforced with/through AI? How AI will Transform Educational Research AI also raises important questions with respect to how we conduct research in education, and opens up new possibilities for data and research methods.

Studies might take up questions on the philosophy of science and technology of AI. How are questions of objectivity, validity, reliability, causality, and replicability addressed, if retained at all?

What are the various potential applications of AI for social science research such as for qualitative data analysis, measurement of traditionally non-quantitative phenomena, incomplete case analysis, matching methods, meta-reviews of research literature, and psychometrics and assessment? What might be the recommended practices or standards for accountability for responsible AI use in education research?

The Spencer Foundation invests in education research that cultivates learning and transforms lives. Learn about Opportunities to Join our Staff Find Out More About Our Legacy Lyle M. Spencer established the Spencer Foundation in 1962 to investigate ways education, broadly conceived, might be improved.

We support high-quality, innovative research on education, broadly conceived. Field-Initiated Research Grant Programs Fellowships for Scholars and Journalists Meeting the Moment Together Spencer Releases Report on Preparing Scholars to Conduct Transformative Research in Education Browse Our Resources and Tools Resources and Tools For Applicants