Eco-Intelligence Summit: AI in a Climate Focused Future

Talitha Washington, Ph.D., is a distinguished mathematician, serves as the Executive Director of the Center for Applied Data Science & Analytics (CADSA) at Howard University. A transformational leader, Dr. Washington guides CADSA’s direction in harnessing the power of data to address society’s most pressing challenges through groundbreaking research, expanded educational opportunities, and innovative advancements on a global scale. She holds the Sean McCleese Endowed Chair, is a Professor of Mathematics, and is the co-Chair of the President’s AI Advisory Council, which guides the university’s AI strategy across research, academic, and enterprise initiatives.

Dr. Washington serves as the Past-President of the Association for Women in Mathematics and a former member of the Census Scientific Advisory Committee of the U.S. Census Bureau. Her research interests include applied mathematics, dynamical systems, nonstandard finite difference schemes, data science, artificial intelligence, and education.

Randy Bumpers is an instructional designer and AI researcher focused on the responsible adoption of emerging technologies and their implications for equity and sustainability. He serves as Director of Student Success and Learning Experience Design at the American Association of State Colleges and Universities (AASCU), where he supports regional public universities in designing data-informed strategies that strengthen student outcomes. Randy is also a doctoral student in Higher Education Leadership and Policy Studies at Howard University, where his research examines how faculty at Historically Black Colleges and Universities make sense of—and integrate—AI in teaching and institutional practice. His work bridges AI governance, digital equity, and student success innovation to help higher education harness technology in ways that are transparent, ethical, and beneficial to society.

Nathaniel is an AI & Environment Research Consultant focusing on understanding the environmental impacts of generative AI and data centers. With 5+ years of experience in climate policy and tech governance, he has curated over 2,000 resources for the AI  & Environment Resource Hub open-access database. He has delivered insights across webinars, podcasts, and publications exploring both the environmental footprint of AI data center infrastructure and applications of AI in environmental science

Jeremy Blackstone is an Assistant Professor at Howard University in the Electrical Engineering and Computer Science Department. He received his PhD in Computer Science and Engineering from University of California, San Diego and received his Bachelor’s and Master’s degree in Systems and Computer Science at Howard University. He performs research in behavioral security, hardware security, and network security working on projects developing countermeasures for ransomware, side channel attacks and denial of service attacks.

1. How do you think AI reshaping climate activism, conservation science, and environmental decision-making—and what ethical frameworks are needed to ensure AI-driven solutions support equity, transparency, and long-term sustainability?
2. AI tools have a variety of beneficial applications and its use is becoming increasingly ubiquitous, however, as we heard the energy, water, and land use costs of data centers necessary to power AI cause detrimental environmental impacts. Do you think there is an ethical, and realistic, way of leveraging the benefits of AI taking these negative impacts into consideration?
3. What role do you think the government should play in creating policies that govern AI infrastructure and use at the Federal / State / Local level? Depending on the role, what policies do you think should be in place or aspects of its use (infrastructure / AI) should legislators take into consideration when creating or enacting those policies?

1. Can higher education institutions integrate AI into climate and environmental research and workforce training in ways that are ethical, inclusive, and aligned with real-world sustainability and labor market needs?
2. What is higher education’s responsibility in the climate and sustainability landscape related to AI?
3. Environmental justice asks: “Who benefits and who bears the burden?” How should higher education institutions apply that lens to sustainability decisions and decisions around AI? How do we ensure consent and shared value?

1. 1. What is one significant insights or lesson you are taking away from today’s discussions on the intersection of AI, climate change, and environmental sustainability?
   2. What is one actionable step you think can you or your organization take to address the environmental and climate impacts of AI technologies? How will you implement this step in your work or community?
   3. How do you think the stakeholders represented here can better collaborate to address the challenges and opportunities of AI in the context of climate and environmental sustainability?
   4. What is one strategy or approach that was  discussed today can help ensure that AI is developed and implemented in an ethical, equitable, and environmentally sustainable way?
   5. Looking ahead, what is one critical area for research, policy development, or community engagement to ensure AI supports a sustainable and just future?