AI for Safety and Safety of AI
Discover research that intersects AI system deployment and safety
This track gathers research that intersects AI system deployment and safety, focusing on frameworks and methods to ensure responsible and trustworthy machine learning in sensitive domains. Topics include techniques to build secure AI systems, human-machine alignment techniques, such as user-controlled text generation, and policy-related frameworks and ideas promoting transparency and fairness. Discussions will also include applications of responsible AI in law, education, and environmental monitoring.
Education and Workforce of the Future
Consider how responsible, inclusive, and ethical AI can transform education and the evolving demands of the 21st-century workforce
This track explores how responsible, inclusive, and ethical AI can transform education and training to meet the evolving demands of the 21st-century workforce. Topics include innovative approaches to AI-enhanced learning, skills development, and human-AI collaboration across educational, workplace, and community settings. Discussions will also feature interdisciplinary work that bridges research, policy, and practice to ensure equitable access to future-ready education and training.
Foundation Models: AI for Science Advances
Learn about the transformative potential of large-scale AI models in accelerating scientific discovery
This track explores the transformative potential of large-scale AI models in accelerating scientific discovery. It will showcase innovative research at the intersection of foundation models and scientific domains, including (but not limited to) physics, chemistry, biology, materials science, climate modeling, psychology, and healthcare. The track will feature research that advances methods for pre-training, adapting, fine-tuning, or aligning foundation models; novel applications that demonstrate meaningful scientific insights; evaluations of interpretability, robustness, and reliability; and discussions on responsible deployment and interdisciplinary collaboration.
Health AI and the Impact on Rural Healthcare
Uncover health challenges of data acquisition and application to dispersed communities
Over the past two years, the Lucy Family Institute has invited a variety of business, government, academic, and non-profit partners to campus as part of the Health Equity Data Forum. Each year, this has led to impactful research and data analysis questions. This year, the Health AI track will be part of the larger RISE AI conference, allowing attendees to meet and collaborate with researchers, industry partners, and other stakeholders.
This year’s focal topic will be Rural Healthcare; exploring the issues of first and last mile challenges of data acquisition and application to dispersed communities. Rural healthcare topics include the mental health, transportation, availability/location of specialists, food accessibility, and availability/accessibility of people for clinical trials. Addressing these factors can significantly change outcomes for this population. This track will explore the possibilities of AI and data models to address these communities.
Human-Centered Responsible AI
Delve into the design, development, study, and evaluation of human-centered AI
This track centers on the design, development, study, and evaluation of AI systems that prioritize human values, agency, and well-being. It will feature submissions that explore how AI can be shaped by or for the people it affects, whether through participatory design, explainability, alignment, value-sensitive engineering, or other approaches. Topics include human-AI collaboration, methods for surfacing user intent, preferences, and values, socio-technical system design, and approaches that foreground fairness, accountability, explainability, and transparency of AI systems. Discussions will also feature interdisciplinary work that integrates perspectives from HCI, AI, and other relevant disciplines to advance responsible AI that complements and empowers human capabilities.
Reimagining Global Governance and Policymaking
Explore how artificial intelligence is transforming governance and policymaking
This track examines how artificial intelligence is transforming governance and policymaking across local, national, and global contexts. It brings together research on AI’s role in designing, implementing, and analyzing policy, with attention to both real-world applications and conceptual innovations. Topics include the use of AI in policymaking processes, the political and social biases embedded in systems like large language models, and the potential of AI to advance global governance and public policy. Collectively, these papers offer a multidimensional perspective on the opportunities and risks of AI in building more responsive, transparent, and inclusive institutions.
