DePaul raise Lab
Our Mission
Our research is grounded in authentic partnerships with communities underserved by technology. We don't just study communities—we learn from them, partner with them, and ensure they lead in defining what responsible AI means.
15+
Community Partners
5
Countries Engaged
100%
Community Benefit Focus
3
Policy Influences
Our Mission
RAISE Lab envisions a future where AI systems truly serve the common good—where technology empowers communities, preserves cultural heritage, and advances justice rather than perpetuating harm. We're building toward a world where community voices lead AI development, where cultural competence is standard practice, and where the benefits of artificial intelligence reach everyone.
Community Leadership
AI systems designed with and by the communities they serve, ensuring authentic representation and ownership.
Academic Revolution
A new model for university research that centers community partnership and measures success by social impact.
Global Equity
Technology that bridges rather than widens global divides, preserving linguistic and cultural diversity while advancing capability.
Policy Transformation
Countries engaged in collaborative aGovernance frameworks that prioritize community benefit and justice in AI development and deployment.
Tag Content
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Public Interest Technology
The Responsible AI Systems and Societal Experiences (RAISE) Lab at DePaul University serves as the primary research hub for Dr. Jay L. Cunningham’s scholarship at the intersection of Human–Computer Interaction (HCI), AI ethics, and public-interest technology. The lab advances interdisciplinary, community-engaged research that critically examines how AI systems are designed, governed, and experienced in real-world social contexts.
RAISE Lab research is organized around seven interrelated pillars:
Community Centered Research
Developing community-informed frameworks for measuring AI harm that center affected communities' experiences and expertise, with particular focus on natural language technologies and culturally competent evaluation processes.
Justice-Oriented Innovation
Creating ethical frameworks for data practices in AI ventures that ensure fairness and cultural competence, with community ownership and benefit from data used in AI systems, especially for disproportionately affected users.
Global Perspective, Local Impact
Addressing AI inequities affecting Global South communities through hyperlocal language technologies and international research partnerships.
Research to Practice Pipleine
Investigating design methodologies, interaction paradigms, and implementation strategies for intelligent systems that are meaningfully integrated into human experiences and environmental contexts, prioritizing user agency and contextual appropriateness.
