Accelerating Responsible AI for Education initiative

Accelerating Responsible AI for Education initiative is sponsored by Rice University. This initiative provides grants to faculty at Rice University to integrate responsible AI across various disciplines, including humanities, engineering, and sciences.

Rice University Awards 44 Grants to Lead the Way in Responsible AI | Digital Learning | Rice University Rice University Awards 44 Grants to Lead the Way in Responsible AI Rice University invests in 42 groundbreaking projects to integrate responsible AI across the humanities, engineering, and the sciences.

Rice University invests in 44 groundbreaking projects to integrate responsible AI across the humanities, engineering, and the sciences. "One of Rice's strategic goals is to be a leader in the development and implementation of the responsible use of artificial intelligence.

These grants empower faculty to experiment with AI in the classroom, create or rebuild courses to seamlessly integrate AI and learn from one another by building community within schools. With this support, they are better equipped to transform AI-related teaching and learning, accelerating Rice's leadership in AI education" said Amy Dittmar, the Howard R. Hughes Provost and executive vice president for academic affairs.

New Courses: Cross-Disciplinary AI Fluency Rice Digital Learning & Strategy is providing support to enable faculty to develop or redesign 16 courses to bring AI fluency to students in every corner of the campus. These classes ensure that whether a student is studying archaeology or chemical engineering, they have the tools to succeed in an AI-driven world.

Building large-scale AI software projects for the senior capstone of Rice’s new Bachelor’s of AI AI Tool Survey (DSCI 128) A project-based intro to tools like NotebookLM and Midjourney. Algorithmic Ethics (DSCI 305) "Red Teaming" models to find bias and ensure fairness. Ancient Cities (ANTH 363) Using AI to study history while critiquing AI-generated essays.

Using AI to reconstruct fossil anatomy and human origins. Design Build Ship (BUSI 365) Rapidly prototyping startup ideas using AI "sprints." Generative AI for Finance (MGMT 675) Using AI agents to execute Python code for data management, financial reporting, and analysis.

Human/AI Teaming (ELEC 631) Prototyping tools that augment human expertise in peer tutoring. Using Generative AI to troubleshoot complex engineering systems. Demystifying the math behind transformer and diffusion models.

Modern AI Models (DSCI 401) Exploring Deep Learning with a focus on accountability. Public Health Media (HEAL 212) Learning to identify and counter AI-driven misinformation. Using robots and Python to automate chemical experiments.

Social Epidemiology (HEAL 498) Using AI to humanize research through storytelling. Using math to build connections between formulas and computational behavior. Teaching non-CS majors to build programs via iterative prompting.

Exploration Grants: AI Experimentation These 16 projects provide seed funding for faculty to conduct small-scale experiments with AI in their teaching. AI-Driven Clinical Simulations Using AI-driven patient avatars to help medical Spanish students practice realistic healthcare communication. Integrating AI training assessments with immersive cycling to prescribe health plans.

Redesigning independent study projects as AI-assisted experiences for graduate students. Using LLMs to provide immediate feedback on research proposals, helping students refine experimental logic. Developing and fine-tuning an AI-based oral examiner for business course projects and presentations.

Developing specialized assistants for database courses that explain concepts without giving away answers. Developing an AI-powered "Forecasting Assistant" to help students synthesize complex economic data and improve the accuracy of market predictions. Using tools like Claude and Perplexity to identify risks in medical device designs.

Using Generative AI to accelerate data-driven decisions and build professional data science portfolios. Integrating AI assessment tools and OpenStax Assignable to provide immediate feedback in high-enrollment anatomy courses Interdisciplinary Research Exploring responsible AI for graduate-level writing while comparing AI-generated work to human-authored content.

Language Learning (Spanish) Using AI avatars for medical simulations and reflective writing practice. Transnational Asian Studies: Evaluating how chatbots help or hinder oral communication in second languages. Materials Science & Engineering Integrating generative AI tools into laboratory workflows to accelerate the discovery of new materials and optimize experimental design.

Using AI to produce initial mental health interventions for students to critically evaluate and revise. Returning to Socratic dialogic learning methods using AI tutors that guide students toward their own solutions. Professional Productivity Helping Engineering Management students identify when AI helps—and when it hurts—work quality.

Faculty Learning Communities (FLCs) To build long-term expertise, Rice Digital Learning & Strategy is empowering faculty to lead peer-based explorations of AI topics most relevant to their disciplines by funding seven learning communities where faculty collaborate on AI policy and teaching methods. George R. Brown School of Engineering Statistics: Connecting data analysis with real-world engineering hardware.

School of Social Sciences Economics: Developing an AI-powered "Forecasting Assistant" to help students synthesize complex economic data and improve market predictions. Engineering Communication George R. Brown School of Engineering Engineering: Integrating generative AI into engineering curricula to enhance technical writing, presentation skills, and professional storytelling.

Modern and Classical Languages: Curating a repository of AI-enhanced assignments that strengthen digital literacy. Multidisciplinary: Developing an archive of peer-reviewed use cases and benchmarks to test the capabilities and limits of AI in scholarly research. Transnational Asian Studies: Evaluating how chatbots help or hinder oral communication in second languages.

Natural Sciences Assessment Wiess School of Natural Sciences BioSciences: Creating a toolkit for teaching "with, without, and against AI" through redesigned assignments and rubrics. George R. Brown School of Engineering Rice Center for Engineering Leadership: Creating a toolkit for faculty to design “AI-resistant” assessments and clear usage policies.

School of Social Sciences Sociology: Using spatial AI and LLMs to study complex issues like health inequality. Bringing AI to the Public Rice’s commitment extends beyond the campus into the Houston community. The Glasscock School of Continuing Studies will offer a public course on Responsible Artificial Intelligence .

Led by seven Rice experts, the course features various guest speakers and covers multiple industries. Scholarships will ensure community members and local educators can access this global-standard expertise. Faculty leaders for this public course are Rob Bruce and Korin Brody.

Accelerating the Future – Rice Aims to Lead Globally in Responsible AI Rice is demystifying and democratizing AI across all disciplines. Through this diverse array of courses and learning communities, we examine AI’s technical foundations alongside its ethical implications and historical evolution.

This comprehensive approach ensures our students understand not just how AI works, but how its applications shape society and the human experience. The Accelerating Responsible AI and Education programs are partly funded from a generous philanthropic investment from Lori and Chuck Whitten to expand innovation and AI literacy to equip faculty with tools, knowledge, and support to harness AI in transformative and ethical ways.