Innovation

The Ethics Institute serves as the central hub for ethical guidance, collaboration, and community engagement around AI in research, education, and university practices at Michigan State University. From convening the university’s AI Summit to supporting the development of guidelines, research, and faculty working groups, the Institute has led efforts to ensure MSU’s approach to AI is thoughtful, inclusive, and aligned with our institutional values. By bringing together voices from across disciplines, the Ethics Institute fosters dialogue and shapes practices that prioritize equity, responsibility, and innovation in the age of automation.

The Evidence Driven Learning Innovation (EDLI) research center is a collaboration of educators and researchers in the Colleges of Arts and Letters, Business and Natural Science, MSU Libraries, and MSU IT. Our mission is to humanize the digital learning experience and use a values-driven approach to develop and evaluate digital pedagogies and technologies for 21st-century learning.

The integration of Artificial Intelligence (AI) in STEM education marks a revolutionary shift in pedagogical methods and learning outcomes. AI's role in customizing and enhancing educational experiences is paramount. The Center for Education and Emerging Technologies explores and pushes forward the use of AI in STEM Education.

The Michigan State University AI Research (MAIR), housed within the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), holds a distinguished position in the dynamic field of Artificial Intelligence (AI). With a rich history of innovation and a commitment to pushing the boundaries of technology, MAIR provides a hub of creativity and discovery in AI research. Led by a diverse team of renowned experts, MAIR endeavors include a wide range of research domains, spanning biometrics, computer vision, data mining, natural language processing, and machine learning.

Danielle Nicole DeVoss

Professor and Chair; Writing, Rhetoric, and Cultures; College of Arts & Letters (CAL)

Kate Fedewa O’Connor

Academic Specialist; Writing, Rhetoric, and Cultures; CAL

Generative artificial intelligence (AI) transforms how writers do their work. We anticipate that students pursuing a bachelor’s degree in professional and public writing, and those minoring in writing, will pursue opportunities in which AI is part of their routines. We’re committed to supporting students in developing thoughtful, ethical, critical, and creative ways to approach and use AI.

In spring 2024, we offered a one-credit, late-start special topics course focused on “Humans, Writing, and AI.” We explored questions about creativity, access, ethics, and more when machines can write for us (and we can write with them). We created, composed, rendered, revised, remixed, and experimented with different AI tools. Importantly, we approached both our critical analysis and our generative creating from a humanities perspective—with attention to the human and the humane.

At the end of the class, we hoped students would:

• be familiar with various contemporary AI tools and have a general understanding of how they work;
• have some comfort with using AI tools to compose content for professional and public contexts;
• be able to explain AI and articulate some of the ways in which AI can and will continue to influence writing processes, practices, and products;
• recognize the various cultural, ethical, disciplinary, and other issues related to AI;
• be able to analyze how bias is embedded in AI systems; and
• be able to ethically navigate and use AI tools.

On the first day, we engaged students in an activity where we collaboratively generated the class AI policy. Together, we reviewed the MSU guidance for AI use for students and instructors and discussed how we wanted to enact the guidance. Our class AI policy was that:

• Everyone in the class has the option and is encouraged to explore the tools they find most interesting and compelling; no specific AI program will be used exclusively (Grammarly, ChatGPT, Gemini, Snapshot AI extension, Adobe AI, Quillbot, MS photo AI generator, Siri, Alexa, CharacterAI).
• We value robust, thoughtful disclosure; AI use should be disclosed in content production (e.g., journal entries, online asynchronous activities).  
• As a class, we will find, share, and build different methods of citing AI (as co-author, as a tool, as reference; cite prompt, include a date stamp).  
• AI prompts should be part of how AI use is disclosed and situated.
• Context of AI use should be recognized and discussed (Who is the audience? What was the purpose? Where was AI used? Why was AI used? How is AI acknowledged or not?)

The class policy was a robust document, and we continued to revise it, as we read about, discussed, and worked with different generative AI tools. About halfway through the class, a call for chapter proposals for book collection on teaching and/with AI was shared across our disciplinary (rhetoric and writing studies) email lists.

We shared the call for chapters with students and invited them to co-author a chapter focused on why students should be included in AI policy and guideline discussions. The chapter—with authors including the two of us and Annika Hauser-Brydon, Margaux Smith, Jonathan Walker, Seth Byle, Nadia Theders, and Jacquelyne Thornton—is under contract and should appear in print soon. It highlights the importance of student involvement in shaping AI policy within the classroom and offers strategies to ensure students play active roles in broader institutional decision-making.

One of the claims we make to support this argument is that students will, indeed, be the decision-makers of the future. We must engage them with fundamental humanistic thinking and approaches; it’s also our job to equip them to shape humanistic thinking and approaches in their futures, whether via human thinking or computational thinking (and especially as the two intersect).

Profiles:

• Danielle Nicole DeVoss
• Kate Fedewa