The University of South Carolina College of Arts and Sciences is launching 11 new cutting-edge projects to explore how to use artificial intelligence in fields ranging from art and design to geography and neuroscience. 

The programs include new courses and research in data science, geography, literature, art, and philosophy focusing on the use of AI in the classroom and beyond, as well as research to study AI’s impacts on society. The projects are launching shortly before the first anniversary of OpenAI’s release of ChatGPT, which initiated a year of disruption by rapidly evolving technology. 

“Artificial intelligence is transforming the world around us, with implications for the ways we teach, create literature and art, conduct research, consume information, and interact with each other,” says Joel Samuels, dean of the College of Arts and Sciences. “Through these projects, our faculty will discover innovative methods for using AI and develop new insights about how to engage this technology effectively and ethically.” 

The projects are supported by the McCausland Innovation Fund, which sponsors faculty in trying new approaches to programs that impact the community or enhance the student experience. 

The artificial intelligence projects are: 

New Courses 

Minds, Brains, and Artificial Intelligence 
Rutvik Desai, Department of Psychology 

While large language models trained on natural language have shown remarkable ability to perform advanced tasks, researchers are divided on whether LLMs truly understand language. In newly developed graduate and senior level undergraduate courses critical for neuroscience, students will engage with questions surrounding AI and ‘true’ intelligence. 

Course Cluster in English and AI 
Michael Gavin, Department of English 

This project will improve upon and develop a series of English courses on AI in the context of literature, writing and more, as well as a technical course (cross-listed with linguistics) on textual computing. Students will learn how AI was developed, consider ethical concerns and gain skills to use AI in practical ways. Courses to be redesigned, include the introductory course, English 280: Literature and AI.

 

Developing and Introducing AI Examples
Megan McKay, Department of Mathematics 

This new course, Mathematical Concepts for Data Analysis, Math 328, will explore today’s leading data science problems, including the application of mathematics to AI. Students will engage with complex concepts through easy-to-understand AI examples, such as creating and training Deep Neural Networks on MATLAB software. The course will be part of the new interdisciplinary data analytics major in the College of Arts and Sciences and College of engineering and Computing. 

Revised Courses 

Teaching Biologists to Code in the Age of AI 
Tad Dallas, Department of Biological Sciences 

This proposal seeks to revise an upper level undergraduate and graduate level course in Ecoinformatics, Biol 599. Students will gain a working knowledge of AI and how to use it ethically, with special emphasis on training large language models and machine learning in biology. Development will include new open-source material allowing other professors to reuse the material freely for other courses in the College of Arts & Sciences. 

AI Ethics 
Leah McClimans, Department of Philosophy 

In a redesign of PHIL 323, Ethics in Science and Technology, this AI Ethics course will look at modern and future robots — from toasters to autonomous vehicles — to better understand how to solve social problems using technical solutions. Students will examine problematic computing algorithms and explore improvements, remaining aware of the technology’s potential bias and limitations. 

Process + Systems for Emerging Design: Co-creation with Artificial Intelligence 
Meena Khalili, School of Visual Art and Design 

As artificial intelligence evolves, the design industry must evolve to capitalize on its capabilities. Khalili will lead an enhancement of the existing course, ARTS 346, Process and Systems, to incorporate AI and machine learning into the curriculum. Students will learn about training models and machine learning to incorporate AI as a co-creator for design solutions.

Integration of AI Technologies in STEM: Creating a Bot-ter, More Equitable Experience in the Science Classroom 
Charles Andy Schumpert, Department of Biological Sciences 

Biology students will learn how to integrate generative artificial intelligence into their STEM studies. Students in a variety of BIOL courses (Biol 101, 302, 423, and 620) will learn how to use AI ethically and in a way that increases access and opportunity in those courses. For example, students will use emerging technology to create practice exam questions to use as study tools and to create visuals that will help demonstrate challenging topics. 

Engineering Ethics in the Age of Artificial Intelligence 
Michael Stoeltzner, Department of Philosophy 

With a renewed set of themes and case studies, this restructuring of PHIL 325, Engineering Ethics, will modernize a popular ethics course, allowing it to reflect ongoing changes in the engineering profession over the last decade. Students will research case studies that reflect the ethical challenges of AI in various engineering fields. 

Research Projects 

Artificial Intelligence and Misinformation in American Politics 
Kristin Lunz Trujillo, Department of Political Science 

AI can create false or misleading political information that appears credible. With a national survey administered in 2024, this project will investigate how AI influences American political attitudes and behavior, and how this knowledge can be used as an educational intervention to help people recognize AI-generated content. 

Engaging Students in AI-based Neuroimaging (MRI) Research 
Chris Rorden, Department of Psychology 

With the advent of AI, neuroscientists are developing new methods to identify complex patterns in brain imaging data. The project will integrate AI-based approaches into the Honors College course ABC’s of Neuroimaging (SCHC 402), and the Psychology course Image to Inference (PSYC 589 / 888). Students will train in these cutting-edge methods through research projects using data from USC’s 3T MRI and related studies.