2023-2024 Awards

The following projects have been selected for McCausland Innovation Fund awards.

Complexions Contemporary Ballet partnership 

Lead: Stephanie Milling, Department of Theatre and Dance

• Students in the Betsy Blackmon Dance Program at will collaborate with Complexions Contemporary Ballet. Two members of Complexions will spend several weeks in residence at the university to choreograph a new performance for the students using Complexions’ unique style and dance methods. The entire Complexions company will join the program’s annual dance gala in April. Complexions Contemporary Ballet has performed in 20 countries on five continents, earning praise for its fusion of dance methods and styles from different cultures.

Minds, Brains, and Artificial Intelligence 

Lead: 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 

Lead: 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

Lead: 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. 

Teaching Biologists to Code in the Age of AI 

Lead: 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 - Ethics in Science and Technology

Lead: 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 

Lead: 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 

Lead: 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 

Lead: 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. 

Artificial Intelligence and Misinformation in American Politics

Lead: 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 

Lead: 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.