Think artificial intelligence is strictly the realm of data science and statistics?
The Davis Institute for Artificial Intelligence is enabling Colby students and faculty to challenge common disciplinary associations with artificial intelligence (AI) by introducing AI and machine learning into a multitude of classrooms.
Italian studies, studio art, and government, to name but a few.
In its first semester of operation, the Davis Institute has already granted funding to multiple creative course proposals. By traversing disciplinary boundaries in unforeseen ways, faculty and students are already bringing a liberal arts mindset to the exploration of the social and ethical implications of AI.
Here are eight surprising places where students are encountering AI in their courses this year.
Studio Art and Computer Science
Amanda Lilleston, Visiting Professor of Print and Digital Media
Hannen Wolfe, Assistant Professor of Computer Science
Art has long been seen as an act of the human hand. However, a new module within the Digital Printmaking course challenges this by introducing technology into the creative process. Students will collaborate with motion-tracking software and simulated neural-network systems to teach computers to imitate their unique marks or sketches. Inspired by the artwork of Sougwen Chung, the module will culminate in the production and presentation of hybrid artforms combining each student’s hand with AI technology.
Gianluca Rizzo, the Paul D. and Marilyn Paganucci Associate Professor of Italian Language and Literature
In a new course titled A Practical Introduction to the Translation of Literary Texts, students analyze the benefits and limitations of both traditional and automated translation. Through analytical discussion and direct practice within one of four offered languages, students will compare translations done by humans against those by machine to determine whether AI can truly capture the complexity of a given text. Students will also explore creative uses of AI technology such as potential new genres of machine-assisted literature and the use of deliberate mistranslation as a compositional technique.
Science, Technology, and Society
Aaron Hanlon, Associate Professor of English and Director of the Science, Technology, and Society Program
In contemporary usage, the term “data” has seemingly become synonymous with fact. The new course History and Philosophy of Data seeks to unveil where this unwavering faith in data stems from. By tracing the etymology and historical usage of the word “data,” students will examine underlying assumptions and concepts attached to the term. Students will then apply this knowledge to explore how blind trust in data generates key issues in AI and data-related fields, focusing specifically on algorithmic bias.
Amber Hickey, Visiting Assistant Professor of Art and American Studies
Looking toward the future, many think of advanced technology and artificial intelligence. Others hope for a world that has progressed past our current social inequalities. A new module within the standing Contemporary Art course combines these two visions in the present, fostering discussion on how AI and contemporary art together inform and impact social justice. Through guest artists and a series of public events, students will collaborate in exploring Indigenous perspectives of hybrid artforms, animating oral histories, and utilizing art to resist racist and gender-discriminatory AI flaws.
Dan Shea, Professor of Government
Nick Jacobs, Assistant Professor of Government
Two new modules seek to modernize the Concepts and Methods of Political Science Research course by combining traditional techniques with AI tools. The first module centers on AI survey research and alternative methods to polling. Students will analyze how AI can mitigate common polling issues and learn to develop, write, and code open-ended responses into survey research. In the second module, students focus on the efficacy of using AI text-analysis tools to examine the fluctuating nature of political language and the emergence of new terms and ideas in politics.
Science, Technology, and Society
Kara Kugelmeyer, Data Services Librarian
As AI technology prepares to expose society to new lawless frontiers, the new Contemporary Information Ethics, Law, and Policy course prepares students to face difficult questions of what the limitations of AI technology should be. Through discussion, case-study analysis, and guest lectures, students will examine how data, information usage, and technology has had negative impacts on society, the environment, and individuals. Furthering this research, students will develop potential countermeasures to mitigate sources of harm that are currently intertwined with AI technology.
Alison Bates, Assistant Professor of Environmental Studies
The clean-energy transition, the focus of the Renewable Energy Systems course, seeks to reinvent our methods for powering society by mitigating fossil fuels and greenhouse gasses. In the course’s new module, students will investigate how AI is currently integrated into the clean-energy transition and examine how AI can analyze energy-equity metrics to promote justice through this transition. Students will showcase their efforts by drafting a policy memo to illustrate the data, ethics, and explanations for their proposed example of encouraging equity through the energy transition.
East Asian Studies and Computer Science
Ying Li, Assistant Professor of Computer Science
Hong Zhang, Associate Professor of East Asian Studies
Upon first glance at the Colby China studies website, one is inundated with striking images of comic art and magazine covers. To expand accessibility to Chinese primary sources, Zhang and Li are collaborating to create a public digital humanities platform that will function both as a source for their digitized Chinese magazine database and as an interface to examine digital humanities data. To enhance this platform, their project focuses on adding more primary source datasets and embedding AI tools, such as optical character recognition and text analysis, to the material in the database.
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