Course description: This course explores the implications of new generative AI tools on notions of human creativity and originality, and, at a more applied level, authorship and its multilingual corollary translation. Much of the debate around generative AI has to do with the extent to which AI applications have been or will be able to replicate human authorship or be mistaken for human expression. A major component of the course will be to situate this question in broad historical perspective.
Conceptions of human creativity and authorship as well as theories of translation as “rewriting” have always been shaped by the evolution of technologies for recording, storing, classifying, retrieving, and processing text, starting with writing itself. We'll explore the ways writing tools impacted and reflected evolving conceptions of creativity, originality and authorship; these include technologies for replicating texts at scale such as the printing press or the photocopier, technologies for storing and classifying information (such as indexical reference works organized alphabetically or in some other way, like rhyming dictionaries and bilingual dictionaries), and technologies of automation. Some date from the eighteenth century (see the image above!), but we'll also look at modern and today ubiquitous tools like spell-checkers and auto-complete for writers and term banks and “translation memories” for translators.
In this respect, at the core of the course will be a reflection on interactions between humans and machines as the historical basis for notions of human originality and creative expression, whether as authorship or translation. This offers a framework for considering ways in which AI both represents something new and grows out of certain continuities, thereby demystifying AI and allowing for a more dispassionate assessment of its limitations and possibilities.
Course objectives:
● to develop “critical AI literacy,” which includes understanding the potential harm from the amplification of bias and misinformation, copyright infringement, carbon footprint, replacement of human labor, and concentration of wealth that AI can generate
● as essential to that literacy, to instill a broader, historicized understanding of where AI fits into the larger trajectory of humans developing and using technologies to read, write, organize and process information
● to familiarize students with, demystify and make students better users of the current crop of AI tools
● to familiarize students with the scholarship on AI and the arts/humanities
● and to encourage reflection on the implications for understandings of human exceptionalism
Coursework: A mix of weekly exercises, with a midterm and final project. The final project can be either a short research paper of 1700-2000 words or a more hands-on, applied project with an accompanying reflection paper.
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This course is offered in the Textual Studies Program, and counts as an elective towards the Interdisciplinary Minor in Textual Studies and Digital Humanities. See the flyer below for more information about this program.
The course is approved as an elective in the Data Science minor, counting for the "Data Studies" requirement.
And it satisfies Arts and Humanities (A&H) Area of Knowledge and Social Sciences (SSc) graduation requirements.
No prerequisites.