Summer 2024 Quantitative Methods: Social Sciences GR5075 section 002

Artificial Intelligence (AI) & Social Sc

AI and Social Science

Call Number 12840
Day & Time
Location
TR 9:00am-12:10pm
222 Pupin Laboratories
Points 3
Grading Mode Standard
Approvals Required None
Instructor Gregory M Eirich
Type LECTURE
Method of Instruction In-Person
Course Description

Artificial intelligence (AI) and generative AI – like ChatGPT, MidJourney, and Gemini – are poised to change the world for everyone. It is critical that students understand (and utilize) this new technology at several levels. In this class – through readings and a dozen hands-on activities – students will come to deeply understand AI. Specifically, students will construct (using Python) some of the basic building-blocks of AI, like machine learning (like recommendation systems), natural language processing (like word embeddings) and chatbots. They will test out AI’s capabilities and refine prompts in real-world settings, whether in art, video, writing or Internet-of-Things. They will learn about how generative AI fits into the history of technology adoption and the diffusion of innovation, answering questions like: Will AI be able to replace whole jobs? And if so, when? They will use the lenses of psychology and economics to explore the impact of AI in people’s lives, including in the context of algorithmic fairness, regulation and intellectual property. They will be pushed to take human creativity in new directions, augmented by AI’s “weirdness.” Lastly, students will be pushed to further develop their own uniquely-human skills – like in critical thinking and empathy – in response to the power of generative AI to mimic humans. As best-selling author Seth Stephen-Davidowitz has recently (Dec. 2023) written, “So far, my newest book has higher ratings than either of my previous two books -- even though it was written in 1/36th of the time, thanks to AI. AI is wild!" By the end of this class, students will feel empowered technically and philosophically to handle all new generative AI developments. There are no specific prerequisites for this class.

Web Site Vergil
Subterm 05/20-06/28 (A)
Department Summer Session (SUMM)
Enrollment 20 students (25 max) as of 1:07PM Sunday, July 14, 2024
Subject Quantitative Methods: Social Sciences
Number GR5075
Section 002
Division Summer Session
Section key 20242QMSS5075G002