Can Chat GPT and Crowdsourced Forecasting Help Students Think About International Relations? : A New Class Assignment

The arrival of ChatGPT has sparked existential questions about the future of the humanities and social sciences and has been accompanied in its wake by a hardline response: some instructors treat any use of ChatGPT as a punishable form of plagiarism. The following analysis is an attempt to determine if one can engage constructively with ChatGPT in a student assignment. It does so in the form of a new exercise where students are asked to interact with two significant developments in the field of information analysis simultaneously: ChatGPT, as an example of artificial intelligence, and collective intelligence, in the form of crowdsourced forecasting. Crowdsourced forecasting is founded on the belief that aggregating a large number of insights will yield predictions that are equally or more accurate than expert opinion. Major news outlets have run high-profile stories on crowdsourced forecasting in recent years (New York Times 2023; The Guardian 2022). When asked to assess their experience integrating information from these two sources, the students reported only lukewarm satisfaction with the performance of ChatGPT, while offering somewhat higher reviews for the role of crowdsourced forecasting. Among the most significant outcomes, the students thought more deeply about bias found in new information processes such as ChatGPT and crowdsourced forecasting and learned how to formulate better prompts.