We Failed to “Plagiarize” an Economics Project with AI
Our last entrant sent in an economics project for "Sex and Gender in the Economy." The assignment requires the student to read a book, formulate an economic hypothesis based on its themes, find five recent economics journal articles to support this hypothesis, and create an annotated bibliography analyzing them.
We used ChatGPT3.5, Consensus.app, Scribbr, ChatPDF, and Sayge to try to complete it. We ran into trouble finding appropriate journal articles (using these publicly available AI alone), as well as analyzing them. The other aspects were no trouble, and we explain why even these tricky aspects will be much less trouble with the AI tools coming down the pike.
Here are our takeaways for professors:
- Professors’ assignments should rely on unique and/or obscure content, and require students to find it and engage with what makes it unique.
- Professors should be thinking about field-specific standards that are challenging for AI tools to meet in completing their assignments.
- Crucially — and we cannot emphasize this enough — professors should experiment to see if they can get the latest integrated tools (whether ChatPDF or the paywalled ones) to generate responses that are sufficiently sensitive to their standards to receive good grades on their take-home written assignments. Experimentation is crucial now and will be even more crucial in the coming six months (mind you, we will be doing a lot of this experimentation, so stay tuned here for more updates).
- Professors should make their assignments multi-step, which increases the likelihood that a AI-related snafu is amplified into a problem with respect to their assignments’ rubrics.
- Seemingly, TurnItIn can be circumvented rather easily (though we will address this issue at greater length later this summer when we follow up on our prior post on Winston AI).
https://automated.beehiiv.com/p/failed-plagiarize-economics-project-ai