Christina Prignano Deering

@christinaprignano.com

Multimedia editor 📈 @bostonglobe.com. Rhode Island native ⚓

This project also marked the first time I had to apply STAT's AI use policy to publishing data analysis. I'm pleased with the standard for disclosure and transparency we're trying to set here. I also wanted to make sure I signed my name to this statement instead of using the institutional voice.

anil oza@aniloza.bsky.social · 4w ago

you can also find a link to the github with details of how we did our analysis, and take a look at the data yourself:

screenshot from story reading "A note on the use of AI
This analysis was conducted in partnership with STAT by Jae Yeon Kim, assistant professor of public policy; Betsy Pleasants, a postdoctoral fellow at the Carolina Population Center; and Maria Gallo, professor and chair of the Department of Epidemiology. All are at the University of North Carolina at Chapel Hill.

The researchers used a large language model (LLM) provided by OpenAI to classify comments by whether they support or oppose the proposed rule as well as to count the number of times comments mentioned specified topics.

Classification tasks like this would not be possible to conduct in a timely manner by hand and are well-suited to the capabilities of LLMs. This sort of use of LLMs is different from more “generative” uses (like chatting with an AI bot) that are more prone to “hallucinations.”

AI tools were also used to assist in the process of writing code for this project, but the entire data analysis pipeline uses repeatable code, mostly R and some Python. None of the summary statistics or charts used in this article were generated by AI.

All work was reviewed and verified by humans.

STAT also independently reviewed all code and methodology for this project.

Per STAT’s AI usage policy, all code and underlying data are available for review on Github.

— J. Emory Parker, Data Editor at STAT"

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