Ask the experts: sourcing a high-quality nutrition counseling dataset through Human-AI collaboration
Simone Balloccu, Ehud Reiter, Karen Jia-Hui Li, Rafael Sargsyan, Vivek Kumar, Diego Reforgiato, Daniele Riboni, Ondrej Dusek
Abstract
Large Language Models (LLMs) are being employed by end-users for various tasks, including sensitive ones such as health counseling, disregarding potential safety concerns. It is thus necessary to understand how adequately LLMs perform in such domains. We conduct a case study on ChatGPT in nutrition counseling, a popular use-case where the model supports a user with their dietary struggles. We crowd-source real-world diet-related struggles, then work with nutrition experts to generate supportive text using ChatGPT. Finally, experts evaluate the safety and text quality of ChatGPT’s output. The result is the HAI-coaching dataset, containing ~2.4K crowdsourced dietary struggles and ~97K corresponding ChatGPT-generated and expert-annotated supportive texts. We analyse ChatGPT’s performance, discovering potentially harmful behaviours, especially for sensitive topics like mental health. Finally, we use HAI-coaching to test open LLMs on various downstream tasks, showing that even the latest models struggle to achieve good performance. HAI-coaching is available at https://github.com/uccollab/hai-coaching/
BibTeX
@inproceedings{balloccu-etal-2024-ask,
title = "Ask the experts: sourcing a high-quality nutrition counseling dataset through Human-{AI} collaboration",
author = "Balloccu, Simone and
Reiter, Ehud and
Li, Karen Jia-Hui and
Sargsyan, Rafael and
Kumar, Vivek and
Reforgiato, Diego and
Riboni, Daniele and
Dusek, Ondrej",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.674/",
doi = "10.18653/v1/2024.findings-emnlp.674",
pages = "11519--11545"
}