The Potential of Generative AI in Personalized Nutrition

Oewel, Bruna and Guluzade, Lala and Zhu, Jun and Huang, Yuanhui (2024) The Potential of Generative AI in Personalized Nutrition. In: CHI 2024 Workshop : Designing (with) AI for Wellbeing. ACM, USA, pp. 1-6.

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Abstract

Advancements in Generative AI (GenAI) promise to deliver support for well-being. We conducted semi-structured interviews with 9 participants to gain insights into their expectations and requirements for personalized diets using ChatGPT. The study aimed to understand how ChatGPT and other GenAI tools could be leveraged to support individuals in achieving their personalized dietary goals. Our finding reveals that ChatGPT often failed to meet the participants’ personalized expectations and misinterpreted requests, thereby raising ethical concerns. We argue such concerns within the context of the four principles informed by healthcare ethics: autonomy, non-maleficence, beneficence, and justice.

Item Type:

Contribution in Book/Report/Proceedings

Subjects:

?? nutritionhealthy eatingpersonalized dietartificial intelligenceaigenerative aigenaichatgpt ??

Departments:

Faculty of Science and Technology > School of Computing & Communications

ID Code:

217143

Deposited By:

ep_importer_pure

Deposited On:

31 May 2024 15:30

Refereed?:

Yes

Published?:

Published

Last Modified:

07 Nov 2024 01:41

URI:

https://eprints.lancs.ac.uk/id/eprint/217143