The use of Large Language Models (LLMs) to counter problematic smartphone use and support users’ digital wellbeing has recently gained research interest. Yet, such an approach is still in its infancy, particularly when compared to traditional digital self-control interventions. In this paper, we explore the possibility of using LLMs as “digital wellbeing assistants.” Specifically, we first reviewed the HCI literature and developed four user personas that exemplify widely recognized issues associated with smartphone (over)use. Then, we assessed the capabilities of four popular LLMs-powered chatbots, i.e., Bing, ChatGPT, Gemini, and Claude.AI, in understanding problematic smartphone uses and suggesting practical strategies to address them, using the developed personas as a testing ground. Despite some variations, results show that all three LLMs can offer tailored suggestions based on user characteristics, opening doors for smarter digital self-control interventions that leverage AI to support users’ self-monitoring and regulation capabilities.
Dialogues with digital wisdom: can LLMs help us put down the phone? / De Russis, Luigi; Monge Roffarello, Alberto; Scibetta, Luca. - ELETTRONICO. - (2024), pp. 56-61. (Intervento presentato al convegno GoodIT '24: International Conference on Information Technology for Social Good tenutosi a Bremen (DEU) nel 04 September 2024) [10.1145/3677525.3678640].
Dialogues with digital wisdom: can LLMs help us put down the phone?
De Russis, Luigi;Monge Roffarello, Alberto;Scibetta, Luca
2024
Abstract
The use of Large Language Models (LLMs) to counter problematic smartphone use and support users’ digital wellbeing has recently gained research interest. Yet, such an approach is still in its infancy, particularly when compared to traditional digital self-control interventions. In this paper, we explore the possibility of using LLMs as “digital wellbeing assistants.” Specifically, we first reviewed the HCI literature and developed four user personas that exemplify widely recognized issues associated with smartphone (over)use. Then, we assessed the capabilities of four popular LLMs-powered chatbots, i.e., Bing, ChatGPT, Gemini, and Claude.AI, in understanding problematic smartphone uses and suggesting practical strategies to address them, using the developed personas as a testing ground. Despite some variations, results show that all three LLMs can offer tailored suggestions based on user characteristics, opening doors for smarter digital self-control interventions that leverage AI to support users’ self-monitoring and regulation capabilities.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2992025