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Sustainable Me: A persuasive social AI for adopting sustainable lifestyles

   UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents

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  Mr Jared de Bruin  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

For instructions on how to apply, please see: PhD Studentships: UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents.


  • Martin Lages: School of Psychology
  • Simone Stumpf: School of Computing Science

Adopting a sustainable lifestyle in a modern society is challenging because it requires not only to change the status quo but also to digest a wealth of information that spans across many domains, for example diet, shopping, transport, waste management, heating, leisure activities, etc. Persuasive technology has been studied for its role in behaviour change [1] and decision-making [2] where the technology is seen as a persuasive social actor which can exploit physical, psychological, language, and social cues to persuade people to take a desired action [3]. This research is set against a background of human-human persuasion and decision-making which has a long history of research and study. Individual changes can have a dramatic impact on sustainability, for example, by reducing meat consumption, switching to more environmentally friendly transportation, or making changes to everyday practices, all of which can reduce a person’s carbon footprint. However, a ‘one-size-fits-all’ approach to behaviour change does not work well for people in different circumstances, with different preferences and motivations. This can be exploited by building an AI system that communicates with an individual as a social actor [4], and suggests the most suitable sustainable decisions as well as behaviours in a personalised conversation with the user. Previous research in the energy domain has shown the feasibility of this approach [5,6].

Main aims and objectives

In this PhD project we set out to develop an interactive AI system that is tailored to individual preferences and maximises individual behaviour change while customizing the interaction with the user. As part of this work, the PhD student will gather background on persuasive technology and human-human persuasion to build a conceptual framework for persuasive social interactions that can be applied to adopting a more sustainable lifestyle. The student will design and implement an AI agent that builds a user model of an individual’s circumstances and preferences, and then instantiates and customises the persuasive dialogue with the user to generate individualised interventions. A major aspect of this work will be evaluating the acceptability and usability of this AI agent and its effects on decision-making and behaviour change.

Proposed methods

This PhD will draw on a theoretical basis of behaviour change and persuasion to build a practical system which can be empirically evaluated. It will combine skills in AI development, the design of interactive systems/HCI and experimental studies.

Likely outputs and impacts

This PhD will contribute to a better understanding of how to influence decision-making and change behaviour. It will provide a conceptual framework for building and evaluating persuasive AI agents that make personalized suggestions and engage effectively in a dialogue with the user. It will demonstrate how to design and implement such a socially interactive and persuasive AI. Finally, it will provide guidelines for developing effective socially interactive and persuasive AI. We envisage that this AI system could be made available to individuals, households, local communities, and local government to reduce greenhouse emissions in order to keep global average temperature rise below 1.5C as pledged by the UN at COP26 in Glasgow.


[1] Thaler RH and Sunstein CR (2008) Nudge: improving decisions about health wealth and happiness. Yale University Press.
[2] Lages M, and Jaworska K (2012) How predictable are “spontaneous decisions” and “hidden intentions”. Comparing classification results based on previous responses with multivariate pattern analysis of fMRI BOLD signals. Frontiers in Psychology, 3, 56.
[3] Fogg BJ (2002) Persuasive technology: using computers to change what we think and do. Ubiquity 2002, December: 5:2.
[4] Crosswhite J, Fox J, Reed C, Scaltsas T, and Stumpf S (2004) Computational Models of Rhetorical Argument. In Argumentation Machines: New Frontiers in Argument and Computation, Chris Reed and Timothy J. Norman (eds.). Springer Netherlands, Dordrecht, 175–209.
[5] Mogles N, Padget J, Gabe-Thomas E, Walker I, and Lee JH (2018) A computational model for designing energy behaviour change interventions. User Modeling and User-Adapted Interaction 28, 1: 1–34.
[6] Skrebe S and Stumpf S (2017) An exploratory study to design constrained engagement in smart heating systems. In Proceedings of the 31st British Human Computer Interaction Conference.
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