Buying the ‘Right’ Thing: Designing Food Recommender Systems with Critical Consumers

Lawo, Dennis; Neifer, Thomas; Stevens, Gunnar

doi:10.1145/3411764.3445264

Cited by 20 publications

(18 citation statements)

References 43 publications

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“…Samih et al [36] further explored this concept by developing a knowledge-based explainable recommender system that makes use of a probabilistic soft-logic framework to generate explanations. Lawo et al [28] aimed to enhance the interaction between users and virtual assistants by incorporating a cluster of consumers with ethical and social priorities into the recommendation process and considering their feedback and preferences.…”

Section: Towards Explainable Recommendation Systemsmentioning

confidence: 99%

“…To enhance transparency and, henceforth, effectiveness, Explainable AI (XAI) techniques have been employed in various domains, such as transportation, ŕeet management, and neurosciences [14,33]. Moreover, some studies have proposed semantic models [34] and incorporated negotiation techniques to guide users towards desired quality of life goals [28]. While these efforts have contributed to the őeld of recommender systems, to the best of our knowledge, there is currently no existing system that fully qualiőes as an explainable Nutrition Virtual Coach (NVC).…”

Section: Introductionmentioning

confidence: 99%

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Towards Interactive Explanation-based Nutrition Virtual Coaching Systems

Buzcu,

Tessa,

Tchappi

et al. 2023

Preprint

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The awareness about healthy lifestyles is increasing, opening to personalized intelligent health coaching applications. A demand for more than mere suggestions and mechanistic interactions has driven attention to nutrition virtual coaching systems (NVC) as a bridge between human-machine interaction and recommender, informative, persuasive, and argumentation systems. NVC can rely on data-driven opaque mechanisms. Therefore, it is crucial to enable NVC to explain their doing (i.e., engaging the user in discussions (via arguments) about dietary solutions/alternatives). By doing so, transparency, user acceptance, and engagement are expected to be boosted. This study focuses on NVC agents generating personalized food recommendations based on user-specific factors such as allergies, eating habits, lifestyles, and ingredient preferences. In particular, we propose a user-agent negotiation process entailing run-time feedback mechanisms to react to both recommendations and related explanations. Lastly, the study presents the findings obtained by the experiments conducted with multi-background participants to evaluate the acceptability and effectiveness of the proposed system. The results indicate that most participants value the opportunity to provide feedback and receive explanations for recommendations. Additionally, the users are fond of receiving information tailored to their needs. Furthermore, our interactive recommendation system performed better than the corresponding traditional recommendation system in terms of effectiveness regarding the number of agreements and rounds.

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Section: Towards Explainable Recommendation Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards Interactive Explanation-based Nutrition Virtual Coaching Systems

Buzcu,

Tessa,

Tchappi

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Much research focuses on the provision of information when sustainable grocery shopping, in-store and online. Solutions range from sustainable recommender systems [57] and userpreference based systems [26] to incen-tivisation strategies [19,37], and behavioural nudges [32,37,51]. However, there are two major issues with these approaches.…”

Section: Motivationmentioning

confidence: 99%

“…Customisable. The availability of diverse data gives people the freedom to make choices on environmental as well as social issues of the food system [26], supporting the personalisation of what are the 'right' values for consumers, rather than enforcing a normative understanding. Adaptive tools allow for long-term engagement with sustainability.…”

Section: Joy In the Self Alskdjfalskdjflskdjfalskdjfslkdjflskdjsmentioning

confidence: 99%

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Eco-Joy: Imagining Sustainable and Joyful Food Eco-label Futures

Shakeri

Jung

Bertran

et al. 2022

Adjunct Proceedings of the 2022 Nordic Human-Computer Interaction Conference

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A third of greenhouse gas emissions are attributable to the food sector. A shift in dietary habits could reduce these by half. Engaging and empowering consumers is vital to this critical shift; yet, if we get the framing wrong, we might cause distress or eco-anxiety, impeding initial engagement as well as longer-term diet change. Evoking joy is a powerful yet under-explored motivator to overcome psychological barriers and support pro-environmental attitudes. This pictorial presents the outcomes of a one-day workshop as a series of speculative ideas in the form of an annotated portfolio, highlighting design qualities and interaction mechanisms that afford joy and sustainability in food choices. Our contribution will inspire HCI researchers and designers to reposition joy as a fundamental value to sustainability communication.

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