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LLMs generate sustainability nudges for recommender systems

Researchers have developed a method to generate sustainability-focused explanations for recommender systems using large language models (LLMs). These explanations, grounded in nudge theory, were tested in studies involving choices for instant coffee and hotel bookings. The findings indicate that simply disclosing sustainability information does not alter user choices, but framing this information or referencing social norms significantly increases sustainable selections and simplifies decision-making. The study highlights the potential of LLMs to create scalable, theory-driven explanations for promoting social good. AI

IMPACT Enables scalable, theory-grounded explanations for recommender systems to promote sustainable choices.

RANK_REASON Academic paper detailing a new method for generating recommendation explanations using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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LLMs generate sustainability nudges for recommender systems

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Academic paper detailing a new method for generating recommendation explanations using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Haya Halimeh, Dietmar Jannach, Oliver M\"uller ·

    Nudging Sustainable Choices through LLM-Generated Recommendation Explanations

    arXiv:2607.25726v1 Announce Type: new Abstract: Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustainable choices. Prior research shows that explanations influence users' perceptions of recommendations and can support more informed…