Acceptability lies in the eye of the beholder:Self-other biases in GenAI collaborations

Since the release of ChatGPT, heated discussions have focused on the acceptable uses of generative artificial intelligence (GenAI) in education, science, and business practices. A salient question in these debates pertains to perceptions of the extent to which creators contribute to the co-produced output. As the current research establishes, the answer to this question depends on the evaluation target. Nine studies (seven preregistered, total N = 4498) document that people evaluate their own contributions to co-produced outputs with ChatGPT as higher than those of others. This systematic self–other difference stems from differential inferences regarding types of GenAI usage behavior: People think that they predominantly use GenAI for inspiration, but others use it to outsource work. These self–other differences in turn have direct ramifications for GenAI acceptability perceptions, such that usage is considered more acceptable for the self than for others. The authors discuss the implications of these findings for science, education, and marketing.</p

Making Recommendations More Effective Through Framings: Impacts of User- versus Item-Based Framings on Recommendation Click-Throughs

Companies frequently offer product recommendations to customers, according to various algorithms. This research explores how companies should frame the methods they use to derive their recommendations, in an attempt to maximize click-through rates. Two common framings—user-based and item-based—might describe the same recommendation. User-based framing emphasizes the similarity between customers (e.g., “People who like this also like…”); item-based framing instead em

Internal and external forces that prevent (vs. Facilitate) healthy eating:Review and outlook within consumer Psychology

This article synthesizes recent findings on antecedents of healthy eating. We discuss consumer-related and environment-related forces that influence consumers' healthy food choices and emphasize the duality of these forces so that they can facilitate but also prevent healthy eating. Specifically, our review documents how consumer lay beliefs, goals, and habits shape eating patterns. We further document the impact of environment-related forces on healthy consumption-focusing on intervention strategies and environmental changes (i.e., the trend towards online retail channels). Finally, we discuss three salient tensions (i.e., an innate craving for unhealthy food, a focus on single decisions, and a selective focus on self-control dilemmas) that emerge when taking a holistic view on existing research

Internal and external forces that prevent (vs. Facilitate) healthy eating: Review and outlook within consumer Psychology

This article synthesizes recent findings on antecedents of healthy eating. We discuss consumer-related and environment-related forces that influence consumers' healthy food choices and emphasize the duality of these forces so that they can facilitate but also prevent healthy eating. Specifically, our review documents how consumer lay beliefs, goals, and habits shape eating patterns. We further document the impact of environment-related forces on healthy consumption-focusing on intervention strategies and environmental changes (i.e., the trend towards online retail channels). Finally, we discuss three salient tensions (i.e., an innate craving for unhealthy food, a focus on single decisions, and a selective focus on self-control dilemmas) that emerge when taking a holistic view on existing research

Giving AI a Human Touch:Highlighting Human Input Increases the Perceived Helpfulness of Advice From AI Coaches

How can we increase the acceptance of artificial intelligence (AI) coaching advice? Across five studies (N=3,780), we document that people perceive AI advice as more helpful if human input is (made) salient. Utilizing a naturalistic field setting, study 1 shows that the more students believe that an AI coach contains human input, the more helpful the advice is perceived to be. We find that highlighting human input as an intervention strategy increases the perceived helpfulness of AI advice in the context of photography, compared to various control conditions (study 2 and follow-up study in the appendix). Study 3 shows that the effect is mediated by an increased subjective understanding of AI feedback when human input is highlighted. Study 4 provides evidence through moderation and shows that the positive impact of highlighting human input disappears under low levels of subjective understanding

Giving AI a Human Touch:Highlighting Human Input Increases the Perceived Helpfulness of Advice From AI Coaches

How can we increase the acceptance of artificial intelligence (AI) coaching advice? Across five studies (N=3,780), we document that people perceive AI advice as more helpful if human input is (made) salient. Utilizing a naturalistic field setting, study 1 shows that the more students believe that an AI coach contains human input, the more helpful the advice is perceived to be. We find that highlighting human input as an intervention strategy increases the perceived helpfulness of AI advice in the context of photography, compared to various control conditions (study 2 and follow-up study in the appendix). Study 3 shows that the effect is mediated by an increased subjective understanding of AI feedback when human input is highlighted. Study 4 provides evidence through moderation and shows that the positive impact of highlighting human input disappears under low levels of subjective understanding

The Secret Ingredient Is Me:Customization Prompts Self-Image-Consistent Product Perceptions

Companies frequently allow customers to customize products by assembling different product features or ingredients. Whereas existing research has demonstrated that customers assign greater overall value to customized products, this research focuses on the effect of customization on customers’ perceptions of specific product attributes (e.g., how healthy a product is). The findings of six studies—in the field, laboratory, and online—demonstrate that customizers and noncustomizers differ in their product perceptions even if the product is objectively the same. This is because customization leads customers to perceive the product in line with their own self-image (e.g., as an unhealthy eater), a phenomenon that the authors term “self-image-consistent product perceptions.” essentially, customization may influence product perceptions depending on the product and individuals’ self-image; this can have downstream consequences on recommendations and social media communication. The authors test this theory for different product categories (clothing, food, and vacation packages) and attributes (fashionable, healthy, and adventurous) and demonstrate that framing customization as a simple choice or strengthening product positioning through labeling mitigates negative effects of customization