The Effects of Warmth and Competence Perceptions on Users' Choice of an AI System

Gilad, Zohar; Amir, Ofra; Levontin, Liat

doi:10.1145/3411764.3446863

Cited by 16 publications

(11 citation statements)

References 38 publications

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“…These findings, taken together, confirm that users do not yet fully perceive VAs as social agents but as functional assistive technologies designed to achieve instrumental goals (Kim et al, 2019). This may lead to users focussing on competence instead of warmth to evaluate VAs, in line with the conventional perspective highlighting the importance of competence in AI‐powered applications (Castelo et al, 2019; Gilad et al, 2021). Our findings suggest that developers must consider the functional competence of the VA's system as the foremost priority when designing VA services/systems.…”

Section: Discussionmentioning

confidence: 78%

“…Consumer researchers have utilized SCM to explain how consumers perceive and respond to humanized objects such as brands (Ivens et al, 2015) and chatbots (Seiler & Schär, 2021). AI‐related research has also demonstrated the usefulness of warmth and competence as the two dimensions that significantly predict user preferences for AI‐powered technologies (Gilad et al, 2021). Li and Wang (2022) indicated that perceived usefulness and ease of use (related characterisations of competence; Fernandes & Oliveira, 2021) are significant drivers of consumers' positive attitudes towards service robots.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For instance, performance and reliability are significant determinants of users' trust in computers (Hancock et al, 2011; Lee & See, 2004). Meanwhile, perceived warmth has been shown to have downstream effects on the trustworthiness of AI‐powered systems (Gilad et al, 2021; Khadpe et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Task type's effect on attitudes towards voice assistants

Sung

Duong

2023

Int J Consumer Studies

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There is an emerging interest in examining user attitudes towards voice assistants (VAs); however, there is limited research on how user attitudes are formulated in different contexts. Drawing from the stereotype content models, the current study attempts to investigate how users perceive and evaluate voice assistants (VAs) in different contexts (i.e., functional vs. social tasks) based on warmth, competence and trustworthiness. Study 1 (N = 123) employs a within‐subjects design to examine how task type (functional vs. social) affects user perceptions and attitudes towards a VA (i.e., Google Assistant). Study 2 (N = 116) and Study 3 (N = 61) examine the boundary effect of perceived psychological power and ease of use. The findings show that attitude is significantly more positive in functional tasks (vs. social), and this effect is mediated by perceived competence. This indirect effect is also significantly moderated by perceived ease of use. Perceived warmth does not mediate the effect of social tasks on attitude, and trust in VAs is a direct outcome of functional tasks. Taken together, this study contributes to both theory and practice in many ways. Specifically, the findings are the first to demonstrate a direct effect of task type on consumer perceptions and attitudes. Additionally, the findings indicate that user evaluations of VAs are still dominated by user perceptions of the competence of the VAs.

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Section: Discussionmentioning

confidence: 78%

Section: Literature Reviewmentioning

confidence: 99%

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Task type's effect on attitudes towards voice assistants

Sung

Duong

2023

Int J Consumer Studies

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“…Future research could also examine the downstream consequences of roundness versus precision in a product claim. For example, precision may lead to product competence perceptions, whereas roundedness may lead to product warmth perceptions, which, in turn, may influence product choices (Gilad et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

The effects of pseudo‐relevant 100% claims

Munichor,

Levontin

2023

Psychology and Marketing

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The term “100%” represents perfection. Thus, it is not surprising that marketers believe that claims that contain this term (e.g., “100% organic”) can make products more appealing. This intuition is reflected in the extensive use of 100% claims to describe products' qualities. We discuss how the term 100% can be used to create a claim about perfection that seems to, but does not, provide meaningful information about a product's benefits (e.g., “100% juice”). By appearing to be, but actually not being, relevant to the judgment at hand, these so‐called pseudo‐relevant 100% claims may mislead consumers into making baseless positive assumptions regarding the focal product. Three studies examine how consumers respond to pseudo‐relevant 100% claims. Our results suggest that pseudo‐relevant 100% claims lead to lower product evaluations and consumption intentions than similar claims that include adjacent percentages or no numerical terms. Interestingly, they also suggest spillover effects onto evaluations of the products' customers. Our findings show that consumers pick up on the meaninglessness of the promise of perfection implied by the term “100%” in pseudo‐relevant 100% claims, which causes them to perceive the product as less appealing.

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“…Numerous studies have highlighted their dominant role in accounting for the majority of variance in social perceptions, from approachavoidance tendencies [9,82] to understanding motives [87]. While initially framed for human cognitions, warmth and competence have also been used to understand people's perceptions of nonhuman entities, such as robots [18] and chatbots [43,93]. Another important dimension of public perception is valence, reecting how one emotionally rates an entity as good or bad.…”

Section: Related Work 21 Public Perceptions and Discourses Of Convers...mentioning

confidence: 99%

Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysis

Liu,

Li,

Chen

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Conversational Agents (CAs) have increasingly been integrated into everyday life, sparking signicant discussions on social media. While previous research has examined public perceptions of AI in general, there is a notable lack in research focused on CAs, with fewer investigations into cultural variations in CA perceptions. To address this gap, this study used computational methods to analyze about one million social media discussions surrounding CAs and compared people's discourses and perceptions of CAs in the US and China. We nd Chinese participants tended to view CAs hedonically, perceived voice-based and physically embodied CAs as warmer and more competent, and generally expressed positive emotions. In contrast, US participants saw CAs more functionally, with an ambivalent attitude. Warm perception was a key driver of positive emotions toward CAs in both countries. We discussed practical implications for designing contextually sensitive and usercentric CAs to resonate with various users' preferences and needs. CCS CONCEPTS• Human-centered computing ! Collaborative and social computing; • Social and professional topics ! Cultural characteristics.

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The Effects of Warmth and Competence Perceptions on Users' Choice of an AI System

Cited by 16 publications

References 38 publications

Task type's effect on attitudes towards voice assistants

Task type's effect on attitudes towards voice assistants

The effects of pseudo‐relevant 100% claims

Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysis

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