Anthropomorphism in Artificial Intelligence: A Review of Empirical Work Across Domains and Insights for Future Research

Uysal, Ertugrul; Alavi, Sascha; Bezençon, Valéry

doi:10.1108/s1548-643520230000020015

Cited by 8 publications

(8 citation statements)

References 99 publications

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“…Moreover, such systems can apply sentiment analysis techniques to better understand the user's queries and emotional state [54]. In this context, the opportunities, but also the consequences and risks of anthropomorphizing such AI-based systems should be kept in mind [55], especially considering the technological developments and the rapidly increasing sophistication of thinking and feeling AI. In addition to chatbots or virtual assistants, there are many other applications for generative AI in e-commerce, such as writing product descriptions or marketing texts, search personalization and SEO optimization [56].…”

Section: B Ai/ml-based Approaches To Personalizationmentioning

confidence: 99%

One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce

Wasilewski,

Kolaczek

2024

IEEE Access

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One of the most visible manifestations of the changes brought about by the digitization of everyday life is undoubtedly the spread of electronic commerce. It is difficult to think of the digital economy without considering transactions through electronic channels. In turn, the user interface (UI) is the key to ecommerce, as it is usually the first and primary point of contact between business and consumer. A key trend in e-commerce is the personalization of communications, which can improve the user experience, increase customer satisfaction and deliver tangible business benefits. Today, it is technically possible to base this personalization on an analysis of user behavior using artificial intelligence and machine learning techniques. A common form of personalization in e-commerce is the use of product recommendation systems, but the user interface can be tailored much more extensively. The approach described and discussed in this paper is a multivariant user interface that allows the layout to be tailored to the characteristics, attributes, and behaviors of customer groups generated using machine learning techniques. The results of the research carried out make it possible to verify the practicality of the proposed solution and provide an opportunity to identify development directions that take into account the potential of artificial intelligence. The application of the concept described in the paper is broad, covering all aspects of e-commerce design that require compromises when serving a single UI variant, but allow flexibility and customization for different users when serving a multivariant UI.

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Section: B Ai/ml-based Approaches To Personalizationmentioning

confidence: 99%

One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce

Wasilewski,

Kolaczek

2024

IEEE Access

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“…With AI writing assistants, this tendency could lead to viewing the system as an impartial confidant to trust implicitly. Anthropomorphizing AI can significantly influence how teens receive AI-generated advice or views, especially on sensitive topics [21].…”

Section: Ai As Authoritative Companionmentioning

confidence: 99%

The Double-Edged Sword of AI Writing Tools

2024

Preprint

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As AI, specifically Generative AI (GenAI) writing tools, become prevalent in education, concerns arise about their influence on high school students' beliefs and worldviews during a vulnerable stage. This survey examines factors that heighten adolescents' susceptibility to uncritically adopting AI perspectives, including AI literacy deficits, AI's persuasive objectivity, peer dynamics, and psychological tendencies. It explores the disproportionate impact on underserved youth and the importance of workforce preparation.The survey proposes a multifaceted approach to safeguarding adolescent autonomy, emphasizing AI literacy education focused on critical thinking and responsible use. It highlights the need for international collaboration to establish universal guidelines adaptable to local contexts and workforce demands. It underscores participatory design's role in empowering adolescents and calls for policies promoting AI transparency, fairness, and accountability.The work concludes by emphasizing coordinated efforts among stakeholders to equip the next generation with tools and knowledge to critically engage with AI and shape their futures in an AI-driven world. Recommendations for future research and action are provided.

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“…In relationship to human behaviour, anthropomorphism is 'the tendency to imbue the behaviour of nonhuman agents with human-like characteristics' [40, p.864]. This is considered an innate human characteristic that manifests in childhood and may apply to physical appearance, emotional and mental states, and motivations of non-human objects [41]. In relationship to AI, anthropomorphism relates to perceiving a mind, personality, and motivations in the AI [41].…”

Section: Genai and The Challenge Of Anthropomorphismmentioning

confidence: 99%

GenAI and me: the hidden work of building and maintaining an augmentative partnership

Boulus-Rødje,

Cranefield,

Doyle

et al. 2024

Pers Ubiquit Comput

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It has been argued that emergent AI systems should be viewed as working partners rather than tools. Building on this perspective, this study investigates the process through which academics develop a working partnership with generative AI chatbots using a relationship lens and collaborative autoethnographic methods. Based on a collaborative autoethnographic analysis of our experiences of working with AI, we identify five stages of relationship development in building a successful working partnership with generative AI: Playing Around, Infatuation, Committing, Frustration, and Enlightenment and Readjustment. In reporting each stage, we provide vignettes to illustrate the emotional and cognitive challenges and rewards involved, the developing skills, and the experienced anthropomorphic dimension of this emerging relationship. Drawing on prior theory, we identify and examine three types of work that are required in developing this working partnership: articulation work, relationship work, and identity work. We analyse how each type of work unfolds with the stages of relationship development and consider implications for research and practice.

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Anthropomorphism in Artificial Intelligence: A Review of Empirical Work Across Domains and Insights for Future Research

Cited by 8 publications

References 99 publications

One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce

One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce

The Double-Edged Sword of AI Writing Tools

GenAI and me: the hidden work of building and maintaining an augmentative partnership

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