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Human Versus Machine: Contingency Factors of Anthropomorphism as a Trust-Inducing Design Strategy for Conversational Agents

In: Information Systems and Neuroscience

Author

Listed:
  • Anna-Maria Seeger

    (University of Mannheim)

  • Armin Heinzl

    (University of Mannheim)

Abstract

Conversational agents are increasingly popular in various domains of application. Due to their ability to interact with users in human language, anthropomorphizing these agents to positively influence users’ trust perceptions seems justified. Indeed, conceptual and empirical arguments support the trust-inducing effect of anthropomorphic design. However, an opposing research stream that has widely been overlooked provides evidence that human-likeness reduces agents’ trustworthiness. Based on a thorough analysis of psychological mechanisms related to the contradicting theoretical positions, we propose that the agent substitution type acts as a situational moderator variable on the positive relationship between anthropomorphic design and agents’ trustworthiness. We argue that different agent types are related to distinct user expectations that influence the cognitive evaluation of anthropomorphic design. We further discuss how these differences translate into neurophysiological responses and propose an experimental set-up using a combination of behavioral, self-reported and eye-tracking data to empirically validate our proposed model.

Suggested Citation

  • Anna-Maria Seeger & Armin Heinzl, 2018. "Human Versus Machine: Contingency Factors of Anthropomorphism as a Trust-Inducing Design Strategy for Conversational Agents," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph (ed.), Information Systems and Neuroscience, pages 129-139, Springer.
    • Handle: RePEc:spr:lnichp:978-3-319-67431-5_15
    DOI: 10.1007/978-3-319-67431-5_15
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    Cited by:

    1. Pizzi, Gabriele & Scarpi, Daniele & Pantano, Eleonora, 2021. "Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot?," Journal of Business Research, Elsevier, vol. 129(C), pages 878-890.
    2. Rizomyliotis, Ioannis & Kastanakis, Minas N. & Giovanis, Apostolos & Konstantoulaki, Kleopatra & Kostopoulos, Ioannis, 2022. "“How mAy I help you today?” The use of AI chatbots in small family businesses and the moderating role of customer affective commitment," Journal of Business Research, Elsevier, vol. 153(C), pages 329-340.
    3. Thuy Duong Oesterreich & Eduard Anton & Julian Schuir & Alexander Brehm & Frank Teuteberg, 2023. "How can I help you? Design principles for task-oriented speech dialog systems in customer service," Information Systems and e-Business Management, Springer, vol. 21(1), pages 37-79, March.
    4. Przegalinska, Aleksandra & Ciechanowski, Leon & Stroz, Anna & Gloor, Peter & Mazurek, Grzegorz, 2019. "In bot we trust: A new methodology of chatbot performance measures," Business Horizons, Elsevier, vol. 62(6), pages 785-797.

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