Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions

By Eun Go, Shyam Sundar. Computers in Human Behavior, 2019

870 citations recorded by the source corpus.

Abstract Chatbots are replacing human agents in a number of domains, from online tutoring to customer-service to even cognitive therapy. But, they are often machine-like in their interactions. What can we do to humanize chatbots? Should they necessarily be driven by human operators for them to be considered human? Or, will an anthropomorphic visual cue on the interface and/or a high-level of contingent message exchanges provide humanness to automated chatbots? We explored these questions with a 2 (anthropomorphic visual cues: high vs. low anthropomorphism) × 2 (message interactivity: high vs. low message interactivity) × 2 (identity cue: chat-bot vs. human) between-subjects experiment (N = 141) in which participants interacted with a chat agent on an e-commerce site about choosing a digital camera to purchase. Our findings show that a high level of message interactivity compensates for the impersonal nature of a chatbot that is low on anthropomorphic visual cues. Moreover, identifying the agent as human raises user expectations for interactivity. Theoretical as well as practical implications of these findings are discussed.

Subfields: Artificial Intelligence, Literature and Literary Theory, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/d551ae4bb44863ee3e5344db033367540a64144b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Literature and Literary Theory

In Sociology and Political Science

Citations in the corpus

A Literature Survey of Recent Advances in Chatbots (2021, background): “Nonetheless, different levels of embodiment-the way chatbots are human-like [10]-and disclosure-how and when the nature of the chatbot is revealed to the user-seem to impact users’ engagement with and trust in chatbots [11]).”
Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review (2021, background): “Humanoid service robots and artificial intelligence bots, for example, are increasingly attracting industry attention (Araujo, 2018; Go & Sundar, 2019; Larivi (cid:1) ere et al., 2017; Thomaz et al., 2020).”
An Overview of Chatbot Technology (2020, background): “Human-likeness can be suggested by using human ﬁgures (visual cues), human-associated names, or identity (identity cues) and mimicking of human languages (conversational cues) [24].”
AI literacy and its implications for prompt engineering strategies (2024, background): “Moreover, identifying the LLM-based AI system as human raises user expectations for inter-activity (Go & Sundar, 2019).”
UvA-DARE (Digital Academic Repository) Privacy concerns in chatbot interactions (neutral): “In the machine-like version, the chatbot did not carry a human-like name (it was called ChatbotX), similar to Araujo [2]; displayed a neutral visual of a dialog bubble, similar to Go and Sundar [20]; and only asked questions without acknowl-edging previous answers.”
Emotionally-Aware Chatbots: A Survey (2019, background): “cus right now is to have an intelligent and humanizing machine to have a better engagement when communicating with human [16].”
Teachers’ attitudes towards chatbots in education: a technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics (2021, background): “…perceptions of the agents’ anthropomorphic level through different types of social cues: visual attributes, such as the agent having the shape of a human figure, identity attributes such as personal names, and conversational features using language that mimic the human one (Go and Sundar 2019).”
AI-based chatbots in customer service and their effects on user compliance (2020, background): “Besides two exceptions that focused on verbal ADCs (Araujo 2018; Go and Sundar 2019), to the best of our knowledge, no other studies have directly targeted verbal ADCs to extend past research on embodied agents.”
“Chatting with ChatGPT”: Analyzing the factors influencing users' intention to Use the Open AI's ChatGPT using the UTAUT model (2023, background): “Prior scholarships [112,113] suggested that interactivity is essential when designing and promoting chatbots to potential users.”