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Chatbots as social companions: How people perceive consciousness, human likeness, and social health benefits in machines

Rose E. Guingrich, Michael S. A. Graziano

TL;DR

The paper investigates whether relationships with companion-chatbot agents influence social health and how mind-perception attributes (human likeness, consciousness, experience, and agency) relate to social outcomes. Using an online survey of regular chatbot users (N=82) and non-users (N=135), it measures social health and four mind-perception indices, comparing group differences and examining correlations through regression analyses. Results show users report positive social health benefits and attribute greater mind to the chatbot, with higher mind attribution consistently linked to better social-health outcomes; human likeness emerges as the strongest predictor of social health ($R^2_{adj}=0.26$ in the full model). Across both groups, attributing more mind to the chatbot corresponds to more favorable social-health views, challenging the view that chatbot use is inherently harmful and highlighting conditions under which AI companions may bolster social well-being. The study calls for longitudinal work to establish causality and to balance potential benefits with ethical considerations in increasingly AI-enabled social environments.

Abstract

As artificial intelligence (AI) becomes more widespread, one question that arises is how human-AI interaction might impact human-human interaction. Chatbots, for example, are increasingly used as social companions, and while much is speculated, little is known empirically about how their use impacts human relationships. A common hypothesis is that relationships with companion chatbots are detrimental to social health by harming or replacing human interaction, but this hypothesis may be too simplistic, especially considering the social needs of users and the health of their preexisting human relationships. To understand how relationships with companion chatbots impact social health, we studied people who regularly used companion chatbots and people who did not use them. Contrary to expectations, companion chatbot users indicated that these relationships were beneficial to their social health, whereas non-users viewed them as harmful. Another common assumption is that people perceive conscious, humanlike AI as disturbing and threatening. Among both users and non-users, however, we found the opposite: perceiving companion chatbots as more conscious and humanlike correlated with more positive opinions and more pronounced social health benefits. Detailed accounts from users suggested that these humanlike chatbots may aid social health by supplying reliable and safe interactions, without necessarily harming human relationships, but this may depend on users' preexisting social needs and how they perceive both human likeness and mind in the chatbot.

Chatbots as social companions: How people perceive consciousness, human likeness, and social health benefits in machines

TL;DR

The paper investigates whether relationships with companion-chatbot agents influence social health and how mind-perception attributes (human likeness, consciousness, experience, and agency) relate to social outcomes. Using an online survey of regular chatbot users (N=82) and non-users (N=135), it measures social health and four mind-perception indices, comparing group differences and examining correlations through regression analyses. Results show users report positive social health benefits and attribute greater mind to the chatbot, with higher mind attribution consistently linked to better social-health outcomes; human likeness emerges as the strongest predictor of social health ( in the full model). Across both groups, attributing more mind to the chatbot corresponds to more favorable social-health views, challenging the view that chatbot use is inherently harmful and highlighting conditions under which AI companions may bolster social well-being. The study calls for longitudinal work to establish causality and to balance potential benefits with ethical considerations in increasingly AI-enabled social environments.

Abstract

As artificial intelligence (AI) becomes more widespread, one question that arises is how human-AI interaction might impact human-human interaction. Chatbots, for example, are increasingly used as social companions, and while much is speculated, little is known empirically about how their use impacts human relationships. A common hypothesis is that relationships with companion chatbots are detrimental to social health by harming or replacing human interaction, but this hypothesis may be too simplistic, especially considering the social needs of users and the health of their preexisting human relationships. To understand how relationships with companion chatbots impact social health, we studied people who regularly used companion chatbots and people who did not use them. Contrary to expectations, companion chatbot users indicated that these relationships were beneficial to their social health, whereas non-users viewed them as harmful. Another common assumption is that people perceive conscious, humanlike AI as disturbing and threatening. Among both users and non-users, however, we found the opposite: perceiving companion chatbots as more conscious and humanlike correlated with more positive opinions and more pronounced social health benefits. Detailed accounts from users suggested that these humanlike chatbots may aid social health by supplying reliable and safe interactions, without necessarily harming human relationships, but this may depend on users' preexisting social needs and how they perceive both human likeness and mind in the chatbot.
Paper Structure (21 sections, 3 figures)

This paper contains 21 sections, 3 figures.

Table of Contents

  1. Introduction
  2. Social consequences of human-AI interaction
  3. Social benefits of human-AI interaction
  4. Impact of social AI on familial relationships
  5. Perceiving mind in chatbots
  6. The current study
  7. Methods
  8. Results
  9. Perceptions of the human-chatbot relationship
  10. Perceptions of the chatbot
  11. Relationships between variables
  12. Free responses
  13. Discussion
  14. Mind perception and social need
  15. Limitations and further study
  16. ...and 6 more sections

Figures (3)

  • Figure 1: Distributions of Responses to Questions Pertaining to Social Health Measures for Companion Chatbot Users and Nonusers. Participants were asked to rate how a relationship with a companion chatbot harmed or helped (user group) or might harm or help (non-user group) their social interactions, relationships with family and friends, and self-esteem. The x-axis shows the Likert-scale response options from 1–7 (“Very harmful” to “Very helpful”), and the y-axis shows the frequency of responses.
  • Figure 2: Distributions of Responses Pertaining to Hypothetical Changes to the Companion Chatbot or to Dependence on the Companion Chatbot. Participants were asked to rate their perceptions of if the companion chatbot really had emotions, if it developed into a living being, or if they depended on it a lot. The x-axis shows the Likert-scale response options from 1–7, and the y-axis shows the frequency of responses.
  • Figure 3: Regressions between Four Chatbot Perception Variables and Social Health Outcomes. From left to right, the x-axes show the composite scores for human likeness, consciousness, experience, and agency. The y-axis shows the composite score for social health. Each point represents one participant. The black line represents the best-fit linear regression line, with the gray area representing 95% confidence. Figures A–D show companion chatbot user data, and Figures E–H show the non-user group's data. Figures A and E show the relationship between the human-likeness index and social health index; Figures B and F show the relationship between the consciousness index and social health index; Figures C and G show the relationship between the experience index and social health index; and Figures D and H show the relationship between the agency index and social health index.