Behavioral Cues of Humanness in Complex Environments: How People Engage With Human and Artificially Intelligent Agents in a Multiplayer Videogame

Stephanie Tulk Jesso; William G Kennedy; Eva Wiese

doi:10.3389/frobt.2020.531805

Behavioral Cues of Humanness in Complex Environments: How People Engage With Human and Artificially Intelligent Agents in a Multiplayer Videogame

Front Robot AI. 2020 Nov 13:7:531805. doi: 10.3389/frobt.2020.531805. eCollection 2020.

Authors

Stephanie Tulk Jesso¹, William G Kennedy², Eva Wiese¹

Affiliations

¹ Social and Cognitive Interactions Lab, Department of Psychology, George Mason University, Fairfax, VA, United States.
² Center for Social Complexity, Department of Computational Data Science, College of Science, George Mason University, Fairfax, VA, United States.

Abstract

The development of AI that can socially engage with humans is exciting to imagine, but such advanced algorithms might prove harmful if people are no longer able to detect when they are interacting with non-humans in online environments. Because we cannot fully predict how socially intelligent AI will be applied, it is important to conduct research into how sensitive humans are to behaviors of humans compared to those produced by AI. This paper presents results from a behavioral Turing Test, in which participants interacted with a human, or a simple or "social" AI within a complex videogame environment. Participants (66 total) played an open world, interactive videogame with one of these co-players and were instructed that they could interact non-verbally however they desired for 30 min, after which time they would indicate their beliefs about the agent, including three Likert measures of how much participants trusted and liked the co-player, the extent to which they perceived them as a "real person," and an interview about the overall perception and what cues participants used to determine humanness. T-tests, Analysis of Variance and Tukey's HSD was used to analyze quantitative data, and Cohen's Kappa and χ² was used to analyze interview data. Our results suggest that it was difficult for participants to distinguish between humans and the social AI on the basis of behavior. An analysis of in-game behaviors, survey data and qualitative responses suggest that participants associated engagement in social interactions with humanness within the game.

Keywords: Cognitive plausibility; Human-AI Interactions; Social AI; Social Robotics; Turing Tests; Videogames; Virtual Agents.