How AI’s self-prolongation influences people’s perceptions of its autonomous mind: The case of U.S. residents

Abstract

The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to find ways to make sense of the minds of AI. The issue of AI’s capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, to make assessments. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents in the United States, we found that the more people believe that an AI agent seeks continued functioning, the more they believe in that AI agent’s capability of having a mind of its own. Moreover, we also found that the above association becomes stronger if a person is more familiar with personally interacting with AI. This suggests a directional pattern of value reinforcement in perceptions of AI. As the information processing of AI becomes even more sophisticated in the future, it will be much harder to set clear boundaries about what it means to have an autonomous mind.

Exploring Perceptions of AI's Desire for Functioning and its Impact on Beliefs about Autonomous Mind Using the Bayesian Mindsponge Framework (BMF)

“…Vuong et al [1] suggest that the Bayesian Mindsponge Framework (BMF) analytics provides a comprehensive and powerful approach to understanding the complex relationship between people's perceptions of AI's desire to continue functioning and their beliefs about AI's autonomous mind. The BMF combines the principles of the mindsponge mechanism, which explains how individuals process information and generate beliefs, with Bayesian inference, a statistical approach that makes it possible to analyze and quantify complex relationships using actual data [2,3].…”