Extending the Hegselmann-Krause Model of Opinion Dynamics to include AI Oracles
This work addresses how AI influences opinion dynamics in social systems, offering incremental insights into convergence behaviors under different information access scenarios.
The study extended the Hegselmann-Krause model to include an AI Oracle that averages community opinions, finding that with only Oracle access, opinions converge to a common value, while with full access to the true value, they converge to it but may be delayed, and partial access can lead to non-convergence unless universal Oracle access is provided.
The Hegselmann-Krause (HK) model of opinion dynamics describes how opinions held by individuals in a community change over time in response to the opinions of others and their access to the true value, T, to which these opinions relate. Here, I extend the simple HK model to incorporate an Artificially Intelligent (AI) Oracle that averages the opinions of members of the community. Agent-based simulations show that (1) if individuals only have access to the Oracle (and not T), and incorporate the Oracle's opinion as they update their opinions, then all opinions will converge on a common value; (2) in contrast, if all individuals also have access to T, then all opinions will ultimately converge to T, but the presence of an Oracle may delay the time to convergence; (3) if only some individuals have access to T, opinions may not converge to T, but under certain conditions, universal access to the Oracle will guarantee convergence to T; and (4) whether or not the Oracle only accesses the opinions of individuals who have access to T, or whether it accesses the opinions of everyone in the community, makes no marked difference to the extent to which the average opinion differs from T.