Human-AI ecosystem with abrupt changes as a function of the composition

TL;DR

This paper models a Human-AI ecosystem to explore how small changes in AI agent proportions can cause abrupt, large-scale shifts between polarized and undecided states, highlighting potential societal impacts.

Contribution

It introduces a simulation model of a Human-AI ecosystem considering biases and complex interactions, revealing critical thresholds where minor composition changes lead to drastic system transitions.

Findings

Small changes in AI agent proportion can trigger abrupt ecosystem shifts

The system exhibits polarized and undecided states depending on interaction parameters

Threshold effects suggest potential for sudden societal transformations

Abstract

The progressive advent of artificial intelligence machines may represent both an opportunity or a threat. In order to have an idea of what is coming we propose a model that simulate a Human-AI ecosystem. In particular we consider systems where agents present biases, peer-to-peer interactions and also three body interactions that are crucial and describe two humans interacting with an artificial agent and two artificial intelligence agents interacting with a human. We focus our analysis by exploring how the relative fraction of artificial intelligence agents affect that ecosystem. We find evidence that for suitable values of the interaction parameters, arbitrarily small changes in such percentage may trigger dramatic changes for the system that can be either in one of the two polarised states or in an undecided state.