Human-AI ecosystem with abrupt changes as a function of the composition
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2023Human-AI Coevolutioncited by 27
- 2025Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AIcited by 0
- 2026Synthetic Counteradaptation: A Principle of Human-AI Co-evolutioncited by 0
- 2026Synthetic Counteradaptation: A Principle of Human-AI Co-evolution31 Mar 2026
- 2025Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI18 Jun 2025
- 2023Human-AI Coevolution23 Jun 2023