# An AI Theory of Mind Will Enhance Our Collective Intelligence

arXiv: https://arxiv.org/abs/2411.09168 · HTML: https://mlsanity.com/paper/2411.09168/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 155 references that are in the map.
- First posted on arXiv 14 Nov 2024.

## Builds on (most cited first, 22 of 22)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Emergent Abilities of Large Language Models](https://mlsanity.com/paper/2206.07682/) (2022)
- [Chain of Thought Empowers Transformers to Solve Inherently Serial Problems](https://mlsanity.com/paper/2402.12875/) (2024)
- [Cooperating with Machines](https://mlsanity.com/paper/1703.06207/) (2017)
- [A new sociology of humans and machines](https://mlsanity.com/paper/2402.14410/) (2024)
- [Theory of Minds: Understanding Behavior in Groups Through Inverse Planning](https://mlsanity.com/paper/1901.06085/) (2019)
- [The free energy principle made simpler but not too simple](https://mlsanity.com/paper/2201.06387/) (2022)
- [Human-AI Coevolution](https://mlsanity.com/paper/2306.13723/) (2023)
- [Technological Approach to Mind Everywhere (TAME): an experimentally-grounded framework for understanding diverse bodies and minds](https://mlsanity.com/paper/2201.10346/) (2021)
- [Designing Ecosystems of Intelligence from First Principles](https://mlsanity.com/paper/2212.01354/) (2022)
- [Collective Intelligence in Human-AI Teams: A Bayesian Theory of Mind Approach](https://mlsanity.com/paper/2208.11660/) (2022)
- [JIDT: An information-theoretic toolkit for studying the dynamics of complex systems](https://mlsanity.com/paper/1408.3270/) (2014)
- [AI-enhanced Collective Intelligence](https://mlsanity.com/paper/2403.10433/) (2024)
- [A Review on Machine Theory of Mind](https://mlsanity.com/paper/2303.11594/) (2023)
- [Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation](https://mlsanity.com/paper/1806.09373/) (2018)
- [Integrated information as a common signature of dynamical and information-processing complexity](https://mlsanity.com/paper/2106.10211/) (2021)
- [Factorised Active Inference for Strategic Multi-Agent Interactions](https://mlsanity.com/paper/2411.07362/) (2024)
- [The Morphospace of Consciousness](https://mlsanity.com/paper/1705.11190/) (2017)
- [The morphospace of language networks](https://mlsanity.com/paper/1803.01934/) (2018)
- [Biological arrow of time: Emergence of tangled information hierarchies and self-modelling dynamics](https://mlsanity.com/paper/2409.12029/) (2024)
- [Comparing Information-Theoretic Measures of Complexity in Boltzmann Machines](https://mlsanity.com/paper/1706.09667/) (2017)

## Built on by (most cited first, 1 of 1)

- [Enhancing Collective Intelligence in Large Language Models Through Emotional Integration](https://mlsanity.com/paper/2503.04849/) (2025)

## Abstract (arXiv)

Collective intelligence plays a central role in many fields, from economics and evolutionary theory to neural networks and eusocial insects, and is also core to work on emergence and self-organisation in complex-systems theory. However, in human collective intelligence there is still much to understand about how specific psychological processes at the individual level give rise to self-organised structures at the social level. Psychological factors have so far played a minor role in collective-intelligence studies because the principles are often general and applicable to agents without sophisticated psychologies. We emphasise, with examples from other complex adaptive systems, the broad applicability of collective-intelligence principles, while noting that mechanisms and time scales differ markedly between cases. We review evidence that flexible collective intelligence in human social settings is improved by a particular cognitive tool: our Theory of Mind. We then hypothesise that AIs equipped with a theory of mind will enhance collective intelligence in ways similar to human contributions. To make this case, we step back from the algorithmic basis of AI psychology and consider the large-scale impact AI can have as agential actors in a 'social ecology' rather than as mere technological tools. We identify several key characteristics of psychologically mediated collective intelligence and show that the development of a Theory of Mind is crucial in distinguishing human social collective intelligence from more general forms. Finally, we illustrate how individuals, human or otherwise, integrate within a collective not by being genetically or algorithmically programmed, but by growing and adapting into the socio-cognitive niche they occupy. AI can likewise inhabit one or multiple such niches, facilitated by a Theory of Mind.