# Optimal incentives for collective intelligence

arXiv: https://arxiv.org/abs/1611.03899 · HTML: https://mlsanity.com/paper/1611.03899/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Nov 2016.

## Built on by (most cited first, 3 of 3)

- [AI-enhanced Collective Intelligence](https://mlsanity.com/paper/2403.10433/) (2024)
- [Upgrading Democracies with Fairer Voting Methods](https://mlsanity.com/paper/2505.14349/) (2025)
- [An evolutionary origin of collective decision making in humans and machines](https://mlsanity.com/paper/2610.05676/) (2026)

## Abstract (arXiv)

Collective intelligence is the ability of a group to perform more effectively than any individual alone. Diversity among group members is a key condition for the emergence of collective intelligence, but maintaining diversity is challenging in the face of social pressure to imitate one's peers. We investigate the role incentives play in maintaining useful diversity through an evolutionary game-theoretic model of collective prediction. We show that market-based incentive systems produce herding effects, reduce information available to the group and suppress collective intelligence. In response, we propose a new incentive scheme that rewards accurate minority predictions, and show that this produces optimal diversity and collective predictive accuracy. We conclude that real-world systems should reward those who have demonstrated accuracy when majority opinion has been in error.