  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.
