It’s well known that bees dance to convey where useful resources are located but how do bees convey the quality of the resource and what makes this information credible? Rory Sutherland and Glen Weyl argue that the bees have hit upon a key idea, quadratic dancing or as I like to put it, square dancing.
Seeley’s research shows that the time they spend on dances grows not linearly but quadratically in proportion to the attractiveness of the site they encountered. Twice as good a site leads to four times as much wiggling, three times as good a site leads to nine times as lengthy a dance, and so forth.
Quadratic dancing has some useful properties which can be duplicated in humans with quadratic voting.
Under Quadratic Voting (QV), by contrast, individuals have a vote budget that they can spread around different issues that matter to them in proportion to the value those issues hold for them. And just as with Seeley’s bees, it becomes increasingly costly proportionately to acquire the next unit of influence on one issue. This approach highlights not only frequency of preferences but also intensity of preferences, by forcing individuals to decide how they will divide their influence across issues, while penalising the single-issue fanatic’s fussiness of putting all one’s weight on a single issue. It encourages individuals to distribute their points in precise proportion to how much each issue matters to them.
They offer a useful application
Consider a firm that wants to learn whether customers care about particular product attributes: colour, quality, price, and so on. Rather than simply ask people what they care about — which leads to notoriously inaccurate results, often where people affect strong views just to maximise their individual influence — a business, or a public service, could supply customers with budgets of credits which they then used to vote, in quadratic fashion, for the attributes they want. This forces the group of respondents, like the swarm of bees, to allocate more resources to the options they care most about.