Source | sloanreview.mit.edu | Mark Purdy | Ray Eitel-Porter | Max Klymenko
Traders deciding on the next big market bet. A navigation app quickly mapping out a less-explored area. Fashion brands choosing the hottest color of the season. An airport managing flight delays.
What do these scenarios have in common? In each one, swarm intelligence blends global and local insight to improve how businesses make decisions.
Swarm intelligence is a form of artificial intelligence (AI) inspired by the insect kingdom. In nature, it describes how honeybees migrate, how ants form perfect trails, and how birds flock. In the world of AI, swarm systems draw input from individual people or machine sensors and then use algorithms to optimize the overall performance of the group or system in real time.
Consider Waze, the popular road navigation app that uses swarm intelligence to create and modify maps. Starting with limited digital maps, it began making tweaks based on its users’ GPS data along with manual map modifications by registered users. Entire cities have been mapped using this method, as was the case in Costa Rica’s capital, San José. And just as ants signal danger to their counterparts, so too do Waze users contribute live information from accident locations and traffic jams.