Solving AI’s last-mile problem with crowd-augmented expert work

Visual search tasks, such as identifying an unknownperson or location in a photo,are a crucial element of many forms of investigative work, from academic research, to journalism, to law enforcement. WhileAI techniques likecomputer visioncan often quickly and accurately narrow down a large search space of thousands of possibilities to a shortlist of promising candidates, they usually cannot select the correct match(es) among those, a challenge known as the last-mile problem.We have developedan approach called crowd-augmented expert workto leverage the complementary strengths of human intelligence to solve the last-mile problem. We reporton case studiesdeveloping and deploying two visual search tools, GroundTruth and Photo Sleuth, to illustrate this approach.