Big Thinking in Small Pieces: Computer Guides Humans in Crowdsourced Research

The Knowledge Accelerator, uses a machine-learning program to sort and organize information. Getting a bunch of people to collectively research and write a coherent report without any one person seeing the big picture may seem akin to a group of toddlers producing Hamlet by randomly pecking at typewriters. But Carnegie Mellon University researchers have shown it actually works pretty well - if a computer guides the process. Their system, called the Knowledge Accelerator, uses a machine-learning program to sort and organize information uncovered by individuals focused on just a small segment of the larger project. It makes new assignments according to those findings and creates a structure for the final report based on its emerging understanding of the topic. Bosch, which supported and participated in the study, already is adapting the Knowledge Accelerator approach to gather diagnostic and repair information for complex products. Relying on an individual to maintain the big picture on such projects creates a bottleneck that has confined crowdsourcing largely to simple tasks, said Niki Kittur, associate professor in the Human-Computer Interaction Institute (HCII).