NEXT

NEXT is a tool that applies active learning to crowdsourcing. This is important because it allows the benefit of active learning to be seen by researchers in fields other than machine learning. We have brought these benefits to psychologists, biologists, and sociologists. We have also collaborated with non-academic organizations like the New Yorker, who is using NEXT to run their caption contest in order to discover the funniest caption.

Links:

NEXT: Ask better questions, get better, faster results

New Yorker Caption Contest

Scott Sievert‘s talk on NEXT: Crowdsourcing, Machine Learning and Cartoons

 

Key Messages:

Adaptive sampling reduces data collection cost

NEXT is a crowdsourcing data collection tool that can use adaptive sampling techniques

NEXT is easy to use by experimentalists, algorithm developer and practitioners, and a mathematical background is not required to use it.

NEXT developers use experimentalist engagement to aid research and to gain feedback to improve the software