Crowdsourcing marketplaces like oDesk or Amazon’s Mechanical Turk give us access to people all over the world that can solve various tasks, like virtual personal assistants, image labelers, or people that can clean up gnarly datasets. Humans can solve tasks that artificial intelligence is not yet able to solve, or needs help solving, without having to resort to complex machine learning or statistics. But humans are quirky: give them bad instructions, allow them to get bored, or make them do too repetitive a task, and they will start making mistakes. In this talk, I’ll explain how to effectively benefit from crowd workers to solve your most challenging tasks, using examples from the wild and from our work at Locu.
Machine learning and crowdsourcing are at the core of most of the problems we solve at Locu. When possible, we automate tasks with the help of trained regressions and classifiers. However, it’s not always possible to build machine-only decision-making tools, and we often need to marry machines and crowds. In this talk, I’ll highlight:
Adam is Locu’s Director of Data. He recently completed his Ph.D. in Computer Science at MIT. His dissertation is on database systems and human computation. He is a recipient of the NSF and NDSEG fellowships, and has previously worked at ITA, Google, IBM, and FactSet. In his free time, he builds course content to get people excited about data and programming.
For exhibition and sponsorship opportunities, contact Susan Stewart at firstname.lastname@example.org
For information on trade opportunities with O'Reilly conferences, email email@example.com
For media-related inquiries, contact Maureen Jennings at firstname.lastname@example.org
View a complete list of Strata contacts