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Colloquium @ Cornell Tech: Dan Weld

Monday, October 16, 2017 at 11:00am to 12:00pm

Bloomberg Center-Room 165, Cornell Tech 2 West Loop Road New York, NY 10044

"High-Quality Crowdsourcing"

Crowdsourcing, the act of outsourcing a task to a large group of workers, is skyrocketing in popularity, but also leaves some unsatisfied. Requestors often complain about the low-quality of crowd work, but whose fault is this? We argue that techniques like majority vote and expectation maximization (EM) miss the point and don’t solve the true, underlying problems: confusing task instructions and poor worker training. Instead we advocate three new methods: 1) gated instruction, 2) adaptive testing, 3) micro-argumentation,  and 4) self-improving workflows.  These methods fuse ideas from HCI with AI methods such as partially-observable Markov decision problems & reinforcement learning. As a bonus, we’ll present recent work on active learning, where the crowd does more than just label examples.

 

Daniel S. Weld is Thomas J. Cable / WRF Professor & Entrepreneurial Faculty Fellow at the Allen School of Computer Science & Engineering at the University of Washington. After formative education at Phillips Academy, he went to Yale University for bachelor's degrees in both Computer Science and Biochemistry. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator's award in 1989, an Office of Naval Research Young Investigator's award in 1990, was named AAAI Fellow in 1999 and deemed ACM Fellow in 2005. Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM, guest editor for Computational Intelligence and Artificial Intelligence. He co-founded several companies, including Netbot (acquired by Excite), Adrelevence (acquired by Mediametrix), and Nimble Technology (acquired by Actuate).

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Event Type

Seminar

Departments

Cornell Tech

Tags

CornellTech, CornellTechResearch, CornellTechCommunity, CornellTechColloquia

Speaker

Dan Weld

Speaker Affiliation

University of Washington

Disability Access Information

Available Upon Request