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SSP Forum: Michael Bernstein ('06) on "Crowd-Powered Systems" » Show

Jan. 14, 2013

Start Date

& End Date

12:15 p.m.

Start Time

to

1:05 p.m.

End Time

at 460-126

Location

Symbolic Systems Forum presents...

"Crowd-Powered Systems"
Michael Bernstein
Computer Science Department

Monday, January 14, 2013
12:15-1:05 pm
Margaret Jacks Hall, Greenberg Seminar Room (460-126)
map link: http://campus-map.stanford.edu/?id=01-460&lat=37.4285008259&lng=-122.170359989&zoom=17&srch=460

ABSTRACT:
Crowd-powered systems combine computation with human intelligence, drawn from large groups of people connecting and coordinating online. These hybrid systems enable applications and experiences that neither crowds nor computation could support alone.

Unfortunately, crowd work is error-prone and slow, making it difficult to incorporate crowds as first-order building blocks in software systems. I introduce computational techniques that decompose complex tasks into simpler, verifiable steps to improve quality, and optimize work to return results in seconds. These techniques advance crowdsourcing into a platform that is reliable and responsive to the point where crowds can be used in interactive systems.

In this talk, I will present two crowd-powered systems to illustrate these ideas. The first, Soylent, is a word processor that uses paid micro-contributions to aid writing tasks such as text shortening and proofreading. Using Soylent is like having access to an entire editorial staff as you write. The second system, Adrenaline, is a camera that uses crowds to help amateur photographers capture the exact right moment for a photo. It finds the best smile and catches subjects in mid-air jumps, all in realtime. These systems point to a future where social and crowd intelligence are central elements of interaction, software, and computation.

 BIO:

Michael Bernstein is an Assistant Professor of Computer Science at Stanford University. His research in human-computer interaction focuses on the design of crowdsourcing and social computing systems. This work has received Best Paper awards and nominations at premier venues in human-computer interaction and social computing (ACM UIST, ACM CHI, ACM CSCW, AAAI ISWSM), and it has appeared in venues such as the New York Times, Slate, CNN and The Atlantic. Michael has been awarded the NSF graduate research fellowship, the Microsoft Research PhD fellowship, and the George M. Sprowls Award for best doctoral thesis in Computer Science at MIT. He holds Ph.D. and masters degrees in Computer Science from MIT, and a B.S. in Symbolic Systems from Stanford University.

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