<html><head><style type='text/css'>p { margin: 0; }</style></head><body><div style='font-family: arial,helvetica,sans-serif; font-size: 12pt; color: #000000'><div><span name="x"></span><b>Crowd-Powered Systems</b>
<br>
<b style="color: rgb(0, 0, 0);"><a href="http://people.csail.mit.edu/msbernst/">Michael Bernstein</a></b><span style="color: rgb(0, 0, 0);">, </span><a style="color: rgb(0, 0, 0);" href="http://web.mit.edu/">MIT</a><span style="color: rgb(0, 0, 0);">
</span><br style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);"><a name="2012-02-22">Wednesday, February 22, 2012</a>, 4:30 PM - 5:30 PM
</span><br style="color: rgb(0, 0, 0);"><span style="color: rgb(0, 0, 0);">
</span><a style="color: rgb(0, 0, 0);" href="http://www.princeton.edu/%7Epumap/index.html?id=167">Computer Science</a> Small Auditorium (Room 105)
<br><br>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.
<p><br>
</p><p>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. <br></p><p><br></p><p>
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. <br></p><p><br></p>
Michael Bernstein is a PhD candidate in Computer Science at the
Massachusetts Institute of Technology. His research in human-computer
interaction focuses on crowdsourcing and social computing systems. He
has been awarded Best Student Paper at UIST 2010, Best Paper at ICWSM
2011, the NSF graduate research fellowship and the Microsoft Research
PhD fellowship. His work has appeared in venues like the New York Times,
Slate, CNN and The Atlantic. He earned his masters in Computer Science
at MIT, and a bachelors degree in Symbolic Systems at Stanford
University.
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