Human computation is a relatively new research area that studies how to build intelligent systems that involves human computers, with each of them performing computation (e.g., image classification, translation, and protein folding) that leverage human intelligence, but challenges even the most sophisticated AI algorithms that exist today. With the immense growth of the Web, human computation systems can now leverage the abilities of an unprecedented number of Internet users to perform complex computation. Various genres of human computation applications are available today, including games with a purpose (e.g., the ESP Game) that generates useful data through gameplay, crowdsourcing marketplaces (e.g., Amazon Mechanical Turk) that coordinate workers to perform tasks for monetary rewards, and identity verification systems (e.g. reCAPTCHA) that generate useful data through users performing computation for access to online content.

Despite the variety of human computation applications, there exist many common core research issues. How can we design mechanisms for querying human computers in such a way that incentivizes or encourages truthful responses? What are the techniques for aggregating noisy outputs from multiple human computers? How do we effectively assign tasks to human computers to match their particular expertise and interests? What are some programming paradigms for designing algorithms that effectively leverage the humans in the loop? How do we build human computation systems that involve the joint efforts of both machines and humans, trading off each of their particular strengths and weaknesses? Significant advances on such questions will likely need to draw many disciplines, including machine learning, mechanism and market design, information retrieval, decision-theoretic planning, optimization, human computer interaction, etc.

The workshop recognizes the growing opportunity for AI to function as an enabling technology in human computation systems. At the same time, AI can leverage technical advances and data collected from human computation systems for its own advancement. The goal of HCOMP 2012 is to bring together academic and industry researchers from diverse subfields in a stimulating discussion of existing human computation applications and future directions of this relatively new subject area. The workshop also aims to broaden the scope of human computation to more than the issue of data collection to a broader definition of human computation, to study systems where humans perform a major part of the computation or are an integral part of the overall computational system.


Topics of interest include, but are not limited to:

•Programming languages, tools and platforms to support human computation

•Domain-specific challenges in human computation

•Methods for estimating the cost, reliability, and skill of labelers

•Methods for designing and controlling workflows for human computation tasks

•Empirical and formal models of incentives in human computation systems

•Benefits of one-time versus repeated labeling

•Design of manipulation-resistance mechanisms in human computation

•Concerns regarding the protection of labeler identities

•Active learning from imperfect human labelers

•Techniques for inferring expertise and routing tasks

•Theoretical limitations of human computation


The workshop will consist of several invited talks from prominent researchers in different areas related to human computation, selected presentations of technical and position papers, as well as two poster and demo sessions, organized by theme.


Technical papers and position papers may be up to 7 pages in length, and should follow AAAI formatting guidelines. For demos and poster presentations, authors should submit a short paper or extended abstract (up to 2 pages). We welcome early work, and particularly encourage submission of visionary position papers that are more forward looking.

Papers must be submitted electronically via CMT – please visit the supplemental workshop site for further instructions. The submission deadline is April 2, 2012.

Submissions are sought both for new work in the area of human computation as well as for work recently published or soon to be published in another conference or journal; for submissions of the latter kind, the authors must clearly state the venue of publication.

According to AAAI, workshop authors are not required to transfer copyright, so they can still submit their papers to a conference or journal after the workshop. However, AAAI cannot include papers that have been published before. In other words, if your paper was previously published, you should submit just a 2-page abstract; otherwise, you should submit your paper to be published by AAAI.

Call For Papers


Yiling Chen (Chair)

Harvard University

Luis von Ahn

Carnegie Mellon University

Panagiotis Ipeirotis

New York University

Edith Law

Carnegie Mellon University

Haoqi Zhang

Harvard University


Serge Belongie

Michael Berstein

Jeff Bigham

Joel Brandt

Chris Callison-Burch

Ed Chi

Deepak Ganesan

Arpita Ghosh

Kristen Grauman

Bjoern Hartmann

Eric Horviz

Adam Kalai

Ece Kamar

Sep Kamvar

Rob Miller

Paul Resnick

Yaron Singer

Sidd Suri

Jenn Wortman Vaughan

Peter Welinder


Aditya Parameswaran

Adriana Kovashka

Anand Kulkarni

Alex Quinn

Arpita Ghosh

Brendan O’Connor

Chien-Ju Ho

Peng Dai

Devi Parikh

Dafna Shahaf

Greg Little

Yu Zhang

Lydia Chilton

Tim Kraska

Adam Marcus

Michael Bernstein

Paul Andre

Markus Krause

Reid Priedhorsky

Sep Kamvar

Victor Shnayder

Steven Dow

Vamshi Ambati

Jens Witkowski

Alice Gao

Jane Hsu

Yu-an Sun