We discuss challenges and opportunities for developing generalized task markets where human and machine intelligence are enlisted to solve problems, based on a consideration of the competencies, availabilities, and pricing of different problem-solving resources. The approach couples human computation with machine learning and planning, and is aimed at optimizing the flow of subtasks to people and to computational problem solvers. We illustrate key ideas in the context of Lingua Mechanica, a project focused on harnessing human and machine translation skills to perform translation among languages. We present infrastructure and methods for enlisting and guiding human and machine computation for language translation, including details about the hardness of generating plans for assigning tasks to solvers. Finally, we discuss studies performed with machine and human solvers, focusing on components of a Lingua Mechanica prototype.
|Original language||American English|
|Title of host publication||Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010|
|Number of pages||8|
|State||Published - 15 Jul 2010|
|Event||24th AAAI Conference on Artificial Intelligence, AAAI 2010 - Atlanta, United States|
Duration: 11 Jul 2010 → 15 Jul 2010
|Name||Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010|
|Conference||24th AAAI Conference on Artificial Intelligence, AAAI 2010|
|Period||11/07/10 → 15/07/10|
Bibliographical noteFunding Information:
The authors thank Vikram Dendi, Paul Koch, Raman Sarin, Paul Newson and Tommy A. Bros-man for their assistance on the Lingua Mechanica project.
© 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.