AutoMan: A Platform for Integrating Human-Based and Digital Computation.
Humans can perform many tasks with ease that remain difficult or impossible for computers. Crowdsourcing platforms like Amazon Mechanical Turk make it possible to harness human-based computational power at an unprecedented scale, but their utility as a general-purpose computational platform remains...
| Published in: | Communications of the ACM Vol. 59; no. 6; pp. 102 - 110 |
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| Main Authors: | , , , |
| Format: | Article |
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Association for Computing Machinery
Jun2016
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=115648856&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 115648856 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00010782 ACM jtl: Communications of the ACM issn: 00010782 maglogo: N pubinfo: dt: Jun2016 vid: 59 iid: 6 pid: 68 pub: Association for Computing Machinery artinfo: ui: 115648856 10.1145/2927928 ppf: 102 ppct: 8 formats: tig: atl: AutoMan: A Platform for Integrating Human-Based and Digital Computation. aug: au: Barowy, Daniel W. Curtsinger, Charlie Berger, Emery D. McGregor, Andrew affil: College of Information and Computer Sciences, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA su: Computer programming Logic programming Crowdsourcing Distributed computing Programming languages sug: subj: Computer programming Logic programming Crowdsourcing Distributed computing Programming languages ab: Humans can perform many tasks with ease that remain difficult or impossible for computers. Crowdsourcing platforms like Amazon Mechanical Turk make it possible to harness human-based computational power at an unprecedented scale, but their utility as a general-purpose computational platform remains limited. The lack of complete automation makes it difficult to orchestrate complex or interrelated tasks. Recruiting more human workers to reduce latency costs real money, and jobs must be monitored and rescheduled when workers fail to complete their tasks. Furthermore, it is often difficult to predict the length of time and payment that should be budgeted for a given task. Finally, the results of human-based computations are not necessarily reliable, both because human skills and accuracy vary widely, and because workers have a financial incentive to minimize their effort. We introduce AutoMan, the first fully automatic crowd- programming system. AutoMan integrates human-based computations into a standard programming language as ordinary function calls that can be intermixed freely with traditional functions. This abstraction lets AutoMan programmers focus on their programming logic. An AutoMan program specifies a confidence level for the overall computation and a budget. The AutoMan runtime system then transparently manages all details necessary for scheduling, pricing, and quality control. AutoMan automatically schedules human tasks for each computation until it achieves the desired confidence level; monitors, reprices, and restarts human tasks as necessary; and maximizes parallelism across human workers while staying under budget. pubtype: Periodical doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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