Human-based computation: Difference between revisions

Revision as of 13:20, 26 May 2023

Revision as of 13:23, 26 May 2023

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Viewed as a form of social organization, human-based computation often surprisingly turns out to be more robust and productive than traditional organizations.<ref>{{cite web |url=http://research.3form.com/alex/pub/gecco-2002-18.pdf |title=Evolutionary Computation as a Form of Organization |author=Kosorukoff, Alexander, and David Goldberg |date=2002 |access-date=12 May 2022 |archive-url=https://web.archive.org/web/20110707063732/http://research.3form.com/alex/pub/gecco-2002-18.pdf |archive-date=7 July 2011 |url-status=dead}}</ref> The latter depend on obligations to maintain their more or less fixed structure, be functional and stable. Each of them is similar to a carefully designed mechanism with humans as its parts. However, this limits the freedom of their human employees and subjects them to various kinds of stresses. Most people, unlike mechanical parts, find it difficult to adapt to some fixed roles that best fit the organization. Evolutionary human-computation projects offer a natural solution to this problem. They adapt organizational structure to human spontaneity, accommodate human mistakes and creativity, and utilize both in a constructive way. This leaves their participants free from obligations without endangering the functionality of the whole, making people happier. There are still some challenging research problems that need to be solved before we can realize the full potential of this idea.

The algorithmic outsourcing techniques used in human-based computation are much more scalable than the manual or automated techniques used to manage outsourcing traditionally. It is this scalability that allows to easily distribute the effort among thousands of participants. It was suggested recently that this mass outsourcing is sufficiently different from traditional small-scale outsourcing to merit a new name [[crowdsourcing]].<ref>{{cite magazine |url=https://www.wired.com/2006/06/crowds/ |title=The Rise of Crowdsourcing |author=Howe, Jeff |magazine=Wired |date=June 2006|access-date=12 May 2022}}</ref> However, others have argued that crowdsourcing ought to be distinguished from true human-based computation.<ref>{{cite bookjournal |url=https://www.springer.com/gp/book/9781461488057 |title=Handbook of Human Computation |author=Michelucci, Pietro |journal=Springerlink |access-date=12 May 2022}}</ref> Crowdsourcing does indeed involve the distribution of computation tasks across a number of human agents, but Michelucci argues that this is not sufficient for it to be considered human computation. Human computation requires not just that a task be distributed across different agents, but also that the set of agents across which the task is distributed be ''mixed:'' some of them must be humans, but others must be traditional computers. It is this mixture of different types of agents in a computational system that gives human-based computation its distinctive character. Some instances of crowdsourcing do indeed meet this criterion, but not all of them do.

Human Computation organizes workers through a task market with APIs, task prices, and software-as-a-service protocols that allow employers / requesters to receive data produced by workers directly in to IT systems. As a result, many employers attempt to manage worker automatically through algorithms rather than responding to workers on a case-by-case basis or addressing their concerns. Responding to workers is difficult to scale to the employment levels enabled by human computation microwork platforms.<ref name="mw-cw">{{cite journal | last1 = Irani | first1 = Lilly|author1-link=Lilly Irani | year = 2015 | title = The Cultural Work of Microwork | journal = New Media & Society | volume = 17 | issue = 5 | pages = 720–739 | doi = 10.1177/1461444813511926| s2cid = 377594 }}</ref> Workers in the system Mechanical Turk, for example, have reported that human computation employers can be unresponsive to their concerns and needs<ref name="to-acm">{{cite journal | last1= Irani|first1=Lilly|last2 = Silberman | first2 = Six | year=2013|title=Turkopticon:Interrupting Workers Invisibility on Amazon Mechanical Turk|journal=Proceedings of SIGCHI 2013|series=Chi '13|pages=611–620|url=http://dl.acm.org/citation.cfm?id=2470742|doi=10.1145/2470654.2470742|isbn=9781450318990|s2cid=207203679}}</ref>