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The Influence of Crowdsourcing Business Model into Artificial Intelligence

The Influence of Crowdsourcing Business Model into Artificial Intelligence

Anna Szopa
Copyright: © 2019 |Pages: 11
ISBN13: 9781522583622|ISBN10: 1522583629|EISBN13: 9781522583639
DOI: 10.4018/978-1-5225-8362-2.ch013
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MLA

Szopa, Anna. "The Influence of Crowdsourcing Business Model into Artificial Intelligence." Crowdsourcing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 246-256. https://doi.org/10.4018/978-1-5225-8362-2.ch013

APA

Szopa, A. (2019). The Influence of Crowdsourcing Business Model into Artificial Intelligence. In I. Management Association (Ed.), Crowdsourcing: Concepts, Methodologies, Tools, and Applications (pp. 246-256). IGI Global. https://doi.org/10.4018/978-1-5225-8362-2.ch013

Chicago

Szopa, Anna. "The Influence of Crowdsourcing Business Model into Artificial Intelligence." In Crowdsourcing: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 246-256. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8362-2.ch013

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Abstract

We observe situation in which human computation processes leverage the abilities of people via the Web to perform complex computation. In this context human intelligence is harnessed to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms. The aim of this paper is to achieve an in-depth understanding of the influence of crowdfunding business process into Artificial Intelligence and what kind of computational problems can be efficiently answered using human computation. Wisdom of crowd has been applied successfully to a range of tasks, from translating text and marking images, collecting information to building large databases and to solve problems that are difficult for machines to solve. Presented hybrid solutions will be considered as optimization- leveraging machine intelligence to help improve the accuracy and efficiency of algorithms.

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