The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence
Author
Abstract
Suggested Citation
DOI: 10.1177/2053951720919776
Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-02554196
Download full text from publisher
References listed on IDEAS
- Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
- David H. Autor & David Dorn, 2013.
"The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market,"
American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
- David H. Autor & David Dorn, 2009. "The Growth of Low Skill Service Jobs and the Polarization of the U.S. Labor Market," NBER Working Papers 15150, National Bureau of Economic Research, Inc.
- Autor, David & Dorn, David, 2012. "The Growth of Low Skill Service Jobs and the Polarization of the U.S. Labor Market," IZA Discussion Papers 7068, Institute of Labor Economics (IZA).
- Siou Chew Kuek & Cecilia Paradi-Guilford & Toks Fayomi & Saori Imaizumi & Panos Ipeirotis & Patricia Pina & Manpreet Singh, 2015. "The Global Opportunity in Online Outsourcing," World Bank Other Operational Studies 22284, The World Bank.
- David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
- Schmidt, Florian A., 2019. "Crowdproduktion von Trainingsdaten: Zur Rolle von Online-Arbeit beim Trainieren autonomer Fahrzeuge," Study / edition der Hans-Böckler-Stiftung, Hans-Böckler-Stiftung, Düsseldorf, volume 127, number 417, October.
More about this item
Keywords
Digital platform labour; micro-work; datafied production processes; artificial intelligence; machine learning;NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-05-25 (Big Data)
- NEP-CMP-2020-05-25 (Computational Economics)
- NEP-PAY-2020-05-25 (Payment Systems & Financial Technology)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-02554196. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD). General contact details of provider: https://hal.archives-ouvertes.fr/ .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.