Ghost work

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Ghost work is work performed by a human, but believed by a customer to be performed by an automated process. [1] The term was coined by anthropologist Mary L. Gray and computer scientist Siddharth Suri in their 2019 book, Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. [2]

Contents

Definition

Gray and Suri state that ghost work focuses on task-based and content-driven work that can be funneled through the Internet and application programming interfaces (APIs). They say that this work can include labelling, editing, and sorting information or content, as well as content moderation. [3]

They also state that ghost work can be performed remotely and on a contractual basis and that it is an invisible workforce, scaled for those who desire full-time, part-time, or ad-hoc work. [3] [4] A benefit of ghost work is flexible hours because the worker chooses when they complete a task, making it an appealing option for those in between jobs or in need of side work. [4]

Ghost work is differentiated from gig work or temporary work because it is task-based and uncredited. While gig work involves a general platform, ghost work emphasizes the software or algorithm aspect of assisting machines to automate further. Through labelling content, ghost workers teach the machine to learn. Ghost workers at Amazon have found ways to help each other and self-organize, often through WhatsApp groups where they mobilize to push for changes to the platform. [5]

False perception

According to Lilly Irani, an associate professor of labor at the University of California, San Diego, the computer science world and tech companies are invested in producing the image of technological magic. [2] She says that MTurk hides the people involved in the production, whose visibility could otherwise obstruct this favorable perception. [2] Her view is that this perception isn't only aimed at the public image of the company but also at investors, who are significantly more likely to back businesses built on scalable technology, rather than unwieldy work forces demanding office space and minimum wages. [2] In addition, she feels that there is a strong belief that these workers are a stopgap until better AI reduces the need for relying on humans for such tasks. [2] . Despite the belief, the market for ghost work doesn't show apparent signs of declining. [6] There are some disadvantages, but the ghost work industry will potentially grow even more in the upcoming years. [5]

Related Research Articles

Amazon Mechanical Turk (MTurk) is a crowdsourcing website with which businesses can hire remotely located "crowdworkers" to perform discrete on-demand tasks that computers are currently unable to do as economically. It is operated under Amazon Web Services, and is owned by Amazon. Employers, known as requesters, post jobs known as Human Intelligence Tasks (HITs), such as identifying specific content in an image or video, writing product descriptions, or answering survey questions. Workers, colloquially known as Turkers or crowdworkers, browse among existing jobs and complete them in exchange for a fee set by the requester. To place jobs, requesters use an open application programming interface (API), or the more limited MTurk Requester site. As of April 2019, requesters could register from 49 approved countries.

Human-based computation (HBC), human-assisted computation, ubiquitous human computing or distributed thinking is a computer science technique in which a machine performs its function by outsourcing certain steps to humans, usually as microwork. This approach uses differences in abilities and alternative costs between humans and computer agents to achieve symbiotic human–computer interaction. For computationally difficult tasks such as image recognition, human-based computation plays a central role in training Deep Learning-based Artificial Intelligence systems. In this case, human-based computation has been referred to as human-aided artificial intelligence.

<span class="mw-page-title-main">Crowdsourcing</span> Sourcing services or funds from a group

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Labeled data is a group of samples that have been tagged with one or more labels. Labeling typically takes a set of unlabeled data and augments each piece of it with informative tags. For example, a data label might indicate whether a photo contains a horse or a cow, which words were uttered in an audio recording, what type of action is being performed in a video, what the topic of a news article is, what the overall sentiment of a tweet is, or whether a dot in an X-ray is a tumor.

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<span class="mw-page-title-main">Gig worker</span> Independent on-demand temporary workers

Gig workers are independent contractors, online platform workers, contract firm workers, on-call workers, and temporary workers. Gig workers enter into formal agreements with on-demand companies to provide services to the company's clients.

<span class="mw-page-title-main">Mary L. Gray</span> American anthropologist and author

Mary L. Gray is an American anthropologist and author. She is a Fellow at Harvard University's Berkman Klein Center for Internet and Society, as well as a Senior Principal Researcher at Microsoft Research. Along with her research, Gray teaches at Indiana University, maintaining an appointment as an Associate Professor of the Media School, with affiliations in American Studies, Anthropology, and Gender Studies. In 2020, she was awarded a MacArthur Genius Grant in recognition of her work "investigating the ways in which labor, identity, and human rights are transformed by the digital economy."

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References

  1. ↑ "A walk with Mary Gray - Long version interview - YouTube". www.youtube.com. 4 December 2019. Retrieved 2020-12-25.
  2. 1 2 3 4 5 Gent, Edd. "The 'ghost work' powering tech magic". www.bbc.com. Retrieved 2019-10-22.
  3. 1 2 Gray, Mary L. (2019). Ghost work : how to stop Silicon Valley from building a new global underclass. Siddharth Suri. Boston. ISBN   978-1-328-56624-9. OCLC   1052904468.{{cite book}}: CS1 maint: location missing publisher (link)
  4. 1 2 "Ghost Work and the Future of Employment - MIT Technology Review". MIT Technology Review Events. Retrieved 2019-10-22.
  5. 1 2 Moreschi, Bruno; Pereira, Gabriel; Cozman, Fabio G. (2020-04-17). "The Brazilian Workers in Amazon Mechanical Turk: Dreams and realities of ghost workers". Revista Contracampo. 39 (1). doi: 10.22409/contracampo.v39i1.38252 . ISSN   2238-2577. S2CID   219078629.
  6. ↑ "'Ghost Work' explores the ups and mostly downs of the hidden gig economy". GeekWire. 2019-05-14. Retrieved 2022-05-02.
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