Scan barcode
workable123's review against another edition
5.0
A terrific book on a subject of growing importance. From the title you might expect that the book is a doomsday prediction about how automation will squeeze every last shred of dignity from the workplace. They certainly expand on the problems with ghost work, from not having a channel for feedback or complaints, increasing worker transaction costs, all without a safety net. But the authors offer a balanced and nuanced take, noting that we cannot discount the benefits of this type of system, which has the potential to reduce workplace discrimination, provide remuneration for those whose responsibilities prevent them from working during 9-5 hours, and proving a sense of accomplishment and community.
The historical perspective, from piecework to the 1990s Microsoft court case, was especially well told. The main criticisms are occasionally over-explaining APIs and being redundant with some of the story telling, but would recommend the read!
The historical perspective, from piecework to the 1990s Microsoft court case, was especially well told. The main criticisms are occasionally over-explaining APIs and being redundant with some of the story telling, but would recommend the read!
wilte's review
2.0
Important topic, but book could have been a blog post and felt repetitive (especially yet another paragraph introducing an Indian MTurker, his/her age, religion and some coleur locale; grew stale quite fast).
Piecework in an online environment (the human computation between augmented services). On-demand ghost work platforms and their APIs allow humans to power many of the websites, apps, online services, and algorithms most consumers think are automated.
The burden of transaction costs used to fall on companies, but now it falls squarely on the people doing ghost work.
Leading to Algorithmic cruelty
1 Requesters can upload large number of tasks, and then disappear (workers need to be hypervigilant, spun as flexibility)
2 The API governs interaction, no one to turn to for guidance or assistance (spun as autonomy)
3 platform decides on access and pay-outs, without appeal (supposedly against fraud; technical problems are also the workers’ problem; 30 percent of on-demand gig workers reported not getting paid for work they performed.
Ghost work also became more popular because of "just-in-time" scheduling, which remains common among larger retail and hospitality employers.
Building better work is both a social and a technical challenge
Some snippets:
We examined four different ghost work platforms: Amazon.com's Mechanical Turk (MTurk); Microsoft's internal Universal Human Relevance System (UHRS); the socially minded startup LeadGenius; and Amara.org, a nonprofit site dedicated to translating and captioning content
p54 Hatton argues that this "liability model," which treats workers as a drag on corporate profits, overtook the "asset model" of employment. It is possible that the asset model never made it out of the manufacturing sector after the pas sage of the Taft-Hartley Act in 1947. What is clear is that, by the time the internet was born, the U.S. was already moving quickly to a reliance on contract-driven services indefinitely staffed by contingent labor.
The transaction costs of ghost work don't melt away. Instead they are shifted to the shoulders of requesters and workers.
p143 the future of on-demand work, and the accountability and care for he conditions of those doing macro- or micro-task ghost work, is at a crossroads. One option is to hold companies that rely on software and a human labor pool to deliver a service to consumers legally accountable to that labor pool as their employers. Another option is for workers to continue to fend for themselves through the kindness of strangers and well-intentioned companies hiring them on contract. There might be other viable options that make ghost work a more sustainable form of employment. Finding our way to these other options that distribute the Elements of this new economy to workers, on-demand services, and consumers more equitably could come from considering how far intentional design focused on both profit and worker experience takes us, compared with the limits of narrowly focusing on a single bottom line.
Taken as a whole, the current "gig economy"- an ecosystem ecosystem of inde pendent contractors and small businesses driven by short-term projects that shift to meet market demands - is quietly moving to ghost work platforms. A growing number of people are picking up on-demand gig work online - accepting project-driven tasks, with companies that as sign, schedule, route, and bill work through websites or mobile app
Piecework in an online environment (the human computation between augmented services). On-demand ghost work platforms and their APIs allow humans to power many of the websites, apps, online services, and algorithms most consumers think are automated.
The burden of transaction costs used to fall on companies, but now it falls squarely on the people doing ghost work.
Leading to Algorithmic cruelty
1 Requesters can upload large number of tasks, and then disappear (workers need to be hypervigilant, spun as flexibility)
2 The API governs interaction, no one to turn to for guidance or assistance (spun as autonomy)
3 platform decides on access and pay-outs, without appeal (supposedly against fraud; technical problems are also the workers’ problem; 30 percent of on-demand gig workers reported not getting paid for work they performed.
Ghost work also became more popular because of "just-in-time" scheduling, which remains common among larger retail and hospitality employers.
Building better work is both a social and a technical challenge
Some snippets:
We examined four different ghost work platforms: Amazon.com's Mechanical Turk (MTurk); Microsoft's internal Universal Human Relevance System (UHRS); the socially minded startup LeadGenius; and Amara.org, a nonprofit site dedicated to translating and captioning content
p54 Hatton argues that this "liability model," which treats workers as a drag on corporate profits, overtook the "asset model" of employment. It is possible that the asset model never made it out of the manufacturing sector after the pas sage of the Taft-Hartley Act in 1947. What is clear is that, by the time the internet was born, the U.S. was already moving quickly to a reliance on contract-driven services indefinitely staffed by contingent labor.
The transaction costs of ghost work don't melt away. Instead they are shifted to the shoulders of requesters and workers.
p143 the future of on-demand work, and the accountability and care for he conditions of those doing macro- or micro-task ghost work, is at a crossroads. One option is to hold companies that rely on software and a human labor pool to deliver a service to consumers legally accountable to that labor pool as their employers. Another option is for workers to continue to fend for themselves through the kindness of strangers and well-intentioned companies hiring them on contract. There might be other viable options that make ghost work a more sustainable form of employment. Finding our way to these other options that distribute the Elements of this new economy to workers, on-demand services, and consumers more equitably could come from considering how far intentional design focused on both profit and worker experience takes us, compared with the limits of narrowly focusing on a single bottom line.
Taken as a whole, the current "gig economy"- an ecosystem ecosystem of inde pendent contractors and small businesses driven by short-term projects that shift to meet market demands - is quietly moving to ghost work platforms. A growing number of people are picking up on-demand gig work online - accepting project-driven tasks, with companies that as sign, schedule, route, and bill work through websites or mobile app
ialja's review
5.0
A well-researched analysis of people doing ghost work for big tech companies. As consumers (or even developers), we are often unaware or underappreciate the ghost work that powers our apps. Ghost work ranges from the human labor that goes into labeling training data for AI models, social media content moderation, search engine evaluation, identity verification, software testing, and countless other micro and macro tasks that are invisibly outsourced by today's fast-moving businesses. The book offers insight into the lives and motives of ghost workers, highlighting both the negative and positive effects of this type of work on diverse communities – the authors interviewed almost two hundred on-demand workers across the US and India.
In addition to building empathy for ghost workers, the authors' research provides a much-needed context for discussions on the future of work, especially as we move towards an on-demand economy. While some parts of the book are US-centric – for instance, the review of the history and legislative status of temp work – the research findings offer valuable insights that we should consider when designing or eventually regulating on-demand platforms.
Building upon their research, the authors recommend several practical technical and social fixes that would improve the working conditions and status of ghost work. Finally, they conclude the book with a call for a broader effort to recognize the value generated by invisible work that powers the apps we all use under the illusion of full automation.
In addition to building empathy for ghost workers, the authors' research provides a much-needed context for discussions on the future of work, especially as we move towards an on-demand economy. While some parts of the book are US-centric – for instance, the review of the history and legislative status of temp work – the research findings offer valuable insights that we should consider when designing or eventually regulating on-demand platforms.
Building upon their research, the authors recommend several practical technical and social fixes that would improve the working conditions and status of ghost work. Finally, they conclude the book with a call for a broader effort to recognize the value generated by invisible work that powers the apps we all use under the illusion of full automation.
More...