Book review: Ghost Work

From the book jacket blurb:

Hidden beneath the surface of the internet, a new, stark reality is looming—one that cuts to the very heart of our endless debates about the impact of AI. 

Anthropologist Mary L. Gray and computer scientist Siddharth Suri team up to unveil how services delivered by companies like Amazon, Google, Microsoft, and Uber can only function smoothly thanks to the judgment and experience of a vast, invisible human labor force. 

These people doing "ghost work" make the internet seem smart. They perform high tech, on-demand piecework: flagging X-rated content, proofreading, transcribing audio, confirming identities, captioning video, and much more. An estimated 8 percent of Americans have worked at least once in this "ghost economy," and that number is growing.

I had some familiarity with the exploitative labor practices underpinning some of the technologies under the umbrella term “artificial intelligence”, so I expected to learn a lot more of the grim specifics in this book. I did, and having finished i, now my perception of many facets of the tech industry has been illuminated and expanded.

The section on the history of “ghost work” and invisible labor was surprisingly relevant to costume production/garment work, as the authors investigate in-depth the industrialization of the textile industry in the 18th & 19th centuries, as well as that industry’s reliance on the jobbed-out labor practice of piecework.

In the history section, they also draw a parrallel to the teams of “human computers” (mostly women and people of color), mathematicians who contributed invaluably to NASA and the lunar space-race but whose contributions have been obscured in the historical record.

I expected a certain level of focus on a dystopian hellscape of exploited workers in remote areas of the globe completing monotonous content moderation tasks for pennies through the platform of Mechanical Turk. And yes, that’s a chunk of the book, but the authors also profile positive ghostwork companies like Amara (a translation and subtitling company) and LeadGenius (an account-based marketing company).

Additionally, the book offers a healthy amount of hopeful suggestions of how to push back against the depersonalization and exploitation of ghost workers, and how humane scaffolding of ghostworking could positively reimagine the workforce of the future. In conclusion, the final chapter offers ten very feasible potential fixes.

In considering how I might approach the topic of AI with my students, I’ve been thinking about framing it in terms of the four macro-areas in which AI falls tragically and deeply short, ethically speaking:

1. Sustainability and environmental harm
2. Intrinsic bias and bigotry
3. Copyright and training data consent violation
4. Labor exploitation

Thinking this excellent book might be a contender for some of the reference material I ask them to read in advance of a discussion.