#DataLabelling

The Dark Knaikthedarkknaik
2026-01-06

Was Porcupine a Metaphor?

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The Dark Knaikthedarkknaik
2025-12-28

Nehma's Character Building

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The Dark Knaikthedarkknaik
2025-12-22

Captcha Test & the Nervousness

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The Dark Knaikthedarkknaik
2025-12-18

Dhuku in Jharkand

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The Dark Knaikthedarkknaik
2025-12-10

What is 'Humans in the Loop' About?

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The Dark Knaikthedarkknaik
2025-11-28

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The Dark Knaikthedarkknaik
2025-11-26

After the dhuku marriage ends, an indigenous woman finds a job and interacts with artificial intelligence.

Link: youtube.com/watch?v=k4LnB-OWgQQ

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The Dark Knaikthedarkknaik
2025-11-26

My latest blog is here: Humans in the Loop.
A Cinematic Warning We Cannot Ignore...

Read it on Substack πŸ‘‡
πŸ”— thedarkknaik.substack.com/p/fi

Miguel Afonso Caetanoremixtures@tldr.nettime.org
2025-10-04

"AI tools have become ubiquitous, entering many facets of everyday life. More often than not, β€œartificial intelligence” models are presented as fully automated, having dispensed with the need for human intervention. The human workers who train, test, and maintain AI models and act as the first line of defense against model failures are made visible only occasionally. Media coverage sometimes emerges of hundreds of Indian workers1 who remotely ensure the checkout process goes smoothly while creating the illusion of automation at Amazon Go stores and African content moderators2 who make social media platforms safer at great personal cost. But these stories only scratch the surface of the labor that underpins every part of the AI production process.

Despite being touted as the definitive technological breakthrough of this century, the conditions under which AI models and tools are produced by data workers, in a highly opaque and fissured global supply chain, are still underexplored. Studies of data workers in the Global South have begun to fill gaps in knowledge about the low-paid outsourced labor behind AI, but less is known about U.S. data workers’ conditions.

In this report, we begin to address this gap through a study of the working conditions of U.S.-based data workers, conducted by AWU-CWA and TechEquity.These workers are essential to the development of tools and models developed by big tech companies, but are employed by complex webs of contractors in the U.S.-based sections of the global AI supply chain. Combining data from a survey of 160 data workers with insights from 15 in-depth interviews, we’ve found that the poor working conditions seen in the Global South are also widespread in data work in the U.S."

cwa-union.org/ghost-workers-ai

#DataLabour #DataLabelling #DataAnnotation #BigTech #AI #GenerativeAI #WageSlavery

Miguel Afonso Caetanoremixtures@tldr.nettime.org
2024-07-04

#AI #GenerativeAI #GhostWork #DataLabelling #WageSlavery: "To build AI, Silicon Valley’s most illustrious companies are fighting over the limited talent of computer scientists in their backyard, paying hundreds of thousands of dollars to a newly minted Ph.D. But to train and deploy them using real-world data, these same companies have turned to the likes of Sama, and their veritable armies of low-wage workers with basic digital literacy, but no stable employment.

Sama isn’t the only service of its kind globally. Start-ups such as Scale AI, Appen, Hive Micro, iMerit and Mighty AI (now owned by Uber), and more traditional IT companies such as Accenture and Wipro are all part of this growing industry estimated to be worth $17bn by 2030.

Because of the sheer volume of data that AI companies need to be labelled, most start-ups outsource their services to lower-income countries where hundreds of workers like Ian and Benja are paid to sift and interpret data that trains AI systems."

lithub.com/how-vulnerable-low-

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