AI Gets Profits from Catastrophe?

 Colonialism? No more than any kind of automation at any level.

How the A.I. industry profits from catastrophe

After COVID and economic collapse, low-paying algorithm-training jobs are becoming a way of life for many.    by Karen Hao  

This story is part two of MIT Technology Review’s series on AI colonialism, the idea that artificial intelligence is creating a new colonial world order. It was supported by the MIT Knight Science Journalism Fellowship Program and the Pulitzer Center. Read the full series here.

It was meant to be a temporary side job—a way to earn some extra money. Oskarina Fuentes Anaya signed up for Appen, an AI data-labeling platform, when she was still in college studying to land a well-paid position in the oil industry.

But then the economy tanked in Venezuela. Inflation skyrocketed, and a stable job, once guaranteed, was no longer an option. Her side gig was now full time; the temporary now the foreseeable future.

Today Fuentes lives in Colombia, one of millions of Venezuelan migrants and refugees who have left their country in search of better opportunities. But she’s trapped at home—both by a chronic illness that developed after delayed access to health care and by opaque algorithms that dictate when she works and how much she earns.

Despite threats from Appen to retaliate against her, she chose to go on the record as a named source. She wants people to understand what her life is like to be a critical part of the global AI development pipeline yet for the beneficiaries of her work to also mistreat her and make her invisible. She wants the people who do this work to be seen.

Appen is among dozens of companies that offer data-labeling services for the AI industry. If you’ve bought groceries on Instacart or looked up an employer on Glassdoor, you’ve benefited from such labeling behind the scenes. Most profit-maximizing algorithms, which underpin e-commerce sites, voice assistants, and self-driving cars, are based on deep learning, an AI technique that relies on scores of labeled examples to expand its capabilities. 

The insatiable demand has created a need for a broad base of cheap labor to manually tag videos, sort photos, and transcribe audio. The market value of sourcing and coordinating that “ghost work,” as it was memorably dubbed by anthropologist Mary Gray and computational social scientist Siddharth Suri, is projected to reach $13.7 billion by 2030. .... '