Digital Technologies: The Human Cost of Machine Learning
Context
Your company relies heavily on “ghost workers” to label the vast amounts of data that train your cutting-edge machine learning systems. These workers, often in vulnerable positions, report missed invoices, delayed payments, lack of support, and low wages, sometimes just above local minimums.
Dilemma
A) Maintain current outsourcing practices, keeping costs low and profits high.
B) Increase wages and improve conditions for data annotators, potentially impacting your bottom line.
Summary
Appen, an AI data service company, employs "ghost workers" globally to label data for AI training. These workers, often contractors, report issues like missed or delayed payments and poor communication. They perform tasks such as tagging images, transcribing audio, and categorizing text. Appen faces scrutiny over pay, with workers earning around minimum wage. The company claims it pays above location-based minimum wage. Workers also handle disturbing content, leading to psychological concerns. The work is described as essential but undervalued, with fears of job displacement as AI learns from their labor.
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| Last modified: | 10 June 2025 2.41 p.m. |