Unseen Labour and Exploitation in AI

• AI’s efficiency and accuracy are built on the invisible labour of low-paid workers in developing countries.

• Data annotators play a major role in training AI and Machine Learning (ML) models, which are trained in three steps: self-supervised learning, supervised learning, and reinforcement learning.

• Humans provide feedback on the output the AI produces for better responses and remove errors and jailbreaks.

• Data labelling work is outsourced by tech companies in Silicon Valley to workers in countries like Kenya, India, Pakistan, China, and the Philippines for low wages and long working hours.

• Non-experts are often employed for technical subjects that require prior knowledge, contributing to errors in the output produced by AI.

• AI features marketed as ‘fully automated’ are often underpinned by invisible human work.

• Exposure to sensitive and graphic content daily has been reported to cause severe mental health issues like post-traumatic stress disorder, anxiety, and depression in the workers.

• Voice actors and actors behind AI-generated audios and videos are required to film themselves dancing or singing for these machines to recognise human movements and sounds.

• AI tech workers from Kenya sent a letter to former U.S. President Joe Biden in 2024 about the poor working conditions they are subjected to.

• Most AI tech workers are unaware of the large tech company they are working for and are engaged in online gig work.

• The advancement of AI is powered by such “ghost workers,” and the lack of recognition and informalisation of their work helps tech companies perpetuate this system of labour exploitation.

AI Labour Exploitation is important topic for Civil service exam (WBCS).

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