Many workers on platforms like Amazon Mechanical Turk are using AI language models like GPT-3 to perform their tasks. This use of AI-produced data for tasks that eventually feed machine learning models can lead to concerns like reduced output quality and increased bias.

Human Labor & AI Models:

• AI systems are largely dependent on human labor, with many corporations using platforms like Amazon Mechanical Turk.
• Workers on these platforms perform tasks such as data labeling and annotation, transcribing, and describing situations.
• This data is used to train AI models, allowing them to perform similar tasks on a larger scale.

Experiment by EPFL Researchers:

• Researchers at the École polytechnique fédérale de Lausanne (EPFL) in Switzerland conducted an experiment involving workers on Amazon Mechanical Turk.
• The workers were tasked with summarizing abstracts of medical research papers.
• It was found that a significant portion of the completed work appeared to be generated by AI models, possibly to increase efficiency and income.

Use of AI Detected Through Specific Methodology:

• The research team developed a methodology to detect if the work was human-generated or AI-generated.
• They created a classifier and used keystroke data to detect whether workers copied and pasted text from AI systems.
• The researchers were able to validate their results by cross-checking with the collected keystroke data.

The Drawbacks and Future of Using AI in Crowdsourced Work:

• Training AI models on data generated by other AI could result in a decrease in quality, more bias, and potential inaccuracies.
• Responses generated by AI systems are seen as bland and lacking the complexity and creativity of human-generated responses.
• Researchers suggest that as AI improves, the nature of crowdsourced work may change with the potential of AI replacing some workers.
• The possibility of collaboration between humans and AI models in generating responses is also suggested.

The Importance of Human Data:

• Human data is deemed as the gold standard as it is representative of humans, whom AI serves.
• The researchers emphasize that what they often aim to study from crowdsourced data are the imperfections of human responses.
• This could imply that measures might be implemented in future to prevent AI usage in such platforms and ensure human data acquisition.

Source (The Register)

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