Feeding AI systems with material they create themselves raises concerns about data quality. AI systems may make mistakes, hallucinate, and show biases learned from internet data, leading to a reinforcement of errors when using AI-generated data to build new AI. This can result in systems getting trapped in cycles of worsening performance. The unique perfection of the human creative mind is deemed necessary for AI machines.
A Times investigation shows how the country’s biggest technology companies, as they raced to build powerful new artificial intelligence systems, bent and broke the rules from the start.
Cade Metz, a technology reporter for The Times, explains what he uncovered.
Guest: Cade Metz, a technology reporter for The New York Times.
Background reading:
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