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Companies are increasingly seeking innovative methods to gather data for their AI systems, but the use of public records poses significant risks. Public records are often biased and can lead to unfair outcomes, especially when used in AI training. Lawmakers need to act swiftly to prevent potential harm from these practices.
The article emphasizes the importance of regulating data collection and retention, particularly concerning personally identifiable information. With the rise of AI technologies, the potential for misuse of data increases, making it crucial for governments to limit their own data practices. The discussion highlights the need for transparency and accountability in AI systems to protect individual privacy.
• Public records can introduce biases in AI training data.
• Regulation of data collection is essential for protecting privacy.
The article discusses how AI systems rely on data, including public records, which can lead to biased outcomes.
The article stresses the need for regulations to safeguard personal data in AI applications.
The article highlights the risks associated with using public records for AI training, including potential biases and inaccuracies.
The article mentions AT&T in the context of data retention practices that can expose individuals to identity theft.
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