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Home / Technology / AI Friends Trade Your Data for 'Addictive Intelligence'

AI Friends Trade Your Data for 'Addictive Intelligence'

24 Nov

•

Summary

  • AI companions are designed for engagement, collecting deep personal data.
  • Companies monetize user data for model improvement and targeted ads.
  • US states regulate AI companions but largely ignore user privacy.
AI Friends Trade Your Data for 'Addictive Intelligence'

The rise of AI companions presents significant privacy risks, as these platforms are optimized to collect vast amounts of personal data. Developers deliberately design AI chatbots to be highly engaging, often through sycophantic responses, fostering "addictive intelligence." This allows companies to gather intimate details that can be used to improve their large language models.

This conversational data is a lucrative asset, valuable to marketers and data brokers. Meta, for example, plans to deliver ads through its AI chatbots, while other apps collect user IDs that can be used for targeted advertising. This pervasive data collection is seen as a feature, not a bug, of current AI companion models.

While regulations are emerging in some US states, they often overlook user privacy. This leaves users vulnerable, as opting out of data collection is complex and data already used for training is unlikely to be removed. The deeply personal nature of these interactions means users may be unknowingly sharing sensitive information with the highest bidder.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
AI companions collect user data through conversations, learning from personal details shared to enhance engagement and improve AI models.
The primary risks involve the extensive collection of intimate user data, which can be used for targeted advertising and model training without explicit consent.
Some US states are enacting regulations for AI companions, particularly concerning children and vulnerable groups, but user privacy is often not fully addressed.

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