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Artificial Intelligence: Many Users Share Intimate Topics with AI Chatbots

Mental health, finances, relationships: Chatbots are often used for intimate topics - despite users having major concerns about the data protection of AI systems.

Translated from German Read in German

Artificial Intelligence: Many Users Share Intimate Topics with AI Chatbots

A growing number of German AI users are turning to chatbots with artificial intelligence for personal and sensitive issues, according to a survey conducted by Swiss software provider Proton. However, this shift in behavior is met with significant distrust from users regarding data privacy. The study found that 68% of German chatbot users have already discussed sensitive topics with AI systems.

Mental health inquiries are the most common, but users also disclose intimate aspects of their lives, including finances, partnerships, work, sexuality, secrets, and family conflicts. Despite the convenience and unbiased nature of AI, respondents expressed strong mistrust in how companies protect their confidential data. Around 40.5% of participants had little or no confidence that companies adequately safeguard sensitive information.

The primary concern is the commercial exploitation of data, with 51% of users fearing that individual marketing or advertising profiles could be created from their conversations. Additionally, 43% of participants worry about their statements being used to train new AI models. Stricter security guarantees could further increase user openness, with 71% of survey participants preferring a chatbot specifically designed with privacy in mind.

Around 44% also indicated a greater willingness to share intimate details if assured that the content would not be used for model training. Proton surveyed a total of 4,014 active users of AI chatbots in Germany, France, the United Kingdom, and the United States between July 22 and August 2, 2026.

Written by urgent.news from Handelsblatt's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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