Discover AI privacy risks when using ChatGPT and other chatbots. Learn what happens to conversations and how to use private AI alternatives.
How to Protect Your Privacy from ChatGPT and Other Chatbots
Do AI chatbots spook your privacy spidey sense? You’re not alone! Here’s how you can protect more of your privacy while using ChatGPT and other AI chatbots.
Top 4 AI chatbot privacy concerns and how to mitigate them | TechTa...
Explore four key chatbot privacy concerns, as well as privacy protection strategies for individual users and organizations hoping to safeguard user data.
Be Careful What You Tell Your AI Chatbot | Stanford HAI
A Stanford study reveals that leading AI companies are pulling user conversations for training, highlighting privacy risks and a need for clearer policies.
Privacy Considerations with AI Tools
Artificial intelligence (AI) tools come in all sorts of flavors. There are notetaking and transcription tools, chatbots, device-wide agentic AI features, grammar and writing tools, translation assistants, AI summaries, and research tools, among others. As a term, “AI” may refer to features in apps, apps themselves, third-party plug-ins, or a...
Using AI Chatbots: Privacy and Information Security Considerations
AI chatbots such as ChatGPT, Copilot, Gemini, and Claude can be powerful tools for learning, productivity, and creativity. However, it’s essential to be aware of privacy and information security risks when using these platforms in the context...
AI ruling prompts warnings from US lawyers: Your chats could be used against you
As people increasingly turn to artificial intelligence for advice, some U.S. lawyers are telling their clients not to treat AI chatbots like trusted confidants when their freedom or legal liability is on the line.
AI chatbots are becoming experts at changing people's minds. What's their secret?
ChatGPT and other AIs use a flood of facts, and the occasional lie, to persuade humans
Lumo: Privacy-first AI assistant where chats stay confidential
Meet Lumo, the zero-access encrypted AI assistant by Proton that does not track or record your conversations. Ask me anything — it's confidential
Lumo: Privacy-first AI assistant where chats stay confidential
Meet Lumo, the zero-access encrypted AI assistant by Proton that does not track or record your conversations. Ask me anything — it's confidential
AI chatbots are sycophants — researchers say it’s harming science
Nature asked researchers who use artificial intelligence how its propensity for people-pleasing affects their work — and what they are doing to mitigate it.
AI chatbots are sycophants — researchers say it’s harming science
Nature asked researchers who use artificial intelligence how its propensity for people-pleasing affects their work — and what they are doing to mitigate it.
AI chatbots are encouraging conspiracy theories – new research
If you interact with chatbots about conspiracy theories, research shows you can can easily fall down the rabbit hole.
AI chatbots are encouraging conspiracy theories – new research
If you interact with chatbots about conspiracy theories, research shows you can can easily fall down the rabbit hole.
User Privacy and Large Language Models: An Analysis of Frontier Developers' Privacy Policies
Hundreds of millions of people now regularly interact with large language models via chatbots. Model developers are eager to acquire new sources of high-quality training data as they race to improve model capabilities and win market share. This paper analyzes the privacy policies of six U.S. frontier AI developers to understand how they use their users' chats to train models. Drawing primarily on the California Consumer Privacy Act, we develop a novel qualitative coding schema that we apply to each developer's relevant privacy policies to compare data collection and use practices across the six companies. We find that all six developers appear to employ their users' chat data to train and improve their models by default, and that some retain this data indefinitely. Developers may collect and train on personal information disclosed in chats, including sensitive information such as biometric and health data, as well as files uploaded by users. Four of the six companies we examined appear to include children's chat data for model training, as well as customer data from other products. On the whole, developers' privacy policies often lack essential information about their practices, highlighting the need for greater transparency and accountability. We address the implications of users' lack of consent for the use of their chat data for model training, data security issues arising from indefinite chat data retention, and training on children's chat data. We conclude by providing recommendations to policymakers and developers to address the data privacy challenges posed by LLM-powered chatbots.
User Privacy and Large Language Models: An Analysis of Frontier Developers' Privacy Policies
Hundreds of millions of people now regularly interact with large language models via chatbots. Model developers are eager to acquire new sources of high-quality training data as they race to improve model capabilities and win market share. This paper analyzes the privacy policies of six U.S. frontier AI developers to understand how they use their users' chats to train models. Drawing primarily on the California Consumer Privacy Act, we develop a novel qualitative coding schema that we apply to each developer's relevant privacy policies to compare data collection and use practices across the six companies. We find that all six developers appear to employ their users' chat data to train and improve their models by default, and that some retain this data indefinitely. Developers may collect and train on personal information disclosed in chats, including sensitive information such as biometric and health data, as well as files uploaded by users. Four of the six companies we examined appear to include children's chat data for model training, as well as customer data from other products. On the whole, developers' privacy policies often lack essential information about their practices, highlighting the need for greater transparency and accountability. We address the implications of users' lack of consent for the use of their chat data for model training, data security issues arising from indefinite chat data retention, and training on children's chat data. We conclude by providing recommendations to policymakers and developers to address the data privacy challenges posed by LLM-powered chatbots.
Experts Caution Against Using AI Chatbots for Emotional Support
TC faculty break down the risks of using artificial intelligence for emotional support, and what a healthier AI future might look like
