Artificial intelligence algorithms need big amounts of data. The strategies utilized to obtain this information have raised concerns about privacy, surveillance and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT products, constantly collect personal details, raising concerns about invasive data gathering and unapproved gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to procedure and combine large quantities of data, possibly resulting in a surveillance society where specific activities are constantly kept an eye on and examined without sufficient safeguards or transparency.

Sensitive user data collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has taped millions of personal conversations and permitted short-lived workers to listen to and transcribe some of them. [205] Opinions about this widespread security range from those who see it as a necessary evil to those for whom it is plainly unethical and an offense of the right to privacy. [206]
AI designers argue that this is the only way to deliver important applications and have actually developed several methods that attempt to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have begun to see personal privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the concern of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer system code