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

AI-powered devices and services, such as virtual assistants and IoT items, continually collect individual details, raising concerns about intrusive data event and unauthorized gain access to by 3rd parties. The loss of privacy is more intensified by AI's ability to procedure and combine vast quantities of information, possibly resulting in a surveillance society where individual activities are continuously kept track of and examined without sufficient safeguards or transparency.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, pediascape.science Amazon has tape-recorded millions of private conversations and enabled short-lived workers to listen to and transcribe some of them. [205] Opinions about this widespread security variety from those who see it as an essential evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206]
AI developers argue that this is the only way to provide important applications and have established several strategies that attempt to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have begun to see privacy in regards to fairness. Brian Christian composed that professionals have pivoted "from the concern of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code