Artificial intelligence algorithms need big amounts of data. The techniques used to obtain this data have raised issues about privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising concerns about invasive information event and unauthorized gain access to by third parties. The loss of personal privacy is further intensified by AI's ability to procedure and combine large quantities of information, potentially leading to a security society where individual activities are constantly kept track of and analyzed without sufficient safeguards or transparency.

Sensitive user data gathered may include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has taped millions of private conversations and enabled temporary employees to listen to and transcribe some of them. [205] Opinions about this widespread monitoring variety from those who see it as a necessary evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI designers argue that this is the only method to provide important applications and have established several methods that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to view personal privacy in terms of fairness. Brian Christian wrote that experts have rotated "from the concern of 'what they understand' to the concern of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code