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

AI-powered gadgets and services, such as virtual assistants and IoT items, constantly collect individual details, raising concerns about intrusive information event and unapproved gain access to by 3rd celebrations. The loss of privacy is further worsened by AI's ability to procedure and combine large amounts of data, potentially resulting in a security society where private activities are constantly kept track of and examined without appropriate safeguards or openness.

Sensitive user data gathered may include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has tape-recorded countless private conversations and enabled short-term workers to listen to and transcribe some of them. [205] Opinions about this widespread security variety from those who see it as a required evil to those for whom it is plainly unethical and an offense of the right to personal privacy. [206]
AI designers argue that this is the only way to deliver important applications and have developed several techniques that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have started to view privacy in terms of fairness. Brian Christian wrote 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 often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code