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

AI-powered gadgets and services, such as virtual assistants and IoT products, continually collect personal details, raising concerns about intrusive information event and unapproved gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's ability to process and combine vast quantities of information, potentially resulting in a security society where specific activities are constantly monitored and examined without adequate safeguards or transparency.

Sensitive user information collected may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has tape-recorded millions of personal conversations and permitted short-term employees to listen to and transcribe some of them. [205] Opinions about this prevalent security variety from those who see it as a required evil to those for whom it is plainly unethical and an infraction of the right to personal privacy. [206]
AI developers argue that this is the only way to provide valuable applications and have established numerous strategies that attempt to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to see privacy in regards to fairness. Brian Christian wrote that professionals have rotated "from the concern of 'what they know' to the question 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 system code