Artificial intelligence algorithms require large quantities of information. The methods utilized to obtain this data have raised concerns about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising issues about invasive data gathering and unapproved gain access to by 3rd parties. The loss of privacy is additional worsened by AI's ability to process and combine large amounts of information, potentially resulting in a monitoring society where individual activities are constantly kept track of and analyzed without appropriate safeguards or transparency.

Sensitive user data gathered might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has actually recorded millions of private discussions and enabled temporary employees to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring variety from those who see it as a necessary evil to those for whom it is plainly unethical and an infraction of the right to personal privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have developed several methods that attempt to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to view privacy in terms of fairness. Brian Christian composed that experts have rotated "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