Artificial intelligence algorithms need large quantities of data. The techniques used 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 individual details, raising concerns about intrusive information event and unapproved gain access to by 3rd parties. The loss of privacy is more intensified by AI's capability to process and integrate large amounts of information, possibly resulting in a security society where individual activities are continuously monitored and examined without adequate safeguards or transparency.

Sensitive user information collected might include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has taped countless personal discussions and permitted temporary 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 offense of the right to personal privacy. [206]
AI developers argue that this is the only way to deliver valuable applications and have developed a number of strategies that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have actually begun to see privacy in terms of fairness. Brian Christian composed that professionals have actually rotated "from the concern of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer code