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

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect individual details, raising concerns about invasive data event and unapproved gain access to by third celebrations. The loss of privacy is additional exacerbated by AI's capability to procedure and integrate large quantities of information, potentially resulting in a surveillance society where specific activities are constantly monitored and examined without appropriate safeguards or openness.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded millions of private discussions and enabled short-term workers to listen to and transcribe a few of them. [205] Opinions about this extensive security variety from those who see it as a needed 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 way to provide important applications and have developed numerous strategies that try to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to see personal privacy in terms of fairness. Brian Christian wrote that specialists have pivoted "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, pediascape.science consisting of in domains such as images or computer system code