Artificial intelligence algorithms need big amounts of information. The methods used to obtain this information have raised issues about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect individual details, raising issues about intrusive data event and unapproved gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to procedure and combine vast quantities of information, possibly resulting in a monitoring society where individual activities are continuously kept an eye on and analyzed without sufficient safeguards or openness.

Sensitive user information gathered may include online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has actually tape-recorded millions of personal conversations and enabled short-term employees to listen to and transcribe a few of them. [205] Opinions about this prevalent security range from those who see it as an essential 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 important applications and have actually established numerous methods that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have begun to see privacy in terms of fairness. Brian Christian wrote that professionals have pivoted "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code