Artificial intelligence algorithms need big quantities of information. The methods used to obtain this information have actually raised issues about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal details, raising issues about intrusive information event and unapproved gain access to by 3rd parties. The loss of privacy is more exacerbated by AI's ability to procedure and combine huge amounts of information, possibly resulting in a monitoring society where specific activities are continuously kept track of and analyzed without appropriate safeguards or transparency.

Sensitive user information gathered may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has taped countless private discussions and enabled short-lived workers to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance 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 privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have developed several techniques that attempt to maintain privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to see personal privacy in terms of fairness. Brian Christian composed that experts have actually rotated "from the concern of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code