Artificial intelligence algorithms require large quantities of information. The techniques used to obtain this information have raised issues about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising issues about intrusive data event and unapproved gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's capability to procedure and integrate large quantities of data, possibly causing a security society where specific activities are continuously kept an eye on and examined without appropriate safeguards or openness.

Sensitive user information gathered may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has tape-recorded millions of private conversations and allowed momentary workers to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance range from those who see it as a required evil to those for whom it is plainly unethical and an infraction of the right to privacy. [206]
AI designers argue that this is the only method to provide important applications and have developed several techniques that attempt to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have actually begun to see privacy in terms of fairness. Brian Christian composed that professionals have actually pivoted "from the question of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code