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

AI-powered gadgets and services, such as virtual assistants and IoT items, continuously collect individual details, raising issues about intrusive information event and unapproved gain access to by third parties. The loss of privacy is additional exacerbated by AI's capability to procedure and combine large quantities of data, potentially causing a monitoring society where specific activities are continuously monitored and analyzed without sufficient safeguards or transparency.

Sensitive user information gathered might include online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has tape-recorded millions of personal discussions and allowed short-term workers to listen to and transcribe some of them. [205] Opinions about this widespread 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 developers argue that this is the only way to deliver important applications and have developed a number of techniques that try 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 actually started to see privacy in terms of fairness. Brian Christian composed that specialists have rotated "from the question of 'what they understand' to the concern of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code