Artificial intelligence algorithms require big amounts of data. The techniques used to obtain this data have raised issues about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising issues about intrusive information gathering and unapproved gain access to by third parties. The loss of privacy is further exacerbated by AI's ability to procedure and integrate large quantities of information, potentially resulting in a surveillance society where private activities are constantly monitored and evaluated without appropriate safeguards or openness.

Sensitive user data gathered may include online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has recorded millions of personal discussions and allowed short-term workers to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance variety from those who see it as a necessary evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206]
AI developers argue that this is the only way to provide important applications and have developed a number of techniques that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have actually started to see personal privacy in terms of fairness. Brian Christian wrote that experts have pivoted "from the concern of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code