Artificial intelligence algorithms need large quantities of data. The methods used to obtain this data have raised concerns about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continuously collect individual details, raising concerns about intrusive information event and unapproved gain access to by 3rd parties. The loss of personal privacy is more worsened by AI's ability to procedure and integrate vast quantities of data, possibly causing a surveillance society where private activities are constantly kept track of and analyzed without appropriate safeguards or transparency.

Sensitive user information collected might consist of online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has actually recorded millions of private discussions and permitted temporary workers to listen to and transcribe some of them. [205] Opinions about this extensive monitoring variety from those who see it as a necessary 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 way to provide important applications and have developed numerous methods that attempt to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that experts have pivoted "from the concern of 'what they understand' to the concern of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code