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

AI-powered devices and services, such as virtual assistants and IoT items, continually gather individual details, raising issues about intrusive information event and unauthorized gain access to by third parties. The loss of personal privacy is further exacerbated by AI's capability to procedure and combine large amounts of information, possibly resulting in a surveillance society where private activities are continuously monitored and examined without sufficient safeguards or transparency.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has actually tape-recorded millions of private conversations and enabled temporary 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 dishonest and an offense of the right to privacy. [206]
AI designers argue that this is the only method to deliver important applications and have developed a number of strategies 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 specialists, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that specialists have rotated "from the concern of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code