Artificial intelligence algorithms require large quantities of information. The techniques utilized to obtain this information have raised concerns about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather individual details, raising issues about intrusive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional exacerbated by AI's capability to process and integrate vast quantities of data, potentially leading to a surveillance society where individual activities are constantly kept an eye on and evaluated without sufficient safeguards or openness.

Sensitive user information collected might consist of online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has recorded countless 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 needed evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI designers argue that this is the only method to deliver important applications and have actually developed several techniques that try to maintain privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have begun to view privacy in terms of fairness. Brian Christian wrote that specialists have rotated "from the question of 'what they know' to the concern of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code