Artificial intelligence algorithms require big quantities of data. The strategies utilized to obtain this data have raised concerns about personal privacy, surveillance and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT products, continually gather individual details, raising issues about invasive data event and unauthorized gain access to by third celebrations. The loss of personal privacy is further intensified by AI's capability to process and combine large amounts of information, potentially causing a security society where private activities are constantly kept an eye on and evaluated without appropriate safeguards or openness.

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has actually recorded countless private conversations and enabled short-lived workers to listen to and transcribe a few of them. [205] Opinions about this widespread monitoring variety from those who see it as a necessary evil to those for whom it is plainly dishonest and an infraction of the right to privacy. [206]
AI designers argue that this is the only way to deliver valuable applications and have established a number of techniques that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian wrote that professionals have rotated "from the concern of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer system code