Artificial intelligence algorithms require large quantities of data. The strategies utilized to obtain this data have raised issues about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continually gather individual details, raising issues about invasive information gathering and unapproved gain access to by 3rd parties. The loss of privacy is more worsened by AI's ability to process and combine large quantities of information, potentially causing a security society where individual activities are constantly monitored and evaluated without sufficient safeguards or transparency.

Sensitive user data gathered might include online activity records, geolocation information, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has recorded countless personal conversations and enabled momentary employees to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance variety from those who see it as a required evil to those for whom it is plainly dishonest and an infraction of the right to personal privacy. [206]
AI developers argue that this is the only method to deliver important applications and have actually established a number of techniques that try to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian composed that specialists have rotated "from the question of 'what they understand' to the concern 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