Artificial intelligence algorithms need large amounts of data. The techniques used to obtain this information have raised issues about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continuously gather individual details, raising issues about intrusive data gathering and unauthorized gain access to by 3rd parties. The loss of privacy is further worsened by AI's ability to process and integrate vast quantities of data, possibly resulting in a surveillance society where individual activities are constantly kept an eye on and analyzed without sufficient safeguards or openness.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has recorded millions of personal conversations and permitted 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 required evil to those for whom it is plainly unethical and an infraction of the right to personal privacy. [206]
AI designers argue that this is the only method to provide valuable applications and have developed a number of techniques that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have actually started to see privacy in terms of fairness. Brian Christian composed that professionals have actually rotated "from the concern of 'what they know' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code