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

AI-powered devices and services, such as virtual assistants and IoT products, continuously gather individual details, raising concerns about intrusive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional worsened by AI's capability to process and combine large quantities of data, potentially leading to a monitoring society where private activities are continuously monitored and analyzed without sufficient safeguards or openness.

Sensitive user data gathered may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has recorded millions of personal discussions and enabled momentary employees to listen to and transcribe a few of them. [205] Opinions about this widespread monitoring range from those who see it as a needed evil to those for whom it is plainly unethical 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 developed a number of methods that attempt to maintain 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 actually begun to see personal privacy in terms of fairness. Brian Christian wrote that experts have actually pivoted "from the question of 'what they know' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code