Artificial intelligence algorithms need large amounts of information. The methods used to obtain this data have actually raised concerns about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal details, raising concerns about invasive information gathering and unapproved gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's ability to process and combine large amounts of data, possibly causing a security society where individual activities are constantly monitored and examined without adequate safeguards or openness.

Sensitive user data gathered may include online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has tape-recorded millions of private conversations and enabled short-lived workers to listen to and transcribe a few of them. [205] Opinions about this widespread surveillance range 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 designers argue that this is the only way to provide important applications and have actually established a number of methods that try to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have started to view personal privacy in regards to fairness. Brian Christian composed that professionals have pivoted "from the question of 'what they know' to the concern of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code