Artificial intelligence algorithms require big amounts of information. The methods used to obtain this data have raised concerns about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal details, raising concerns about intrusive information event and unauthorized gain access to by 3rd parties. The loss of privacy is additional intensified by AI's ability to process and integrate large quantities of information, possibly leading to a monitoring society where private activities are constantly monitored and examined without sufficient safeguards or transparency.

Sensitive user data gathered may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has taped millions of private discussions and enabled short-term employees to listen to and transcribe some of them. [205] Opinions about this extensive security range from those who see it as a necessary 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 method to deliver important applications and have developed numerous methods that attempt to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential 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 specialists have actually pivoted "from the concern of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code