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

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising issues about invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by AI's ability to procedure and integrate vast amounts of information, potentially resulting in a monitoring society where individual activities are constantly kept track of and evaluated without sufficient safeguards or transparency.

Sensitive user data gathered might consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has tape-recorded millions of private discussions and allowed momentary workers to listen to and transcribe some of them. [205] Opinions about this prevalent security 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 developers argue that this is the only method to provide valuable applications and have established a number of strategies that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have actually started to view privacy in terms of fairness. Brian Christian wrote that professionals have actually pivoted "from the question of 'what they know' 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