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

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather individual details, raising concerns about intrusive data gathering and unauthorized gain access to by 3rd parties. The loss of privacy is additional intensified by AI's capability to process and combine large quantities of information, possibly resulting in a surveillance society where individual activities are continuously kept track of and analyzed without adequate safeguards or transparency.

Sensitive user information collected may consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has actually taped countless private conversations and enabled short-term workers to listen to and transcribe some of them. [205] Opinions about this extensive security variety from those who see it as a required evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI developers argue that this is the only method to provide valuable applications and have developed a number of strategies that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have started to view personal privacy in terms of fairness. Brian Christian wrote that specialists have 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, consisting of in domains such as images or computer code