Artificial intelligence algorithms need large amounts of information. The methods 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 invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional intensified by AI's capability to procedure and combine vast amounts of information, possibly leading to a monitoring society where individual activities are constantly kept track of and examined without appropriate safeguards or openness.

Sensitive user information collected may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded millions of personal discussions and enabled short-lived workers to listen to and transcribe a few of them. [205] Opinions about this prevalent monitoring 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 developers argue that this is the only way to applications and have established numerous strategies that try to maintain privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to see privacy in regards to fairness. Brian Christian wrote that experts have pivoted "from the concern of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code