Artificial intelligence algorithms need large quantities of data. The techniques used to obtain this data have raised concerns about personal privacy, surveillance and setiathome.berkeley.edu copyright.

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

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has recorded millions of private discussions and enabled short-lived workers to listen to and transcribe some of them. [205] Opinions about this extensive surveillance variety from those who see it as a necessary evil to those for whom it is plainly dishonest and a violation of the right to privacy. [206]
AI developers argue that this is the only way to deliver important applications and have developed a number of methods that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have started to view privacy in regards to fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code