Artificial intelligence algorithms need big amounts of data. The methods used to obtain this data have raised concerns about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously gather individual details, raising issues about invasive information event and unapproved gain access to by third parties. The loss of privacy is additional exacerbated by AI's capability to process and combine huge quantities of information, possibly leading to a surveillance society where individual activities are constantly kept track of and examined without adequate safeguards or transparency.

Sensitive user data gathered might include online activity records, geolocation information, video, or audio. [204] For instance, in order to develop speech acknowledgment algorithms, Amazon has tape-recorded countless personal discussions and allowed temporary workers to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring range from those who see it as a needed evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI developers argue that this is the only method to provide important applications and have developed numerous techniques that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and hb9lc.org differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have started to view privacy in terms of fairness. Brian Christian wrote that professionals have actually rotated "from the question of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code