Artificial intelligence algorithms require big amounts of data. The methods used to obtain this data have actually raised issues about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect individual details, raising issues about intrusive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional exacerbated by AI's capability to procedure and combine huge amounts of data, possibly leading to a security society where specific activities are constantly kept track of and examined without sufficient safeguards or transparency.

Sensitive user data gathered may include online activity records, geolocation information, video, or audio. [204] For instance, in order to construct speech recognition algorithms, Amazon has tape-recorded millions of personal discussions and enabled short-term employees to listen to and transcribe some of them. [205] Opinions about this extensive monitoring variety from those who see it as an essential evil to those for whom it is plainly unethical and a violation of the right to privacy. [206]
AI designers argue that this is the only way to provide valuable applications and have developed several techniques 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 started to see personal privacy in regards to fairness. Brian Christian wrote that specialists have actually rotated "from the question 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 code