Artificial intelligence algorithms require large amounts of data. The strategies used to obtain this information have raised issues about personal privacy, monitoring and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT products, continuously gather individual details, raising concerns about invasive data event and unapproved gain access to by 3rd parties. The loss of personal privacy is more exacerbated by AI's ability to process and combine large amounts of information, potentially resulting in a monitoring society where private activities are continuously kept an eye on and evaluated without adequate safeguards or transparency.

Sensitive user data gathered may include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has actually taped millions of private discussions and enabled short-lived workers to listen to and transcribe some of them. [205] Opinions about this extensive security range from those who see it as a necessary evil to those for whom it is plainly unethical and an offense of the right to personal privacy. [206]
AI developers argue that this is the only way to provide valuable applications and have developed a number of strategies that attempt to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have actually started to view personal privacy in terms of fairness. Brian Christian wrote that experts have pivoted "from the question of 'what they know' 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