Artificial intelligence algorithms require large amounts of data. The techniques utilized to obtain this data have raised issues about privacy, security and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, constantly gather personal details, raising issues about intrusive information event and unapproved gain access to by third celebrations. The loss of privacy is additional intensified by AI's capability to process and integrate vast amounts of data, possibly causing a monitoring society where private activities are continuously kept track of and analyzed without adequate safeguards or openness.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has recorded countless private conversations and enabled momentary employees to listen to and transcribe a few of them. [205] Opinions about this extensive surveillance 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 established several strategies that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have started to view privacy in regards to fairness. Brian Christian wrote that experts have pivoted "from the question of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code