Artificial intelligence algorithms require big quantities of information. The strategies used to obtain this information have raised concerns about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continuously gather individual details, raising concerns about intrusive data event and unapproved gain access to by 3rd parties. The loss of privacy is additional exacerbated by AI's ability to procedure and combine vast amounts of data, possibly leading to a monitoring society where specific activities are constantly kept an eye on and evaluated without adequate safeguards or openness.

Sensitive user information gathered may consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded countless private discussions and allowed short-lived employees to listen to and transcribe some of them. [205] Opinions about this widespread surveillance range from those who see it as an essential evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206]
AI designers argue that this is the only way to provide valuable applications and have established numerous methods that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to view personal privacy in regards to fairness. Brian Christian wrote that experts have pivoted "from the question of 'what they know' to the concern of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer code