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

AI-powered gadgets and services, such as virtual assistants and IoT products, constantly collect individual details, raising concerns about invasive data event and unapproved gain access to by third celebrations. The loss of privacy is further intensified by AI's ability to process and integrate vast quantities of data, potentially causing a surveillance society where individual activities are continuously kept an eye on and examined without adequate safeguards or openness.

Sensitive user information gathered might consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has tape-recorded countless personal discussions and allowed momentary employees to listen to and transcribe some of them. [205] Opinions about this prevalent security variety 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 designers argue that this is the only method to deliver important applications and have developed a number of methods that attempt to maintain privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have started to view privacy in terms of fairness. Brian Christian wrote that experts have pivoted "from the concern 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 system code