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

AI-powered devices and services, such as virtual assistants and IoT items, continually gather individual details, raising concerns about intrusive information event and unapproved gain access to by third parties. The loss of privacy is additional worsened by AI's ability to process and combine huge amounts of data, potentially causing a security society where private activities are continuously kept track of and analyzed without sufficient safeguards or openness.

Sensitive user information collected might include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has tape-recorded countless personal conversations and allowed short-term employees to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance variety from those who see it as a required evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI developers argue that this is the only method to provide important applications and have actually developed a number of techniques that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have actually started to view privacy in terms of fairness. Brian Christian composed that specialists have rotated "from the concern of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code