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

AI-powered gadgets and services, such as virtual assistants and IoT items, continually gather individual details, raising concerns about invasive information gathering and unapproved gain access to by third parties. The loss of personal privacy is more intensified by AI's ability to process and combine huge amounts of data, potentially resulting in a surveillance society where private activities are continuously kept track of and evaluated without adequate safeguards or openness.

Sensitive user information gathered may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has tape-recorded millions of personal conversations and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring range from those who see it as a required evil to those for whom it is plainly dishonest and an offense of the right to personal privacy. [206]
AI developers argue that this is the only method to provide valuable applications and have established numerous techniques 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 experts, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian composed that experts have pivoted "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer code