Artificial intelligence algorithms require large amounts of information. The techniques used to obtain this data have actually raised issues about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect personal details, raising issues about intrusive information event and unapproved gain access to by 3rd parties. The loss of privacy is more worsened by AI's ability to procedure and combine huge quantities of information, potentially causing a surveillance society where individual activities are continuously kept track of and examined without appropriate safeguards or transparency.

Sensitive user information gathered may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has taped countless personal conversations and permitted short-term employees to listen to and transcribe some of them. [205] Opinions about this extensive security variety from those who see it as a necessary evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI designers argue that this is the only way to deliver valuable applications and have established a number of strategies that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to view privacy in regards to fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code