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

AI-powered devices and services, such as virtual assistants and IoT products, continuously collect personal details, raising issues about invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's capability to procedure and integrate vast amounts of data, potentially leading to a surveillance society where private activities are continuously kept an eye on and analyzed without sufficient safeguards or openness.

Sensitive user data collected 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 millions of private discussions and enabled temporary employees to listen to and transcribe some of them. [205] Opinions about this widespread security 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 privacy. [206]
AI developers argue that this is the only method to deliver valuable applications and have established numerous techniques that attempt to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the question 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