Artificial intelligence algorithms require big quantities of information. The strategies utilized to obtain this information have raised issues about privacy, security and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT products, continuously collect personal details, raising concerns about invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more exacerbated by AI's ability to process and combine vast amounts of data, potentially leading to a security society where private activities are continuously monitored and analyzed without adequate safeguards or openness.

Sensitive user information collected may include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has tape-recorded countless private discussions and permitted momentary employees to listen to and transcribe a few of them. [205] Opinions about this widespread security variety from those who see it as an essential evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have established numerous strategies that try to maintain 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 begun to view personal privacy in terms of fairness. Brian Christian wrote that professionals have actually pivoted "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