Artificial intelligence algorithms require large amounts of data. The strategies used to obtain this data have raised issues about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather individual details, raising issues about intrusive data gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is more worsened by AI's capability to procedure and combine huge quantities of information, potentially leading to a security society where specific activities are constantly monitored and evaluated without adequate safeguards or transparency.

Sensitive user information collected may include online activity records, geolocation information, video, archmageriseswiki.com or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has taped countless personal conversations and allowed short-lived employees to listen to and transcribe some 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 unethical and a violation of the right to privacy. [206]
AI designers argue that this is the only way to provide valuable applications and have actually developed several strategies that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have started to see personal privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the concern of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code