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

AI-powered gadgets and services, such as virtual assistants and IoT products, continuously gather individual details, raising concerns about intrusive data event and unapproved gain access to by 3rd parties. The loss of personal privacy is more exacerbated by AI's capability to process and integrate huge quantities of information, potentially leading to a monitoring society where private activities are constantly kept an eye on and evaluated without adequate safeguards or openness.

Sensitive user data collected may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has recorded countless private conversations and allowed temporary employees to listen to and transcribe a few of them. [205] Opinions about this extensive monitoring range from those who see it as a necessary 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 developed several techniques that try to maintain privacy while still obtaining the information, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian wrote that professionals have pivoted "from the question of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code