Artificial intelligence algorithms require big quantities of data. The methods utilized to obtain this data have raised issues about personal privacy, monitoring and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, continuously collect individual details, raising issues about intrusive data gathering and unapproved gain access to by 3rd parties. The loss of personal privacy is more worsened by AI's capability to process and integrate vast amounts of information, potentially leading to a surveillance society where individual activities are continuously kept an eye on and examined without sufficient safeguards or openness.

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to develop speech recognition algorithms, Amazon has tape-recorded countless private conversations and enabled short-term workers to listen to and transcribe a few of them. [205] Opinions about this widespread monitoring range from those who see it as a required evil to those for whom it is plainly unethical and an offense of the right to privacy. [206]
AI developers argue that this is the only method to provide valuable applications and have actually developed numerous strategies that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian wrote that professionals have rotated "from the question of 'what they understand' to the concern of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code