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

AI-powered devices and services, such as virtual assistants and IoT items, continually collect individual details, raising concerns about invasive data gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional intensified by AI's ability to procedure and integrate large quantities of data, potentially leading to a surveillance society where private activities are constantly kept an eye on and analyzed without appropriate safeguards or transparency.

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