Artificial intelligence algorithms need large amounts of data. The techniques utilized to obtain this data have actually raised issues about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continuously gather individual details, raising concerns about intrusive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is more intensified by AI's capability to procedure and combine large amounts of data, potentially leading to a security society where individual activities are constantly kept an eye on and analyzed without appropriate safeguards or transparency.

Sensitive user data collected may include online activity records, geolocation data, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded countless private conversations and permitted momentary employees to listen to and transcribe a few of them. [205] Opinions about this widespread security range from those who see it as a required evil to those for whom it is plainly dishonest and an infraction of the right to personal privacy. [206]
AI designers argue that this is the only method to provide valuable applications and have established numerous techniques that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the question of 'what they know' to the question 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