Artificial intelligence algorithms need large quantities of data. The strategies utilized to obtain this data have raised concerns about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect personal details, raising issues about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is more intensified by AI’s ability to procedure and combine large quantities of data, potentially resulting in a monitoring society where specific activities are constantly kept an eye on and examined without appropriate safeguards or openness.

Sensitive user information gathered may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has tape-recorded millions of private conversations and enabled temporary workers to listen to and transcribe some of them. [205] Opinions about this widespread monitoring variety from those who see it as a necessary evil to those for whom it is plainly unethical and an infraction of the right to personal privacy. [206]
AI designers argue that this is the only way to provide important applications and have developed a number of methods that attempt to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that specialists have rotated “from the concern of ‘what they know’ to the concern of ‘what they’re doing with it’.” [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code