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

AI-powered devices and services, such as virtual assistants and IoT items, continuously gather individual details, raising issues about invasive information gathering and unapproved gain access to by 3rd parties. The loss of privacy is further exacerbated by AI's ability to procedure and combine large quantities of information, potentially leading to a security society where individual activities are continuously monitored and analyzed without adequate safeguards or openness.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded millions of private conversations and permitted short-term employees to listen to and transcribe some of them. [205] Opinions about this extensive monitoring variety from those who see it as a required evil to those for whom it is plainly dishonest and an infraction of the right to privacy. [206]
AI designers argue that this is the only way to provide important applications and have actually established several methods that try to maintain privacy while still obtaining the information, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to view personal privacy in regards to fairness. Brian Christian wrote that professionals have actually pivoted "from the concern of 'what they know' to the question 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 system code