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

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising issues about intrusive information gathering and unapproved gain access to by third celebrations. The loss of privacy is further exacerbated by AI's ability to process and integrate huge quantities of information, possibly leading to a surveillance society where private activities are constantly kept track of and evaluated without adequate safeguards or transparency.

Sensitive user information collected might consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has recorded countless private conversations and enabled momentary workers to listen to and transcribe a few of them. [205] Opinions about this extensive 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 developers argue that this is the only method to deliver valuable applications and have established several strategies that try to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian wrote that specialists have actually rotated "from the concern of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code