Artificial intelligence algorithms need large amounts of information. The methods used to obtain this information have actually raised issues about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather individual details, raising concerns about intrusive data event and unauthorized gain access to by 3rd parties. The loss of privacy is further intensified by AI's capability to process and integrate huge quantities of information, possibly resulting in a surveillance society where specific activities are constantly kept track of and examined without adequate safeguards or transparency.

Sensitive user information gathered might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech acknowledgment algorithms, Amazon has taped millions of private discussions and enabled momentary employees to listen to and transcribe some of them. [205] Opinions about this extensive security variety from those who see it as a needed evil to those for whom it is plainly dishonest and an infraction of the right to privacy. [206]
AI developers argue that this is the only way to provide important applications and have established a number of methods that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have started to see personal privacy in terms of fairness. Brian Christian composed that experts have actually pivoted "from the question of 'what they know' 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 code