Artificial intelligence algorithms need big amounts of information. The techniques used to obtain this information have raised concerns about privacy, monitoring 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 ability to process and combine large quantities of information, potentially causing a surveillance society where private activities are continuously kept an eye on and examined without sufficient safeguards or openness.

Sensitive user data gathered might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has actually recorded millions of private conversations and permitted temporary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent 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 privacy. [206]
AI developers argue that this is the only method to deliver important applications and have developed a number of techniques that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that experts have pivoted "from the concern of 'what they know' to the concern 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 system code