Artificial intelligence algorithms require big amounts of information. The strategies utilized to obtain this information have raised issues about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising concerns about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is further exacerbated by AI's capability to procedure and combine vast quantities of information, potentially resulting in a surveillance society where individual activities are continuously 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 instance, in order to build speech recognition algorithms, Amazon has actually taped millions of private conversations and permitted short-term to listen to and transcribe some of them. [205] Opinions about this prevalent security range from those who see it as an essential evil to those for whom it is plainly unethical and an infraction of the right to privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have developed a number of techniques that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have begun to see personal privacy in terms of fairness. Brian Christian wrote that experts have rotated "from the concern of 'what they understand' to the question of 'what they're doing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code