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

AI-powered gadgets and services, such as virtual assistants and IoT items, continually gather individual details, raising concerns about intrusive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to procedure and combine vast amounts of data, possibly resulting in a security society where individual activities are continuously kept track of and examined without sufficient safeguards or openness.

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has tape-recorded millions of private discussions and permitted short-term employees to listen to and transcribe some of them. [205] Opinions about this widespread surveillance variety from those who see it as a necessary evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206]
AI developers argue that this is the only way to deliver valuable applications and have actually developed several strategies 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 personal privacy professionals, such as Cynthia Dwork, have begun to view privacy in terms of fairness. Brian Christian wrote that specialists have actually pivoted "from the question of 'what they know' to the concern of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code