Artificial intelligence algorithms need big quantities of data. The techniques used to obtain this data have actually raised concerns about privacy, surveillance and copyright.

AI-powered gadgets and services, such as virtual and IoT products, continually gather individual details, raising concerns about intrusive information gathering and unapproved gain access to by 3rd parties. The loss of privacy is further exacerbated by AI's ability to procedure and integrate huge amounts of data, possibly causing a security society where specific activities are constantly kept track of and analyzed without adequate safeguards or transparency.

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has taped millions of private discussions and allowed short-lived employees to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring range from those who see it as an essential evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have actually established a number of techniques that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have started to view privacy in terms of fairness. Brian Christian wrote that specialists have rotated "from the question of 'what they know' to the concern of 'what they're finishing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer code