Artificial intelligence algorithms require large amounts of data. The techniques utilized to obtain this data have actually raised issues about personal privacy, monitoring and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, continuously collect personal details, raising concerns about intrusive data gathering and unapproved gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to process and combine huge quantities of data, potentially causing a monitoring society where specific activities are constantly kept track of and analyzed without sufficient safeguards or transparency.

Sensitive user data gathered might consist of online activity records, geolocation information, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has taped millions of private conversations and allowed short-term workers to listen to and transcribe a few of them. [205] Opinions about this extensive security range from those who see it as a needed evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI designers argue that this is the only way to deliver important applications and have established a number of methods that try to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian wrote that professionals have rotated "from the concern of 'what they understand' to the question 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