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 devices and services, such as virtual assistants and IoT items, continuously collect personal details, raising concerns about invasive data gathering and unapproved gain access to by 3rd parties. The loss of personal privacy is additional intensified by AI's ability to procedure and combine large amounts of information, potentially resulting in a monitoring society where specific activities are continuously kept an eye on and evaluated without appropriate safeguards or transparency.

Sensitive user data collected might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech acknowledgment algorithms, Amazon has actually tape-recorded millions of personal discussions and permitted short-term employees to listen to and transcribe a few of them. [205] Opinions about this prevalent surveillance variety 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 developers argue that this is the only way to provide important applications and have developed numerous methods that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian composed that professionals have actually rotated "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code