Artificial intelligence algorithms need large amounts of data. The techniques used to obtain this data have raised concerns about personal privacy, monitoring and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, constantly collect personal details, raising concerns about invasive data gathering and unapproved gain access to by 3rd parties. The loss of personal privacy is further exacerbated by AI's capability to procedure and combine large quantities of information, possibly leading to a security society where specific activities are constantly kept an eye on and evaluated without sufficient safeguards or transparency.

Sensitive user data collected may consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has actually taped millions of private discussions and enabled momentary employees to listen to and transcribe some of them. [205] Opinions about this widespread surveillance 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 developers argue that this is the only method to deliver valuable applications and have actually developed numerous methods that try to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have started to view privacy in regards to fairness. Brian Christian composed that professionals have rotated "from the concern of 'what they understand' to the question 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 code