Artificial intelligence algorithms need large amounts of data. The methods used to obtain this data have raised issues about privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect individual details, raising issues about intrusive information event and unauthorized gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to procedure and integrate large amounts of data, potentially resulting in a monitoring society where specific activities are constantly kept track of and examined without appropriate safeguards or transparency.

Sensitive user data gathered may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech acknowledgment algorithms, Amazon has taped millions of personal discussions and allowed temporary workers to listen to and transcribe some of them. [205] Opinions about this extensive surveillance variety from those who see it as a needed evil to those for whom it is plainly unethical and a violation of the right to privacy. [206]
AI designers argue that this is the only way to deliver important applications and have actually established several methods that attempt to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that professionals have actually pivoted "from the concern of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code