Artificial intelligence algorithms require big amounts of information. The strategies used to obtain this data have raised concerns about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continuously gather personal details, raising concerns about invasive data event and unauthorized gain access to by 3rd parties. The loss of privacy is further worsened by AI's capability to process and combine large amounts of data, possibly leading to a security society where individual activities are continuously kept an eye on and evaluated without adequate safeguards or transparency.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has taped millions of personal conversations and permitted temporary workers to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance variety from those who see it as a necessary evil to those for garagesale.es whom it is plainly dishonest and an offense of the right to privacy. [206]
AI developers argue that this is the only method to deliver valuable applications and have established a number of strategies that try 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 actually begun to view privacy in terms of fairness. Brian Christian composed that experts have rotated "from the question of 'what they know' to the question of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code