Artificial intelligence algorithms require big quantities of information. The methods utilized to obtain this data have raised issues about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather personal details, raising issues about intrusive data event and unauthorized gain access to by 3rd parties. The loss of privacy is further intensified by AI's ability to process and combine vast quantities of information, potentially leading to a security society where individual activities are constantly kept track of and evaluated without adequate safeguards or transparency.

Sensitive user information collected may include online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has taped millions of personal conversations and enabled temporary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent surveillance range from those who see it as a needed evil to those for whom it is plainly unethical and an offense of the right to privacy. [206]
AI designers argue that this is the only method to deliver important applications and have actually established numerous strategies that try to maintain privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have begun to see personal privacy in regards to fairness. Brian Christian composed that experts have pivoted "from the question of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code