Artificial intelligence algorithms require big quantities of information. The techniques used to obtain this information have actually raised issues about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly collect personal details, raising issues about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is additional intensified by AI's capability to process and combine large quantities of information, possibly resulting in a security society where individual activities are continuously monitored and analyzed without adequate safeguards or transparency.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has taped millions of personal conversations and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this prevalent security variety from those who see it as a needed evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI designers argue that this is the only method to provide important applications and have established numerous strategies that attempt to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have begun to see privacy in terms of fairness. Brian Christian wrote that experts have actually rotated "from the concern of 'what they know' 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