Artificial intelligence algorithms require large quantities of information. The techniques used to obtain this data have raised issues about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising issues about intrusive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more exacerbated by AI's capability to process and integrate huge quantities of data, possibly causing a surveillance society where individual activities are constantly kept track of and analyzed without adequate safeguards or openness.

Sensitive user information collected might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has tape-recorded millions of personal conversations and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this prevalent security range from those who see it as a required 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 method to provide valuable applications and have actually developed several methods that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, 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 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 code