Artificial intelligence algorithms need large quantities of information. The techniques used to obtain this information have raised issues about personal privacy, surveillance and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, continually gather individual details, raising issues about invasive data gathering and unapproved gain access to by 3rd parties. The loss of privacy is additional intensified by AI's capability to procedure and integrate large quantities of information, potentially resulting in a surveillance society where individual activities are continuously monitored and evaluated without adequate safeguards or openness.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has actually taped millions of personal conversations and permitted short-lived workers to listen to and transcribe some of them. [205] Opinions about this widespread security variety from those who see it as a necessary evil to those for whom it is plainly dishonest and an of the right to personal privacy. [206]
AI designers argue that this is the only method to provide important applications and have developed several methods that attempt to maintain personal privacy while still obtaining the information, such as data 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 wrote 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, consisting of in domains such as images or computer code