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

AI-powered devices and services, such as virtual assistants and IoT items, continuously gather individual details, raising issues about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is more intensified by AI's capability to procedure and integrate vast quantities of information, potentially leading to a surveillance society where specific activities are constantly kept an eye on and examined without sufficient safeguards or openness.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For instance, in order to develop speech recognition algorithms, Amazon has taped millions of private conversations and permitted momentary workers to listen to and transcribe a few of them. [205] Opinions about this widespread security range from those who see it as a necessary evil to those for whom it is plainly dishonest and an infraction of the right to personal privacy. [206]
AI developers argue that this is the only method to deliver valuable applications and have developed numerous strategies that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have actually begun to view personal privacy in terms of fairness. Brian Christian wrote that experts have rotated "from the question of 'what they understand' 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