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

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather personal details, raising issues about intrusive information event and unauthorized gain access to by third parties. The loss of personal privacy is further worsened by AI's capability to procedure and combine huge amounts of data, potentially leading to a security society where private activities are continuously monitored and analyzed without adequate safeguards or openness.

Sensitive user data collected may include online activity records, geolocation data, video, or audio. [204] For instance, in order to construct speech recognition algorithms, Amazon has taped countless private discussions and enabled momentary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent monitoring range from those who see it as a necessary evil to those for whom it is plainly dishonest and a violation of the right to privacy. [206]
AI designers argue that this is the only way to deliver important applications and have actually developed several techniques that try to maintain 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 started to see privacy in terms of fairness. Brian Christian wrote that specialists have rotated "from the question of 'what they know' to the concern 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