Artificial intelligence algorithms require large amounts of information. The methods used to obtain this information have raised concerns about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continually collect individual details, raising issues about invasive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is further exacerbated by AI's capability to process and integrate large amounts of data, potentially resulting in a surveillance society where specific are constantly kept an eye on and examined 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 acknowledgment algorithms, Amazon has recorded countless private discussions and allowed momentary employees to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring variety from those who see it as an essential evil to those for whom it is plainly unethical and an offense of the right to personal privacy. [206]
AI designers argue that this is the only way to deliver important applications and have developed numerous strategies that attempt to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have actually started to view privacy in regards to fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they understand' to the concern of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code