Artificial intelligence algorithms need large quantities of information. The methods used to obtain this data have raised concerns about privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather personal details, raising concerns about invasive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's ability to process and combine vast amounts of information, potentially resulting in a monitoring society where specific activities are continuously monitored and evaluated without sufficient safeguards or transparency.

Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech acknowledgment algorithms, Amazon has actually recorded millions of private discussions and allowed momentary employees to listen to and transcribe a few of them. [205] Opinions about this extensive surveillance variety from those who see it as a needed evil to those for whom it is plainly dishonest and an infraction of the right to privacy. [206]
AI developers argue that this is the only method to deliver important applications and have developed a number of methods that try to privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have actually started to see personal privacy in regards to fairness. Brian Christian wrote that specialists have actually pivoted "from the concern 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