Artificial intelligence algorithms require big quantities of information. The techniques used to obtain this data have actually raised concerns about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather individual details, raising issues about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is more worsened by AI's ability to process and integrate huge amounts of information, possibly leading to a monitoring society where individual activities are continuously monitored and evaluated without sufficient safeguards or openness.

Sensitive user data collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has taped millions of private conversations and allowed short-term workers to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring range from those who see it as a required evil to those for whom it is plainly unethical and an infraction of the right to personal privacy. [206]
AI developers argue that this is the only way to deliver important applications and have developed a number of methods that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian composed that specialists have rotated "from the concern of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code