Artificial intelligence algorithms need big quantities of information. The methods used to obtain this information have raised issues about privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect personal details, raising concerns about invasive data gathering and unauthorized gain access to by third parties. The loss of privacy is more worsened by AI's ability to process and combine vast amounts of data, potentially resulting in a security society where specific activities are continuously monitored and analyzed without adequate safeguards or transparency.

Sensitive user data gathered may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech acknowledgment algorithms, Amazon has tape-recorded countless private conversations and enabled short-term workers to listen to and transcribe some of them. [205] Opinions about this prevalent security 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 designers argue that this is the only way to deliver important applications and have actually established several techniques that attempt to maintain privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have begun to see personal privacy in terms of fairness. Brian Christian composed that professionals have actually pivoted "from the question of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer system code