Artificial intelligence algorithms require large quantities of information. The techniques utilized to obtain this information have raised concerns about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather individual details, raising issues about intrusive data gathering and unapproved gain access to by third parties. The loss of privacy is additional worsened by AI's capability to process and combine huge quantities of data, possibly leading to a surveillance society where individual activities are continuously monitored and evaluated without appropriate safeguards or openness.

Sensitive user data collected may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has recorded countless private conversations 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 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 valuable applications and have developed several methods that try to maintain 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 view privacy in terms of fairness. Brian Christian composed that specialists have actually 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, including in domains such as images or computer system code