Artificial intelligence algorithms require big amounts of data. The techniques used to obtain this data have raised issues about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather individual details, raising concerns about intrusive information gathering and unapproved gain access to by third celebrations. The loss of personal privacy is further worsened by AI's capability to procedure and integrate vast amounts of data, possibly resulting in a security society where private activities are constantly kept an eye on and examined without adequate safeguards or openness.

Sensitive user data gathered might include online activity records, geolocation data, video, or audio. [204] For instance, in order to develop speech acknowledgment algorithms, Amazon has actually taped millions of private conversations and enabled short-term workers to listen to and transcribe a few of them. [205] Opinions about this extensive security range 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 developers argue that this is the only way to provide important applications and have established several methods that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have actually started to see privacy in regards to fairness. Brian Christian wrote that professionals have actually pivoted "from the concern of 'what they know' to the concern of 'what they're making with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer system code