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

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect 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 ability to process and integrate large quantities of data, potentially leading to a security society where specific activities are continuously monitored and evaluated without sufficient safeguards or openness.

Sensitive user data gathered may consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has actually tape-recorded countless personal conversations and allowed short-lived workers to listen to and transcribe a few of them. [205] Opinions about this extensive surveillance variety from those who see it as a necessary evil to those for whom it is plainly dishonest and a violation of the right to privacy. [206]
AI designers argue that this is the only way to deliver important applications and have established several strategies that try to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have actually begun to see personal privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the concern of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code