Artificial intelligence algorithms require large amounts of information. The strategies utilized to obtain this data have raised issues about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continually collect individual details, raising issues about invasive data gathering and unapproved gain access to by 3rd celebrations. The loss of personal privacy is more intensified by AI's capability to process and integrate huge quantities of information, possibly causing a monitoring society where specific activities are constantly monitored and evaluated without sufficient safeguards or transparency.

Sensitive user information collected may consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has taped millions of private conversations and allowed temporary employees 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 an offense of the right to privacy. [206]
AI designers argue that this is the only way to provide important applications and have actually established several techniques that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to view privacy in regards to fairness. Brian Christian wrote that professionals have pivoted "from the question of 'what they know' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code