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

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather individual details, raising issues about invasive information event and unauthorized gain access to by 3rd parties. The loss of privacy is more intensified by AI's ability to process and integrate huge quantities of data, potentially leading to a security society where individual activities are constantly kept an eye on and examined without sufficient safeguards or openness.

Sensitive user information gathered might include online activity records, geolocation information, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has actually taped countless personal discussions and permitted temporary employees 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 dishonest and an infraction of the right to privacy. [206]
AI designers argue that this is the only method to deliver important applications and have developed a number of methods that attempt to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have begun to view personal privacy in regards to fairness. Brian Christian composed that professionals have pivoted "from the concern of 'what they know' to the concern of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code