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

AI-powered gadgets and services, such as virtual assistants and IoT products, constantly gather personal details, raising issues about invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by AI's capability to process and combine vast quantities of data, potentially resulting in a surveillance society where private activities are constantly kept track of and evaluated without adequate safeguards or transparency.

Sensitive user information gathered may include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has actually tape-recorded countless personal discussions and enabled short-term workers to listen to and transcribe a few of them. [205] Opinions about this prevalent monitoring 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 privacy. [206]
AI designers argue that this is the only way to deliver valuable applications and have actually established numerous methods that attempt to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have begun to see privacy in terms of fairness. Brian Christian composed that professionals have rotated "from the concern of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code