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

AI-powered devices and services, such as virtual assistants and IoT items, continually collect individual details, raising concerns about invasive data gathering and unapproved gain access to by third parties. The loss of privacy is more exacerbated by AI’s capability to process and integrate huge amounts of data, possibly resulting in a surveillance society where individual activities are constantly kept track of and evaluated without sufficient safeguards or transparency.

Sensitive user information collected may include online activity records, geolocation information, video, or audio. [204] For instance, in order to construct speech acknowledgment algorithms, Amazon has tape-recorded millions of personal conversations and permitted short-lived workers to listen to and transcribe a few of them. [205] Opinions about this widespread surveillance variety from those who see it as a required evil to those for whom it is plainly unethical and an offense of the right to personal privacy. [206]
AI designers argue that this is the only way to provide valuable applications and have established a number of strategies that attempt to maintain personal 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 started 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 finishing with it’.” [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code