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

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect individual details, raising issues about invasive data gathering and unapproved gain access to by 3rd parties. The loss of privacy is further worsened by AI’s ability to procedure and combine vast quantities of data, potentially causing a surveillance society where private activities are continuously monitored and examined without adequate safeguards or transparency.

Sensitive user data collected might consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to develop speech recognition algorithms, Amazon has tape-recorded millions of personal discussions and enabled short-lived employees to listen to and transcribe some of them. [205] Opinions about this extensive surveillance range from those who see it as a needed 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 actually established several strategies that attempt to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have started to view personal privacy in terms of fairness. Brian Christian wrote that professionals have pivoted “from the question of ‘what they know’ to the concern 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 system code