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

AI-powered gadgets and services, such as virtual assistants and IoT products, constantly collect individual details, raising issues about intrusive information gathering and unapproved gain access to by 3rd parties. The loss of personal privacy is further exacerbated by AI's ability to process and integrate large amounts of information, possibly leading to a security society where specific activities are constantly kept track of and evaluated without appropriate 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 recognition algorithms, Amazon has taped countless private discussions and allowed short-lived employees to listen to and transcribe a few of them. [205] Opinions about this widespread security 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 deliver valuable applications and have developed 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 privacy specialists, such as Cynthia Dwork, have actually begun to view personal privacy in terms of fairness. Brian Christian wrote that specialists have pivoted "from the question of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code