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

AI-powered devices and services, such as virtual assistants and IoT products, constantly collect personal details, raising issues about intrusive data event and unauthorized gain access to by third parties. The loss of personal privacy is further worsened by AI's capability to process and combine huge amounts of data, possibly resulting in a monitoring society where private activities are continuously kept track of and analyzed without sufficient safeguards or openness.

Sensitive user information collected may consist of online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has taped countless private discussions and enabled momentary employees to listen to and transcribe a few of them. [205] Opinions about this widespread surveillance variety from those who see it as a needed evil to those for whom it is plainly unethical and an infraction of the right to privacy. [206]
AI developers argue that this is the only method to deliver valuable applications and have actually established several methods that attempt to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have actually begun to see personal privacy in terms of fairness. Brian Christian wrote that specialists have actually pivoted "from the concern of 'what they know' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code