Artificial intelligence algorithms need big quantities of information. The methods used to obtain this information have raised concerns about privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually gather individual details, raising issues about intrusive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by AI's ability to process and integrate vast quantities of information, potentially causing a security society where individual activities are continuously monitored and examined without appropriate safeguards or openness.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has actually tape-recorded millions of private discussions and permitted temporary workers to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring variety from those who see it as a necessary evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI developers argue that this is the only way to deliver valuable applications and have actually established numerous methods that try 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 regards to fairness. Brian Christian composed that professionals have actually pivoted "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