Artificial intelligence algorithms require big quantities of information. The techniques used to obtain this data have raised issues about personal privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising issues about invasive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional worsened by AI's ability to process and integrate huge amounts of data, potentially leading to a security society where private activities are constantly kept an eye on and analyzed without appropriate safeguards or openness.

Sensitive user information collected might consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has actually taped millions of personal discussions and allowed temporary employees to listen to and transcribe a few of them. [205] Opinions about this widespread monitoring range from those who see it as a needed evil to those for whom it is plainly dishonest and a violation of the right to personal privacy. [206]
AI developers argue that this is the only way to deliver valuable applications and have actually developed several methods that try to maintain personal privacy while still obtaining the information, such as information 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 experts have pivoted "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code