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

AI-powered devices and services, such as virtual assistants and IoT items, constantly gather personal details, raising issues about invasive information event and unapproved gain access to by 3rd parties. The loss of privacy is additional intensified by AI's capability to process and combine large quantities of data, potentially causing a security society where individual activities are constantly monitored and evaluated without adequate safeguards or openness.

Sensitive user information collected might consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to develop speech recognition algorithms, Amazon has taped countless private conversations and allowed momentary workers to listen to and transcribe a few of them. [205] Opinions about this widespread security variety from those who see it as an essential evil to those for whom it is plainly dishonest and an infraction of the right to personal privacy. [206]
AI developers argue that this is the only way to provide valuable applications and have developed a number of methods that attempt to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have actually started to see privacy in terms of fairness. Brian Christian composed that experts have actually pivoted "from the question of 'what they know' to the question 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 system code