Artificial intelligence algorithms need large amounts of data. The methods used to obtain this information have actually raised concerns about personal privacy, monitoring and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, constantly gather personal details, raising issues about intrusive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more worsened by AI's capability to process and integrate huge quantities of information, potentially resulting in a security society where specific activities are constantly kept an eye on and examined without appropriate safeguards or openness.

Sensitive user information collected may include online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has taped millions of personal discussions and allowed momentary workers to listen to and transcribe a few of them. [205] Opinions about this extensive surveillance 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 privacy. [206]
AI developers argue that this is the only method to provide valuable applications and have developed numerous methods that try to maintain privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Dwork, have begun to view personal privacy in regards to fairness. Brian Christian wrote that professionals have actually pivoted "from the concern of 'what they know' to the question of 'what they're finishing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer system code