Artificial intelligence algorithms need big amounts of information. The techniques utilized to obtain this information have raised issues about privacy, surveillance and copyright.

AI-powered gadgets and services, such as virtual assistants and IoT items, constantly collect individual details, raising concerns about intrusive data gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's ability to process and combine vast amounts of information, potentially causing a surveillance society where individual activities are continuously monitored and examined without sufficient safeguards or openness.

Sensitive user data collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has actually tape-recorded millions of private conversations and allowed short-term employees to listen to and transcribe some of them. [205] Opinions about this prevalent security variety from those who see it as a required evil to those for whom it is plainly dishonest and an offense of the right to privacy. [206]
AI designers argue that this is the only method to provide important applications and have established a number of techniques that attempt to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to view personal privacy in regards to fairness. Brian Christian composed that professionals have actually rotated "from the question of 'what they understand' to the question of 'what they're doing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code