Artificial intelligence algorithms require large amounts of information. The strategies 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 concerns about intrusive information gathering and unapproved gain access to by 3rd parties. The loss of privacy is further exacerbated by AI's capability to procedure and integrate vast quantities of data, potentially leading to a security society where individual activities are constantly monitored and analyzed without sufficient safeguards or openness.

Sensitive user data gathered may consist of 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 enabled momentary workers to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring variety from those who see it as a needed evil to those for whom it is plainly dishonest and an offense of the right to personal privacy. [206]
AI developers argue that this is the only method to deliver valuable applications and have developed a number of techniques that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have actually begun to view personal privacy in regards to fairness. Brian Christian composed that experts have actually rotated "from the concern of 'what they know' to the question of 'what they're doing with it'." [208]
Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code