Artificial intelligence algorithms require big quantities of information. The strategies used to obtain this data have actually raised concerns about privacy, surveillance and copyright.

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising concerns about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is additional worsened by AI's capability to procedure and combine large amounts of information, potentially leading to a monitoring society where private activities are continuously monitored and analyzed without appropriate safeguards or openness.

Sensitive user information gathered may include online activity records, geolocation information, video, or audio. [204] For instance, in order to develop speech acknowledgment algorithms, Amazon has recorded millions of personal conversations and enabled momentary workers to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance range from those who see it as a needed evil to those for whom it is plainly unethical and an infraction of the right to privacy. [206]
AI developers argue that this is the only method to provide valuable applications and have actually established 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 specialists, such as Cynthia Dwork, have actually begun to see privacy in terms of fairness. Brian Christian wrote that specialists have 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, including in domains such as images or computer code