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

AI-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising concerns about intrusive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is more intensified by AI's ability to process and combine huge quantities of information, possibly leading to a surveillance society where specific activities are continuously monitored and evaluated without sufficient safeguards or transparency.

Sensitive user information collected might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has actually tape-recorded countless personal discussions and permitted momentary workers to listen to and transcribe some of them. [205] Opinions about this extensive surveillance variety from those who see it as a necessary evil to those for whom it is plainly unethical and an infraction of the right to privacy. [206]
AI designers argue that this is the only method to provide important applications and have developed a number of techniques that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy professionals, 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 understand' to the concern of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code