Artificial intelligence algorithms need large quantities of information. The methods 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 items, continually collect individual details, raising issues about intrusive information gathering and unauthorized gain access to by third parties. The loss of privacy is more worsened by AI's capability to process and combine large quantities of data, potentially causing a surveillance society where specific activities are continuously monitored and evaluated without sufficient safeguards or openness.

Sensitive user data gathered might include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech acknowledgment algorithms, Amazon has actually recorded millions of personal conversations and enabled temporary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent security 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 way to provide valuable applications and have developed numerous strategies that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have actually begun to view privacy in terms of fairness. Brian Christian composed that experts have actually pivoted "from the question of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code