Artificial intelligence algorithms need large quantities of data. The methods utilized to obtain this data have raised concerns about personal privacy, security and copyright.

AI-powered devices and services, such as virtual assistants and IoT items, continually gather individual details, raising issues about invasive data event and unapproved gain access to by third parties. The loss of privacy is additional exacerbated by AI's capability to process and integrate large quantities of data, possibly causing a monitoring society where specific activities are continuously kept an eye on and examined without sufficient 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 tape-recorded countless private discussions and permitted temporary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent security variety from those who see it as an essential evil to those for whom it is plainly dishonest and an infraction of the right to personal privacy. [206]
AI designers argue that this is the only method to deliver valuable applications and have actually established a number of methods that try to maintain personal privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to see privacy in regards to 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 frequently trained on unlicensed copyrighted works, including in domains such as images or computer code