Artificial intelligence algorithms require large quantities of data. The methods used to obtain this information have raised concerns about personal privacy, surveillance and copyright.

AI-powered devices and services, such as and IoT products, constantly gather personal details, raising issues about invasive data gathering and unauthorized gain access to by 3rd celebrations. The loss of privacy is additional worsened by AI's ability to procedure and integrate large amounts of data, possibly causing a surveillance society where private activities are continuously monitored and examined without sufficient safeguards or openness.

Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For instance, in order to develop speech acknowledgment algorithms, Amazon has taped millions of private conversations and allowed short-term employees to listen to and transcribe a few of them. [205] Opinions about this extensive security range from those who see it as a necessary 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 way to deliver valuable applications and have actually established numerous methods that attempt 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 experts, such as Cynthia Dwork, have begun to see privacy in terms of fairness. Brian Christian composed that experts have actually rotated "from the concern of 'what they know' to the concern of 'what they're finishing with it'." [208]
Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer system code