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Artificial intelligence algorithms need large quantities of data. The methods used to obtain this data have raised concerns about privacy, monitoring and copyright.
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AI-powered devices and services, such as virtual assistants and IoT products, constantly gather individual details, raising concerns about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by [AI](https://git.andert.me)'s ability to process and integrate huge amounts of information, potentially leading to a security society where private activities are continuously kept an eye on and analyzed without appropriate safeguards or openness.
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Sensitive user information collected might include online activity records, geolocation data, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has tape-recorded millions of private discussions and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this prevalent monitoring 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 privacy. [206] +
[AI](https://nailrada.com) designers argue that this is the only way to provide important applications and have established several strategies that try to maintain personal privacy while still obtaining the data, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy specialists, such as Cynthia Dwork, have started to view personal privacy in terms of fairness. Brian Christian wrote that specialists have pivoted "from the concern of 'what they understand' to the question 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 code \ No newline at end of file