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<br>Artificial intelligence algorithms require large amounts of data. The strategies used to obtain this information have actually raised concerns about personal privacy, monitoring and copyright.<br> |
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<br>[AI](https://handsfarmers.fr)-powered gadgets and services, such as virtual assistants and IoT products, constantly gather personal details, raising issues about invasive information event and unapproved gain access to by 3rd parties. The loss of privacy is additional exacerbated by [AI](https://tubevieu.com)'s ability to process and combine large quantities of data, potentially leading to a monitoring society where specific activities are constantly monitored and evaluated without appropriate safeguards or transparency.<br> |
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<br>Sensitive user information gathered may include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has taped countless personal discussions and allowed momentary employees to listen to and transcribe a few of them. [205] Opinions about this widespread monitoring 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 privacy. [206] |
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<br>AI designers argue that this is the only method to deliver important applications and have actually established numerous techniques that try to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy specialists, such as Cynthia Dwork, have started to see personal privacy in terms of fairness. Brian Christian wrote that professionals have pivoted "from the question of 'what they know' to the question of 'what they're making with it'." [208] |
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<br>Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer system code |
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