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<br>Artificial intelligence algorithms require big quantities of data. The strategies utilized to obtain this information have raised issues about personal privacy, security and copyright.<br> |
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<br>AI-powered devices and services, such as virtual assistants and IoT items, constantly gather personal details, raising concerns about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is more exacerbated by [AI](https://mcn-kw.com)'s ability to process and integrate vast quantities of data, possibly resulting in a surveillance society where specific activities are continuously monitored and analyzed without sufficient safeguards or transparency.<br> |
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<br>Sensitive user information gathered may consist of online activity records, geolocation data, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has taped countless personal discussions and allowed short-term employees to listen to and transcribe a few of them. [205] Opinions about this widespread security variety from those who see it as a required evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206] |
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<br>AI developers argue that this is the only way to provide valuable applications and have established a number of strategies that try to maintain personal privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy experts, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian composed that experts have actually rotated "from the concern of 'what they understand' to the concern of 'what they're doing with it'." [208] |
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<br>Generative [AI](https://projob.co.il) is frequently trained on unlicensed copyrighted works, including in domains such as images or computer system code |
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