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<br>Artificial intelligence algorithms require large quantities of data. The methods used to obtain this data have raised issues about personal privacy, surveillance and copyright.<br> |
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<br>AI-powered devices and services, such as virtual assistants and IoT products, continually collect personal details, raising concerns about invasive data event and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by [AI](http://175.24.174.173:3000)'s capability to procedure and combine vast quantities of data, potentially causing a security society where private activities are constantly monitored and analyzed without adequate safeguards or transparency.<br> |
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<br>Sensitive user information collected may include online activity records, geolocation information, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has taped millions of personal discussions and enabled temporary employees to listen to and transcribe some of them. [205] Opinions about this extensive monitoring range from those who see it as a necessary evil to those for whom it is plainly unethical and a violation of the right to privacy. [206] |
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<br>[AI](https://www.mafiscotek.com) developers argue that this is the only method to provide important applications and have established several strategies that attempt to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some personal privacy professionals, such as Cynthia Dwork, have started to view personal privacy in terms of fairness. Brian Christian composed that specialists have pivoted "from the question of 'what they understand' to the question of 'what they're making with it'." [208] |
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<br>Generative [AI](https://nukestuff.co.uk) is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code |
