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<br>Artificial intelligence algorithms require big quantities of information. The methods used to obtain this data have raised concerns about personal privacy, surveillance and copyright.<br> |
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<br>[AI](http://work.diqian.com:3000)-powered gadgets and services, such as virtual assistants and IoT items, constantly collect individual details, raising issues about invasive data event and unapproved gain access to by third parties. The loss of privacy is further intensified by [AI](https://www.pkgovtjobz.site)'s capability to process and integrate large amounts of information, possibly causing a surveillance society where private activities are constantly kept track of and analyzed without adequate safeguards or openness.<br> |
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<br>Sensitive user data gathered might consist of online activity records, geolocation data, video, or audio. [204] For example, in order to build speech recognition algorithms, Amazon has taped countless private conversations and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this extensive monitoring 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 method to deliver valuable applications and have developed numerous methods that try to maintain privacy while still obtaining the data, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to see privacy in terms of fairness. Brian Christian composed that specialists have actually rotated "from the concern of 'what they understand' to the question of 'what they're making with it'." [208] |
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<br>Generative AI is frequently trained on unlicensed copyrighted works, including in domains such as images or computer code |
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