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<br>Artificial intelligence algorithms require large amounts of information. The methods used to obtain this data have raised issues about privacy, security and copyright.<br> |
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<br>[AI](https://starleta.xyz)-powered devices and services, such as virtual assistants and IoT products, continually collect individual details, raising concerns about invasive data event and unapproved gain access to by 3rd parties. The loss of personal privacy is further worsened by AI's capability to process and integrate large quantities of data, possibly causing a monitoring society where specific activities are constantly monitored and evaluated without adequate safeguards or transparency.<br> |
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<br>Sensitive user information collected may include online activity records, geolocation data, video, or audio. [204] For example, in order to construct speech recognition algorithms, Amazon has taped countless personal discussions and allowed temporary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent security variety from those who see it as a necessary evil to those for whom it is plainly dishonest and an offense of the right to personal privacy. [206] |
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<br>[AI](https://kohentv.flixsterz.com) designers argue that this is the only way to provide valuable applications and have developed numerous 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 professionals, such as Cynthia Dwork, have started to view privacy in terms of fairness. Brian Christian wrote that professionals 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 often trained on unlicensed copyrighted works, consisting of in domains such as images or computer system code |
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