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<br>Artificial intelligence algorithms require large amounts of data. The techniques utilized to obtain this information have raised concerns about privacy, security and copyright.<br> |
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<br>AI-powered gadgets and services, such as virtual assistants and IoT products, constantly collect individual details, raising issues about invasive data event and unauthorized gain access to by third parties. The loss of personal privacy is more intensified by AI's capability to process and combine large amounts of information, possibly leading to a surveillance society where private activities are continuously monitored and analyzed without adequate safeguards or openness.<br> |
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<br>Sensitive user data collected might include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech recognition algorithms, Amazon has taped countless private discussions and allowed short-lived employees to listen to and transcribe some of them. [205] Opinions about this prevalent surveillance range from those who see it as a required evil to those for whom it is plainly unethical and an offense of the right to privacy. [206] |
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<br>[AI](http://190.117.85.58:8095) developers argue that this is the only method to provide valuable applications and have actually developed a number of methods that attempt to maintain privacy while still obtaining the data, such as information aggregation, de-identification and differential personal privacy. [207] Since 2016, some personal privacy experts, such as Cynthia Dwork, have actually begun to see personal privacy in regards to fairness. Brian Christian wrote that specialists have pivoted "from the question of 'what they know' to the question of 'what they're finishing 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 system code |
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