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<br>Artificial intelligence algorithms need large quantities of information. The methods used to obtain this information have raised concerns about personal privacy, surveillance and copyright.<br> |
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<br>[AI](https://git.skyviewfund.com)-powered gadgets and services, such as virtual assistants and IoT products, continually gather personal details, raising issues about invasive information gathering and unauthorized gain access to by 3rd parties. The loss of privacy is further exacerbated by AI's capability to process and combine vast amounts of information, potentially causing a surveillance society where individual activities are constantly monitored and examined without appropriate safeguards or openness.<br> |
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<br>Sensitive user data collected may include online activity records, geolocation information, video, or audio. [204] For instance, in order to build speech acknowledgment algorithms, Amazon has actually tape-recorded millions of personal conversations and permitted temporary employees to listen to and transcribe some of them. [205] Opinions about this extensive security 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 developers argue that this is the only way to deliver valuable applications and have actually established several methods that attempt to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have actually started to see personal privacy in regards to fairness. Brian Christian wrote that specialists have actually pivoted "from the question of 'what they understand' to the concern of 'what they're doing with it'." [208] |
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<br>Generative AI is often trained on unlicensed copyrighted works, including in domains such as images or computer code |
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