Artificial intelligence algorithms need large amounts of data. The strategies used to obtain this data have raised issues about privacy, monitoring and copyright.
AI-powered devices and services, such as virtual assistants and IoT products, continuously gather personal details, raising concerns about intrusive information gathering and unauthorized gain access to by 3rd parties. The loss of personal privacy is further worsened by AI's ability to process and combine vast amounts of data, potentially causing a surveillance society where private activities are constantly kept track of and analyzed without sufficient safeguards or transparency.
Sensitive user data gathered may consist of online activity records, geolocation information, video, or audio. [204] For instance, in order to develop speech recognition algorithms, Amazon has actually taped millions of personal conversations and enabled momentary employees to listen to and transcribe a few of them. [205] Opinions about this prevalent surveillance range 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]
AI designers argue that this is the only way to provide valuable applications and have actually developed a number of strategies that try to maintain privacy while still obtaining the information, such as data aggregation, de-identification and differential personal privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have begun to view personal privacy in terms of fairness. Brian Christian wrote that professionals have pivoted "from the concern of 'what they understand' to the question of 'what they're making with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, consisting of in domains such as images or computer code
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AI Pioneers such as Yoshua Bengio
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