Artificial intelligence algorithms need large quantities of information. The methods used to obtain this data have raised concerns about personal privacy, security and copyright.
AI-powered gadgets and services, such as virtual assistants and IoT products, continuously collect individual details, raising concerns about intrusive information event and unauthorized gain access to by 3rd parties. The loss of personal privacy is further intensified by AI's ability to process and combine vast quantities of information, potentially causing a security society where individual activities are constantly kept track of and examined without adequate safeguards or transparency.
Sensitive user information collected may include online activity records, geolocation information, video, or audio. [204] For example, in order to develop speech recognition algorithms, Amazon has recorded countless private conversations and allowed short-term employees to listen to and transcribe a few of them. [205] Opinions about this extensive monitoring variety from those who see it as a needed evil to those for whom it is plainly unethical and a violation of the right to personal privacy. [206]
AI designers argue that this is the only method to provide important applications and have established a number of methods that try to maintain personal privacy while still obtaining the information, such as information aggregation, de-identification and differential privacy. [207] Since 2016, some privacy professionals, such as Cynthia Dwork, have started to view personal privacy in regards to fairness. Brian Christian wrote that professionals have actually pivoted "from the concern of 'what they understand' to the question of 'what they're finishing with it'." [208]
Generative AI is typically trained on unlicensed copyrighted works, including in domains such as images or computer code
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AI Pioneers such as Yoshua Bengio
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