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Government officials' easier access to individuals' private data does present privacy and cybersecurity concerns. But that compounds the preexisting privacy problem of the government hoovering up ...
Dirty data infiltrates AI systems, compromising their integrity and increasing the risk of costly retraining. As digital privacy concerns grow, regulatory approaches have emerged to protect user data across various sectors. In the United States, privacy regulation has traditionally been sector-based, with different industries having their own ...
The companies committed to ensure AI products undergo both internal and external security testing before public release; to share information on the management of AI risks with the industry, governments, civil society, and academia; to prioritize cybersecurity and protect proprietary AI system components; to develop mechanisms to inform users ...
Some AI safety thinkers once argued that AI systems should first be developed in "air-gapped" systems, away from the internet, where they might potentially cause harm. Such suggestions seem ...
Concerns cited ranged from how AI is used in surveillance and in spreading fake content online (known as deep fakes when they include doctored video images and audio generated with help from AI) to cyberattacks, infringements on data privacy, hiring bias, autonomous vehicles, and drones that do not require a human controller. [72]
The mood on AI has shifted as the technology takes root, from one of concerns around safety to geopolitical competition, as countries jockey to nurture the next big AI giant.