Search results
Results from the WOW.Com Content Network
Focusing on evidence-based policy (i.e., real, thorough research on marginal risk) is particularly important because the litany of concerns with AI has been quite divorced from reality.
Deepfakes are the most concerning use of AI for crime and terrorism, according to a new report from University College London. Automated detection methods remain unreliable and deepfakes also ...
The Pan-Canadian Artificial Intelligence Strategy (2017) is supported by federal funding of Can $125 million with the objectives of increasing the number of outstanding AI researchers and skilled graduates in Canada, establishing nodes of scientific excellence at the three major AI centres, developing 'global thought leadership' on the economic ...
We should promote the diffusion of American AI to reinforce U.S. technology leadership and preempt China’s efforts to establish a Digital Silk Road for AI. At the same time, American AI ...
Predictive policing uses data on the times, locations and nature of past crimes, to provide insight to police strategists concerning where, and at what times, police patrols should patrol, or maintain a presence, in order to make the best use of resources or to have the greatest chance of deterring or preventing future crimes.
The AI Now Institute at NYU is a research institute studying the social implications of artificial intelligence. Its interdisciplinary research focuses on the themes bias and inclusion, labour and automation, rights and liberties, and safety and civil infrastructure.
Some worry the artificial intelligence technology could worsen issues like bias or prejudice that may be built into the systems. Police are adopting AI into crime report writing, but do the perks ...
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.