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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 ...
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.
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 ...
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 ...
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.
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.
Artificial intelligence is being increasingly used by police forces, but critics are worried.
Some scholars have said that even if AGI poses an existential risk, attempting to ban research into artificial intelligence is still unwise, and probably futile. [ 166 ] [ 167 ] [ 168 ] Skeptics consider AI regulation pointless, as no existential risk exists.