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A 20-Year Community Roadmap for Artificial Intelligence Research in the US

arXiv.org Artificial Intelligence

Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.


Thinking Machines – Jason Allen Ashlock – Medium

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Like a film critic asked if the Oscars got it right this year, one has to feel a sense of standing too close to the frame, the field of vision too narrow to provide the context necessary for proper judgment. After spending an afternoon among the various installations that comprise "Thinking Machines: Art and Design in the Computer Age: 1959–1989," I wonder if this anxiety applied to the team tasked with creating this exhibit. In this case, I think not. Here, closeness to the frame is a virtue, not a vice.


Ex Machina, Artificial Intelligence, and the Ethical Dangers--or Benefits?--of New Technology

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"If you've created a conscious machine," says Caleb to Nathan toward the beginning of Ex Machina, when Caleb discovers Nathan is on the verge of creating an artificial intelligence indistinguishable from human intelligence, "it's not the history of man. Ex Machina, written and directed by Alex Garland, is an intriguing film about the wonders and dangers of artificial intelligence (AI). Garland's tale is stylishly told, beautifully photographed, and aided by a clever script that subverts standard cinematic clichés. It is also suffused with religious themes and theological motifs--unsurprisingly, because ever since Mary Shelley's Frankenstein, the prospect of human beings creating human-like beings of their own has almost invariably raised the issue of "playing God." In Ex Machina, Caleb is a computer coder brought to Nathan's secret research facility to apply the Turing Test to Nathan's AI--that is, to test whether a human interacting with the robot would be able to tell that the AI is non-human.


AI leaders: Machines will quickly outsmart us when they achieve human-level intelligence

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Oxford philosopher and author Nick Bostrom (left) and DeepMind CEO Demis Hassabis (right). Machines will quickly become significantly smarter than humans when they achieve human level intelligence, according to a high-profile panel of artificial intelligence (AI) leaders. A YouTube video released by the Future of Humanity Institute this week shows Elon Musk, the billionaire cofounder of Tesla, SpaceX and PayPal, talking on a panel earlier this month alongside the likes of DeepMind CEO Demis Hassabis, who sold his company to Google for £400 million in 2014, and Oxford philosopher Nick Bostrom. "Once we get to human level-AI, how long before we get to where things start taking off?" asked MIT professor and panel moderator Max Tegmark, citing an "intelligence explosion." Tegmark added: "Some people say days or hours.