The rapid development of AI systems poses unprecedented risks, including loss of control, misuse, geopolitical instability, and concentration of power. To navigate these risks and avoid worst-case outcomes, governments may proactively establish the capability for a coordinated halt on dangerous AI development and deployment. In this paper, we outline key technical interventions that could allow for a coordinated halt on dangerous AI activities. We discuss how these interventions may contribute to restricting various dangerous AI activities, and show how these interventions can form the technical foundation for potential AI governance plans.

AI has finally settled into the mainstream. Successful proof-of-concepts have emerged in a number of industries, and there have been many examples of successful plant-floor deployments of AI. Some organizations have applied AI/ML projects across the enterprise to complete pipelines. This overall maturity is changing the way companies view the strategic value of AI and the areas in which they want its benefits to be realized. Let's look at 10 AI company strategy trends currently diagnosed by industry experts.

The first annual Day of AI on Friday, May 13 introduced artificial intelligence literacy to classrooms all over the world. An initiative of MIT Responsible AI for Social Empowerment and Education (RAISE), Day of AI is an opportunity for teachers to introduce K-12 students of all backgrounds to artificial intelligence (AI) and its role in their lives. With over 3,000 registrations from educators across 88 countries -- far exceeding the first-year goal of 1,000 registrations in the United States -- the initiative has clearly struck a chord with students and teachers who want to better understand the technology that's increasingly part of everyday life. In today's technology-driven world, kids are exposed to and interact with AI in ways they might not realize -- from search algorithms to smart devices, video recommendations to facial recognition. Day of AI aims to help educators and students develop AI literacy with an easy entry point, with free curricula and hands-on activities developed by MIT RAISE for grades 3-12.

Day of AI is May 13, 2022 when K-12 students across the country will engage in a series of freely available hands-on activities designed to introduce them to Artificial Intelligence (AI) and how it plays a part in their lives today. How did my phone recognize me?) All Day of AI activities are designed to be taught by educators with little or no technology background and to be accessible to students of all backgrounds and abilities, including those with little or no technology experience. The only requirements are an internet connection and a Chromebook or laptop. Day of AI activities are organized by age group and can be run in 30 minute to 1 hour time blocks.

Earlier this month, Brookings Metro published a data-driven snapshot of the growth and geography of the emerging artificial intelligence (AI) economy in the United States. Employing seven basic measures of AI research and commercial activity, the report benchmarked U.S. metropolitan areas on the basis of their core AI assets and capabilities as they stand now. Here, we look at the report's most important takeaways through five charts. The AI industry is growing rapidly, with AI-related projects accounting for a substantially larger share of federal research and development expenditures at U.S. colleges and universities. Similarly, newly founded firms that provide AI solutions of all tech startups expanded to more than 5%, from less than 1% a decade ago.

Last week, the Brookings Institution published an examination of the "extent, location, and concentration" of AI activity in 400 US metro areas, hailing it as the "next great'general purpose technology,'" with the power to spur economic growth. Key takeaways: Although it already feels like AI is everywhere, the tech is still in its early days--and in the US, AI development and commercialization is mega-concentrated in a handful of mostly coastal locales. But, but, but: Brookings also identified 13 other metro areas with "above-average involvement" in AI, including hubs you may have seen coming--New York, Boston, Seattle, Los Angeles, Washington, D.C., San Diego, Austin, Texas, and Raleigh, North Carolina--as well as smaller metro areas like Boulder, Colorado, Lincoln, Nebraska, Santa Cruz, California, Santa Maria-Santa Barbara, California, and Santa Fe, New Mexico. Zoom out: The above 15 metro areas account for two-thirds of AI activity nationwide--and for that matter, more than 50% of the areas Brookings looked at make up just 5% of AI activity, Wired reported.

Much of the U.S. artificial intelligence (AI) discussion revolves around futuristic dreams of both utopia and dystopia. However, it bears remembering that AI is also becoming a real-world economic fact with major implications for national and regional economic development as the U.S. crawls out of the COVID-19 pandemic. Based on advanced uses of statistics, algorithms, and fast computer processing, AI has become a focal point of U.S. innovation debates. Even more, AI is increasingly viewed as the next great "general purpose technology"--one that has the power to boost the productivity of sector after sector of the economy. All of which is why state and city leaders are increasingly assessing AI for its potential to spur economic growth.

A handful of superstar U.S. metro areas are leading the way in AI, while much of the rest of the country is at risk of being left behind. Why it matters: AI can enhance productivity and growth in multiple sectors, but as a technology that tends to centralize around a handful of talent hubs, it could also increase regional economic disparity across the country. What's happening: In a new report released today, researchers at the Brookings Institution assessed the geographic distribution of AI talent, investment and research around the U.S. The other side: More than half of the 261 U.S. metro areas surveyed by Brookings exhibit no significant AI activities at all. What they're saying: "AI is at the stage where it is highly dependent on a super-specific talent base, and there's also a heavy need for massive computing power," says Mark Muro, policy director at Brookings' Metropolitan Policy Program and a co-author of the report. What to watch: Muro notes that many of the AI early adopters benefited from federal investments in R&D that could potentially be spread more evenly around the country.

A new study warns that the American AI industry is highly concentrated in the San Francisco Bay Area and that this could prove to be a weakness in the long run. The Bay leads all other regions of the country in AI research and investment activity, accounting for about one-quarter of AI conference papers, patents, and companies in the US. Bay Area metro areas see levels of AI activity four times higher than other top cities for AI development. "When you have a high percentage of all AI activity in Bay Area metros, you may be overconcentrating, losing diversity, and getting groupthink in the algorithmic economy. It locks in a winner-take-most dimension to this sector, and that's where we hope that federal policy will begin to invest in new and different AI clusters in new and different places to provide a balance or counter," Mark Muro, policy director at the Brookings Institution and the study's coauthor, told WIRED.

Companies around the world are adapting to new ways of doing business, with automation and artificial intelligence playing an important role amid the ongoing pandemic. These insights from MIT Sloan Management Review can help ensure digital transformation initiatives are successful while also resilient in the face of new disruption. As enterprises consider what digital transformation will look like after the pandemic, MIT Sloan senior lecturerGeorge Westermanencourages business leaders to leave behind their pre-pandemic assumptions about innovation. Instead, he said in a recent webinar, lean into how COVID-19 forced enterprises to change for the better. The collective response to the pandemic challenged longstanding notions about the efficiency of remote work, the agility of corporate IT departments, the rigidity of government regulators, and the willingness of customers to embrace (and pay for) digital interactions.