Platform-based talent markets help put the emphasis in human-capital management back where it belongs--on humans. The best way to organize corporations--it's a perennial debate. But the discussion is becoming more urgent as digital technology begins to penetrate the labor force. Although consumers have largely gone digital, the digitization of jobs, and of the tasks and activities within them, is still in the early stages, according to a recent study by McKinsey Global Institute (MGI). Even companies and industries at the forefront of digital spending and usage have yet to digitize the workforce fully (Exhibit 1).1 1.See McKinsey Global Institute, "Digital America: A tale of the haves and have-mores," December 2015. The stage is set for sweeping change as artificial intelligence, after years of hype and debate, brings workplace automation not just to physically intensive roles and repetitive routines but also to a wide range of other tasks. MGI estimates that roughly up to 45 percent of the activities employees perform can be automated by adapting currently demonstrated technologies.

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S. Somasegar is a venture partner at Madrona Venture Group and the former head of Microsoft's Developer Division. More posts by this contributor: Escaping the trough of disillusionment for virtual and augmented reality The intelligent app ecosystem (is more than just bots!) How to join the network Daniel Li is an investor with Madrona Venture Group. More posts by this contributor: The new paradigm for human-bot communication The intelligent app ecosystem (is more than just bots!) How to join the network You can hardly talk to a technology executive or developer today without talking about artificial intelligence, machine learning or bots. While everyone agrees on the importance of machine learning to their company and industry, few companies have adequate expertise to do what they wanted the technology to do. Here are some insights into what we can expect in the coming years around ML and AI.

Artificial intelligence (AI), deep learning, and neural networks represent incredibly exciting and powerful machine learning-based techniques used to solve many real-world problems. For a primer on machine learning, you may want to read this five-part series that I wrote. While human-like deductive reasoning, inference, and decision-making by a computer is still a long time away, there have been remarkable gains in the application of AI techniques and associated algorithms. The concepts discussed here are extremely technical, complex, and based on mathematics, statistics, probability theory, physics, signal processing, machine learning, computer science, psychology, linguistics, and neuroscience. That said, this article is not meant to provide such a technical treatment, but rather to explain these concepts at a level that can be understood by most non-practitioners, and can also serve as a reference or review for technical folks as well.

This week's top Machine Learning stories, including AI agents that both encrypt and explain themselves, and more! Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning!

I have just returned from the fourth annual Heidelberg Laureate Forum and I want to emphasize how very important it has been for ACM Turing laureates to participate in the program. Each year 200 math and computer science undergraduates participate in the program, approximately 100 each. Speeches by laureates are mixed with undergraduate workshops and plenary open sessions. There is ample opportunity for interaction among students and laureates and between students. This year, Brian Schmidt gave the Lindau lecture (from the annual Nobel Prize winners meeting).

No one likes being reduced to a number. For example, there is much more to my financial picture than my credit score alone. There is even scholarly work on weaknesses in the system to compute this score. Everyone may agree the number is far from perfect, yet it is used to make decisions that matter to me, as Moshe Y. Vardi discussed in his Editor's Letter "Academic Rankings Considered Harmful!" (Sept. So I care what my credit score is.

I had an interesting experience recently. I agreed to run a session on computer science for the STEP (Science and Technology Entry Program) students at Union College's Kenney Community Center. The range of students was large, from 7th to 12th grade. Usually in a session like this I start by asking two things. First, in what ways are computers already in their lives?

"Because they added some new modifications for teachers to better manage their class, and to be able to do things like coding and other things that teachers are interested in, it's just easier for teachers to adopt it," says Mimi Ito, research director of the Digital Media and Learning Hub at the University of California--Irvine. Ito also is a co-founder of Connected Camps, a for-profit online learning organization through which teenage coaches use "Minecraft" to teach younger children computer coding and Spanish.

How will AI shape the average North American city by 2030? A panel of experts assembled as part of a century-long study into the impact of AI thinks its effects will be profound. The One Hundred Year Study on Artificial Intelligence is the brainchild of Eric Horvitz, a computer scientist, former president of the Association for the Advancement of Artificial Intelligence, and managing director of Microsoft Research's main Redmond lab. Every five years a panel of experts will assess the current state of AI and its future directions. The first panel, comprised of experts in AI, law, political science, policy, and economics, was launched last fall and decided to frame their report around the impact AI will have on the average American city.