Why Science Should Stay Clear of Metaphysics
Peter Byrne, Nautilus, 2016/09/12

I read Bas C. van Fraassen's The Scientific Image (248 page PDF) not too long after it came out. I had been studying the positivists in depth and while the rejection of positivism (and consequent embrace of continentalism and existentialism) was all the rage, I found in van Fraassen the essence of what I considered the right response to the positivists (which did not involve rejecting empirism). van Fraassen's approach, called 'constructive empiricism', asserted  that "science is a large scale, human enterprise and we need boundaries to determine what we can say is true or not about the world around us. Empiricism is a stance, a pragmatic attitude that is self-constrained by what I call 'bridled irrationality.' That means that the data itself restricts what is rational to believe about the world; it creates a boundary." van Fraassen is one of the towering figures of 20th century philosophy, and this interview is well worth a read.

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The jobs of the future – and two skills you need to get them
Simon Torkington, World Economic Forum, 2016/09/12

"The World Economic Forum’s Future of Jobs study predicts that 5 million jobs will be lost before 2020 as artificial intelligence, robotics, nanotechnology and other socio-economic factors replace the need for human workers."  Keep in mind that the World Economic Forum have been champions of austerity over the years. According to this article, the two 'skills' needed are math skills and social skills. We read from David Deming, associate professor of education and economics at Harvard University, that educators should "complement their teaching of technical skills like mathematics and computer science, with a focus on making sure the workers of the future have the soft skills to compete in the new jobs market." But if we look at his chart (pictured) mathematical skills appear to be almost irrelevant, while the clear line of demarcation is the requirement for social skills. Keep in mind: computers do math. So if you do math, chances are than a computer can do your job.

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Evidence Rebuts Chomsky's Theory of Language Learning
Paul Ibbotson, Michael Tomasello, Scientific American, 2016/09/12

I've never supported Chomsky's theory of language learning. So to me, this is old and unsurprising news: "cognitive scientists and linguists have abandoned Chomsky’s 'universal grammar' theory in droves because of new research examining many different languages." The real mechanisms for language learning are network mechanisms. "Children use various types of thinking that may not be specific to language at all—such as the ability to classify the world into categories (people or objects, for instance) and to understand the relations among things." To my mind (and how I argued in papers like 'Conditional Variability' and 'Why Equi Fails') Chomsky's approach founders on the question of context. This is borne out in the new research. "The contributions from usage-based approaches have shifted the debate in the other direction to how much pragmatics can do for language before speakers need to turn to the rules of syntax."

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Why does deep and cheap learning work so well?
Henry W. Lin, Max Tegmark, arXiv, 2016/09/12

There's a good Technology Review summary of this article. In a nutshell: why do deep learning algorithms, which simulate neural networks, work so well? Mathematically, they should be much less effective, because they are attempting to select the best answer from an enormous number of possible outcomes. According to this paper, the reason is that the laws of physics are biased toward certain outcomes, and neural networks - which emulate physical processes - are biased in a similar manner. “We have shown that the success of deep and cheap learning depends not only on mathematics but also on physics, which favors certain classes of exceptionally simple probability distributions that deep learning is uniquely suited to model.” It's an important lesson: the universe may be described by mathematics, but it is not defined by mathematics.

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How Google And Others Are Plotting The Revenge Of The Web App
Jared Newman, Fast Company, 2016/09/12

I've messed around with web apps in the past and I've never really been interested in developing for the mobile app ecosystem. So I'm hopeful something comes of this. "Web apps represent an optimistic view of the world, in which users are free from walled garden app stores, and developers don't have to rebuild their software for a half-dozen platforms." That's not to say there aren't issues beyond the competitive edge mobile apps enjoy, and this article is lavish in its description of them. And it's not a short article. But the work behind "Progressive Web Apps" offers room for hope. "Building immersive apps using web technology no longer requires giving up the web itself," writes Alex Russell, a developer at Google. "Progressive Apps are our ticket out of the tab, if only we reach for it."

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