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What are some claims by Malcolm Gladwell that are incorrect?

  • Thinks that “Igon Values” exist (he means “eigenvalue”, but he doesn’t know it) [2].
  • More generally, he tends to misuse and misdefine technical terms – e.g., “homology” [3], “sagittal plane” [4], and “power law” [5].
  • He has also famously discussed Paul Ekman and the science of being able to determine whether someone is lying by looking at snapshots of their face – this is a major part of the book Blink. Unfortunately, it all seems to be false [7].
  • That 10,000 hours of practice will turn you into a genius on the order of Mozart or Michael Jordan [8].
  • More generally, Gladwell’s methodology seems to be to oversimplify problems until he can wrap them up with a tidy, attractive-sounding, and pseudo-scientific explanation [9].
  • It’s also not true “that cognitive skills don’t predict a teacher’s effectiveness, that intelligence scores are poorly related to job performance or (the major claim in “Outliers”) that above a minimum I.Q. of 120, higher intelligence does not bring greater intellectual achievements.” [11]

Reforming math curriculum with computers

So next question we might ask: what is math? And by that I mean what do we mean when we say we’re teaching math or doing math? I reckon there are about four pieces to doing math: posing the right question. This is the one that is critically messed up in the outside world most of the time. You ask the wrong question and unsurprisingly, you tend to get the wrong answer. Then there’s this step of taking that real world—it might be real, real world, it might be the theoretical world—and moving it to a kind of math formulation, turning it into the mathematical form that has been so useful. Then there’s what I call step 3, which we’ll come back to, actually computing—taking that formulation and turning it into the answer in a math formulation, manipulating it to the point where you get the result. And then there’s, so to speak, transforming it back (step 4) from that mathematical form to real world and crucially verifying it. You might call that 4b.

Steps to doing math

Here’s the funny thing. We insist that the entire population learns how to do step 3 by hand. Perhaps 80% of doing math education at school is step 3 by hand and largely not doing steps 1, 2, and 4. And yet step 3 is the step that computers can do vastly better than any human at this point, so it’s kind of bizarre that that’s the way around we’re doing things. Instead, I think we should be using computers to do step 3 and we should be using students to do steps 1, 2, and 4 to a much greater extent than we are.

Here’s another argument that I hear: that if you use computers, it dumbs math down. This one is really frustrating. Somehow the idea has come about that, intrinsic to the use of computers, everything turns into mindless button pushing, intellectually all dumbed down. But if you do stuff by hand, it’s all very intellectual and brain training.

Do we really believe most students studying math right now think it’s anything other than fairly mindless? Most of the time what they’re actually doing is running through a bunch of calculating processes they don’t understand for reasons they don’t get. Mindless or not, at least those processes had real practical use 50–100 years ago—they were the only way of calculating. But now they don’t; almost nobody actually uses them anymore outside education.

So let’s be clear about one thing: the mindlessness base we’re starting from with hand-calculating math is pretty low right now. And, far from thinking computers will dumb math down, I actually think, correctly applied, they can do quite the opposite. I think computers are the greatest tool for conceptually understanding math. As I’ve said, they liberate you from calculating to think at a higher level.

But like all tools, they can be used completely mindlessly—for example making endless multimedia presentations. There was one I saw which aimed to use a computer to show people how to solve an equation by hand—all the steps you would take by hand. Now, maybe that’s good if you’re excited about learning that, but it seems to me that it’s completely backward for mainstream math. Why are we getting humans to learn with a computer how to solve an equation by hand that the computer should be solving anyway for them? They should be setting up the problem that the computer then solves, and working with the result.

Announcing an audacious proposal

My first programming job was at a company which was then called VA Software, working on a product called SourceForge. At that time, If you wanted to launch, manage, collaborate on and distribute an Open Source project, you used SourceForge. The problem was, SourceForge was an ad-ridden, user-hostile piece of crap. Getting anything done required several extraneous pageviews & clicks. The site was designed to squeeze every last advertising penny out of you. I can’t blame management for trying to generate more revenue…. two months into my job there, 25% of the company was laid off.

There was much public hand-wringing over the crappiness of the SourceForge user experience. There were two camps in these debates: those that wanted to build an open source, decentralized version of SourceForge (which someone did), and those that pointed out it was a free service, and how dare anyone complain about the user & developer-hostile aspects of the experience. Tolerating the bad behavior of SourceForge “is a necessary evil”, the apologists would say, “otherwise the service we all depend on might go away.” Does any of this sound familiar?

Years later a site called Github came out. It was good. They had no advertising, but charged money for certain features. They quickly became profitable because the service was so good and so important, people were willing to pay. Github has become a much-loved brand and service, and many would agree that it is a key piece of infrastructure in the technical renaissance we are currently experiencing. Github is apparently profitable, and it sounds like the people that work there spend their time trying to make the best service possible, as opposed to spending their time trying to extract additional pennies out of their users.

Wikipedia:Graphic Lab

The Graphics Lab helps improve all graphical content stored on Wikimedia Commons and the English Wikipedia.

Wikigraphists work to improve the quality of the images that have been proposed by the community. This involves work such as extracting key elements from photos, improving the color of images or emphasizing the main subject, ‘stitching’ multiple images together and often vectorizing images (converting to SVG). We also create new drawings, diagrams and maps when requests are made to do so.

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