[Malcolm's] first argument that makes no sense is, “should we want free to be the future?”

Who cares if we want it? It is.

The second argument that makes no sense is, “how will this new business model support the world as we know it today?”

Who cares if it does? It is. It’s happening. The world will change around it, because the world has no choice. I’m sorry if that’s inconvenient, but it’s true.

I must admit to agreeing with this analysis, and there is a message here for higher education. His later comments are even more relevant for those who work at universities that are trying their best to ignore the free / open revolution occurring around them:

Like all dying industries, the old perfect businesses will whine, criticize, demonize and most of all, lobby for relief. It won’t work. The big reason is simple:

In a world of free, everyone can play.

This is huge. When there are thousands of people writing about something, many will be willing to do it for free (like poets) and some of them might even be really good (like some poets). There is no poetry shortage.

Competition! Massive amounts of almost-no-barrier-to-entry competition. Much of it will be poor. I suppose you can take some comfort in that. But some of it will be very, very good. And that should scare existing institutions silly. The education game is about to change, and you (your institution) have three choices:

1. Innovate your way forward. If you allow your business model to become flexible and responsive, you can feel your way forward, influencing the emergent educational context as it simultaneously influences your business model. (A dynamic system!)

2. Wait for others to innovate their way forward. Let them shape the future educational context without your input, and hope that 10 years from now higher education is still a place where your institution is relevant. (If it isn’t, you’ll have only yourself to blame.)

3. Ignore / deny that anything is changing (or will ever change). Higher education is too important, too deeply woven into the fabric of society, too critical for employers, and too big a business to fail. (See you on the other side with GM and AIG.)

Chris’ book may or may not deal with higher education specifically, but higher education will have to deal with his thesis as surely as I’m typing this post. As Lehi taught, there are two types of things in this world – “things to act and things to be acted upon.” The day is close at hand when each university will have to decide which they are.

“All models are wrong, but some are useful.” So proclaimed statistician George Box 30 years ago, and he was right. But what choice did we have? Only models, from cosmological equations to theories of human behavior, seemed to be able to consistently, if imperfectly, explain the world around us. Until now. Today companies like Google, which have grown up in an era of massively abundant data, don’t have to settle for wrong models. Indeed, they don’t have to settle for models at all…

This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves…

Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). Instead, you must understand the underlying mechanisms that connect the two. Once you have a model, you can connect the data sets with confidence. Data without a model is just noise…

There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.

Let’s temporarily assume Chris is right, for the sake of argument. Could it be that educational research is finally on the brink of making an inch of forward progress? Do mediating educational technologies provide us with the opportunities to capture enough data that we could eventually do this “new kind of research?” Could access to this kind of data finally be the killer app for high technology in education?

Elsewhere in the article, Chris says,

Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough. No semantic or causal analysis is required.

Amazon, of course, doesn’t ever ask you to explicitly state your preferences for genres of book. Netflix doesn’t ask for explicit information about your taste in movies. And Google doesn’t need semantic analysis do determine which page is better than another. Is there a time coming when access to a sufficient quantity of educational activity and performance data will finally stomp out the petri dish of poorly informed opinion that is the vast majority of educational research? Would you care if I couldn’t classify your learning style or aptitude a la Cronbach and Snow or your intelligence type a la Gardner if I could consistently give you educational experiences that you found enjoyable and effective? I suspect not.