Why America has more education and less to show for it than ever before
I hope you made the time to read Wufnik’s post from Friday. Entitled “Surrounded by people ‘educated far beyond their capacity to undertake analytical thought,’” his analysis of our culture’s “active willingness to be deceived” represents one of the iconic moments in S&R’s history. If you didn’t see it yet, go read it now.
In addition to the questions the post explicitly addresses, it also raises other critical issues that deserve equally rigorous treatment. One point for further consideration, for instance, lies in his use of the word “educated.” I don’t think it’s terribly controversial to suggest that our society is, by a variety of metrics, more educated than perhaps any society in history. Those metrics would include factors like “number of people who attended college.” At the same time, we are significantly less educated if we pay more attention to factors like the much harder to quantify “capacity for critical thought.” If I had to render the dynamic I have seen as a businessman, scholar, educator, culturalist and social commentator into some sort of formula, it would emphasize the curious decline in the correlation between education and outcome over the past generation or two. Somehow or another, we have more people going to school longer and the net social impact is less intelligence per dollar spent.
Theories as to why are easy to come by. Most are way too surface and tactical to help us understand root causes, though. For me, the political-economic rationale has always been the most helpful: those who are empowered to make a nation’s decisions craft institutions that serve their long-term interests. Duh. A right/center corporate hegemony benefits when it has an ample pool of labor that it can set to the task of making money for it while at the same time assuring the continuity of the political and economic order. Ideally, this means they believe passionately in the goodness and rightness of their system, and at a minimum they’re not boat-rockers.
In other words, if you hand me the task of designing an ed system, the result is going to reflect my values and benefit my worldview. Some have heard me talk about this and accused me of concocting conspiracy theories, which is silly. The basic argument I’m making is consistent with everything from Althusser (a Marxist) to Adam Smith (very much not a Marxist) and is, in essence, perfectly aligned with free market thinking. Each agent acts in his or her perceived best interest, right?
In a context where powerful business interests come to wield an increasingly large amount of power over government decision making – with Exhibit A being the contemporary United States – it’s only logical to expect that institutions like schools will evolve so as to serve the goals of those business interests.
With this in mind, there’s a framework that helps us better understand what has happened to education. It’s called the “Data / Information / Knowledge / Wisdom Hierarchy,” and it’s an effective tool for illustrating the escalating trajectory of intelligence.
There have been plenty of people who have worked on various iterations of the DIKW Hierarchy, and Wikipedia actually provides a good overview with links to places where you can examine as much detail as you have a taste for. For purposes of this discussion, let me summarize my interpretation.
- Data is the fundamental bit. A data point is a raw scrap of signal. No context.
- Information describes an accumulation of data into what we might call a “context field.” (Neither Information nor Data are “true” or “false” in a larger sense. One can array facts in ways that are misleading, profound, or somewhere in between.)
- Knowledge is what happens when we begin applying higher-order intellectual function to information, aggregating, assimilating, analyzing and arranging into it something directional and purposive. It is at this stage that truth emerges.
- Wisdom is the result of highest-order reflection. Ideally it makes best use of both right and left-brain capabilities and yields insights that are critically deep and associative, generating potentially innovative insights into a problem or challenge.
We can dedicate energy to developing even more stringent definitions, but for present purposes this should give you an idea of the concepts.
Let’s illustrate with a hypothetical example.
Say you are given a data point: it’s 72 degrees. This is a discrete bit, and in a vacuum it is utterly without useful meaning. Let’s step up a level in the hierarchy, where we consider some surrounding data points: it’s also February. The reading was recorded in Yellowknife, Canada. Hmmm. Some more data points: the average daytime high temperature for this time of year historically is -3F. It has been above 65F each day for two weeks straight. These are all record highs. Over the past ten years recorded temperatures in Yellowknife have been at least 10d degrees F above historical averages.
Now you have information.
At this point you begin studying climate data, researching experts and peer-reviewed journals. You analyze, critique, read more, broaden your scope of research. At some point you are sufficiently versed to hold intelligent conversations with other informed people, perhaps even experts. You understand what you’re reading when you encounter new data and information and are able to deliberately contextualize it and decide whether your existing mental models are confirmed or need revision. You understand what you know and are aware of what you don’t know, what else needs to be known in order to draw deeper conclusions as to the potential significance of the unusual weather in Yellowknife. This is knowledge.
We now take the final step up to wisdom, which is where we begin in earnest the process of developing theory. We consider hypotheses, we test them and iterate our theories. Theory making is ultimately about two things: explaining and predicting. Good theories help us understand why the world is the way it is. It’s 72F in northern Canada in February. We want to know the reason. Further, really good theory lets us move forward armed with the insights we need to maximize what’s good and minimize what’s bad.
Knowledge and Wisdom and Ideology
For better or worse, we’re all creatures of ideology (and I include myself in this). This term, in its simplest sense, signifies the beliefs, biases and idea sets that comprise our worldviews. Ideologies are lenses that we filter “reality” through and are the tools by which we make sense of our lives. “Democracy” is an ideology, as is any particular political philosophy. Religious views. Regional loyalties (“I live in the greatest city on Earth”). Views on race and gender and human rights. Etc.
Ideology frequently represents a problem for the cultivation of higher order knowledge. While it can provide a helpful frame for the evaluation of data and information, it can also dominate and distort the process if it is inflexible. A classic example would be the fundamentalist creationist confronted with dinosaur fossils. In extreme cases these people have gone so far as to conclude that the fossils were put here by God to test our faith. In these cases, you have a powerful ideology – conservative, literalist Christianity – that becomes the pre-ordained given by which all data is judged. Anything that doesn’t fit the metanarrative is rejected or twisted to fit (the dinosaurs existed but died out 5000 years ago).
The optimal approach, though, assimilates information and adapt ideologies to accommodate new learning. This is perhaps best expressed by a quote that’s alternately attributed to Keynes, Samuelson and Churchill: “When the facts change, I change my mind. What do you do, sir?” Science, for example, is a contentious, iterative process where it takes a great deal of evidence for a posit to be accepted as gospel. Even then, an idea only rises from concept to theory to accepted wisdom via a rigorous process of challenge, testing, revision, more testing, etc. History is replete with scientists who developed elegant theories (many of which gained strong support in their fields), only to be forced, thanks to the emergence of information that invalidated their work, to admit defeat and head back to the drawing board. Often, though, these researchers return later with evidence that further the advances the state of knowledge in their field.
These people are, like the rest of us, born and raised in strongly ideological contexts. Some are religious. Some are Republicans, others Democrats or Independents or Greens or Libertarians or Socialists or Social Democrats or Communists. These worldviews unquestionably flavor their work, but professional success hinges on their ability to privilege scientific method over the demands of ideology.
Ideology begins its incursion into the DIKW process as we transition from Information to Knowledge. This is where some begin ignoring important information or excluding it because it fails to mesh with ideological preconceptions. It also represents the point where we loop back around to the question raised by Wufnik’s brilliant post: what do we mean by “education”?
Are our educational systems content to breed Data herders? Do we emphasize on the critical thinking skills necessary to create powerfully intelligent Knowledge analysts? Do we enable development of the right-brain associative functions that can represent the difference between mere intellectual horsepower and genuinely transformative creativity? Well, that depends on the goals of those calling the shots, doesn’t it? And a close examination of the kinds of students a system produces can tell us a great deal about the politics of the system’s architects.
As Wufnik suggests, the Internet has been a playground for those “educated far beyond their capacity to undertake analytical thought.” What that means (not that his analysis necessarily needs explaining) is that our system of education is producing tremendous numbers of people with access to great amounts of data but no real idea what to do with it. That have, at most, been “educated” in a way that stops at the top end of the Information step of the DIKW Hierarchy (at best – there’s a good argument to be made that it doesn’t even go that far). This lower-level education philosophy doesn’t inculcate more rigorous critical thinking processes and it doesn’t usher the student through the Knowledge/Ideology barrier.
The result: a nation of people who believe strongly, but who lack the orientation to think past their dogmas, and who, thanks to a combination of widespread ignorance and highly sophisticated disinformation engines (like pretty much all corporate media), are awash in Data and neatly packaged disInformation (remember, neither Information nor Data are inherently “truthful”) that can be used in online “debates.”
To put it in Claude Shannon terminology, education in an Internet society thus becomes a question of “signal” versus “noise.” That is, productive communication and “truth” as opposed to static and disinfo. What is the proportion of education and communication that leads us forward to that which obstructs or leads us backward?
“Education” that fails to cultivate the Knowledge / Wisdom trajectory multiplies noise in the system. It bogs us down and renders us eternally vulnerable to those who’d distract us from what I suppose we’ll call enlightenment. Education that focuses on the Knowledge / Wisdom trajectory, on the other hand, represents a laser that lets us cut through the clutter.
Wufnik’s post, I think, makes clear the degree to which contemporary society is a slave to noise, and it’s incumbent on those of us who value genuine social and scientific progress to find ways of liberating our friends, our neighbors, our colleagues and our readers from the ubiquitous cacaphony of willful ignorance.
Perhaps the first step is something every good parent knows from dealing with the terrible twos: you don’t reward bad behavior by reacting to it.