Data is Everywhere: So What?

Data, Information, and Beyond

What gives me pleasure in learning something is that I can teach it. Nothing will ever please me, not even what is remarkably beneficial, if I have learned it for myself only. If wisdom were given to me with this proviso, that I should keep it shut up in myself and never express it to anyone else, I should refuse it: no good is enjoyable to possess without a companion.

                                               Seneca (2017)

 

 

Where is the wisdom
we have lost in knowledge?

Where is the knowledge
we have lost in information?

                                                 T.S. Eliot

[1]

 

Introduction

In the days preceding the 2016 presidential election and turbulent years afterward, the topic of misinformation and disinformation has been everywhere. From the invention of the notion of alternative facts to the ongoing propagation of The Big Lie of the stolen election – boundaries between fiction and nonfiction have been blurred. I’d like to examine a few related notions.

Information, Misinformation, Disinformation, Malinformation

To clarify what I’m talking about I need to begin with a few definitions. I am adopting the following three items to begin a glossary. I don’t insist that these are absolutely correct; in the interest of successful communication, however, I want to let you know just that I mean by certain words[2].

Misinformation: Unintentional mistakes such as inaccurate photo captions, dates, statistics, translations, or when satire is taken seriously.

Disinformation: Fabricated or deliberately manipulated audio/visual content.  Intentionally created conspiracy theories or rumors.

Malinformation: Deliberate publication of private information for personal or corporate rather than public interest, such as revenge porn.  Deliberate change of context, date or time of genuine content.

Moving down the list, we move from what might be an innocent error to an outright lie to an intent to do damage.

But the root word in each case remains information. Let me now offer a glossary entry for information.

Information: That which reduces uncertainty in a decision-making situation. That is, having a piece of information is a difference which makes a difference.

It is this reduction of uncertainty that give information its value. It’s why we’ll pay for a second opinion for a medical situation, or a second estimate on a remodeling project. We want to make better decisions. So if something does not help you make a better decision, by definition it is not actually information.

Information is thus contextual. For you it might be information while for someone else it is not. But what is it for that other person?

Information contrasted with data

Time for another glossary entry.

Data: Whatever we are willing and able to store for potential future retrieval and use. It consists of symbols that represent objects, events, properties etc., and are products of observation.

For example, an individual might have these blood pressure readings in his medical record:

If he simply stores those reading, then they are by definition not information. They are merely data. Let’s suppose that he observes the trend, determines that it is undesirable, and takes some action – makes a decision get appropriate qualified guidance and alter his diet and exercise patterns – then what was merely data gets promoted to the status of information.

Another phrase that we often hear is ‘information overload.’ If you accept my definition of information, then an information overload is much less likely. Data-overload, however, is rampant. We are bombarded with data from myriad sources. The news media, social media, the barber and the bartender, friends, relatives (especially in-laws) … all seem happy to give us more and more input leading to genuine data-overload. Data in plentiful, true information less so.

Information overload is however possible. Suppose you must make a decision and you currently have four pieces of information. That next bit of information, piece number five, might be genuinely helpful. But if you already have 99 pieces, then piece number 100 is not likely to add much even though it might add a smidgen. As the amount of information mounts, it becomes increasingly difficult to separate the vital few bits from the trivial many. And you reach a point of diminishing returns for the cost of acquiring just one more bit.

Building on the work of Ackoff (1999) and Tuthill (1990), we can now begin to construct a hierarchy. At the lowest level, we have data. Up one level, we find information. Since the amount of information is smaller, we will draw this as a pyramid. I’ll call this the ‘data hierarchy.’ Continuing to build, we can add two levels on top of this base.

As we move up, the quantity becomes smaller while the value grows larger. Thus, understanding is more valuable than knowledge which is more valuable than information which is more valuable that data. We’ll get to the two higher levels in just a moment.

The transition from one level to the next higher in each case involves a process. We’ve noted that data must be stored. To transform it into information, it must be selected for relevance to our current situation. Here’s another version of the hierarchy adding the necessary processes.

Another glossary entry.

Noise: Anything which contaminates our supply of data or which impedes our ability to select the information from the underlying data. Note that the noise may appear as opinion or belief masquerading as data.

In terms of the data hierarchy, noise is off-the-chart low. Returning to the blood pressure example, the fact that the patient’s hair was black is simply noise. It’s not worth storing. It has no potential to improve decisions about diet or exercise. Noise simply gets in the way, consuming resources that might be better employed storing genuine data or selecting it as information.  Noise may even be misleading as Kahnema, et.al. (2021) points out. What we need here is a sort of education, a metaphorical ‘noise abatement program.’ Or as Postman and Weingarten (1969) put it, “The purpose [of public education] is to help all students develop built-in, shockproof crap detectors as basic equipment in their survival kits.”

We can hope that over the course of time, our inadvertent inclusion of a bit noise may lead us to wrong (but not catastrophic) decisions. In future iterations, then, our filters may improve. The metamorphosing of data into information will generate better results. But this improvement is entirely optional – not only individuals but even organizations can exhibit learning disabilities!

Information as fodder for learning

Going up one more level is subtly different. Moving from information to knowledge requires a metamorphosis, the appearance of a knower, an person who houses this knowledge. The supporting process we call learning. And going to the topmost level, understanding requires that the knower assimilate or integrate this knowledge with all her other knowledge. Because of the requirement for a knower, we can draw a significant conclusion. It’s not knowledge unless someone knows it. Thus one person can transfer information to another person but cannot transfer knowledge. The knower must also be the learner.

How then does one promote or enable or facilitate learning if we cannot transfer knowledge? We can take it apart, working down the hierarchy. We can take our knowledge and break it into bits of information – and that we can transfer. It involves taking it out of one brain and making it available as input to a second brain. The taking-apart we can call analysis – analyzing something into its constituent bits. Some might call it reductionism; in either case it is an attempt to make a complex phenomenon simpler.

Time for another glossary entry.

Analysis: Converting or decomposing knowledge into information by one person for ease of transfer to enable another person’s learning. Or, similarly, converting information into data for ease of storage.

We seem to be awash in people who want to do analysis. News analysts, financial analysts, political analysts, data analysts of every imaginable ilk. Analysis is everywhere. But we’ve seen that analysis is about taking things apart and simplifying them. Of course, at some point you lose sight of the big picture if you keep breaking it into smaller and smaller pieces. That is, if you focus on blood pressure too exclusively, you can lose track of the actual human being.

And going up the hierarchy is about the opposite of analysis. What is that called?

Complement to analysis is synthesis

While analysis is everywhere, synthesis is much less common. Indeed, taking time to develop a richer understanding before taking action seems to be positively frowned upon. It’s all shoot-from-the-hip-based on private knowledge for short term gains. Perhaps we need a new slogan. How about, “Don’t just do something, stand there!”

Time for yet another glossary entry.

Synthesis: Putting together smaller bits of knowledge to achieve a richer and more comprehensive understanding. Assimilating or integrating new knowledge with preexisting knowledge.

A key responsibility of leaders and educators and coaches and mentors lies in helping others evolve their confidence in and competence with synthesis. Yes, we must have data and information. But we must also remember to look at the whole not just the parts. We must look at the whole system of interrelated components, not just the discrete elements.

Another phrase we hear often is ‘data-driven decision-making.’ Well, data is a good starting point. But given this hierarchy, wouldn’t we really prefer ‘information-driven’ decision-making? Or possibly even ‘understanding-driven decision-making?’

Here’s an updated version of the data hierarchy with the more recent additions.

If we have the achievement of understanding as a goal, then we need to move up the hierarchy. Moving up the hierarchy to develop a richer understanding requires learning (to metamorphose information into knowledge) and integration (to transform knowledge into understanding).

Ultimate goal is wisdom

Beyond understanding, we find one more level to consider. While having a rich understanding is surely important, we often need to take action.  Above and beyond understanding we find wisdom.  Our last glossary entry, Ackoff again:

Wisdom: the ability to perceive and evaluate the long-run consequences of behavior.  It often includes a willingness to make short-run sacrifices for the sake of long-run gains, making effective decisions that are value-full, not value-free.  Wisdom is understanding combined with applied values.

Let’s recap with a different slant. Perry (Steinberg, 1970) wrote that

“Through education men acquire the civilization of the past, and are enabled both to take part in the civilization of the present, and make the civilization of the future.  In short, the purpose of education is three-fold: inheritance, participation, and contribution.”

Inheritance from the past, participation in the present, and contribution to the future. Warfield[3], after quoting Perry, suggested an addition: integration. Warfield’s concern was with the rise of the specialists and the diminishing attention paid to the generalists. The latter are those who can synthesize across multiple disciplines. It’s as though our collective ability to acquire knowledge has outstripped our ability to develop our wisdom.

While our world is growing more interconnected, many seem to withdraw in the face of the resulting complexity, yearning for a simpler time. They often fall into the trap of looking at a problem or an issue from just one perspective. Ackoff et al. made a key point here.

“It’s important to realize that problems are not disciplinary; there is no such thing as economic, health, governmental, educational, physical, chemical (and so on) problems.  The adjectives in front of the word problem tell us nothing about the problem.  They tell us about the point of view of the person looking at the problem.”

If we aspire to address the problems meaningfully, we must rely on wisdom. We must be willing to examine a problem from multiple frames, bringing our values along to guide our thinking and leverage our understanding. It might help if we swapped out decision-making and substituted option-selection instead. This might remind us that we are choosing only from among the options we’ve identified. And looking from another perspective might open our eyes to still more options.

Epstein (2009) quotes 3M researcher Andy Ouderkirk:

“If you’re working on well-defined and well-understood problems, specialists work very, very well. As ambiguity and uncertainty increases, which is the norm with systems problems, breadth becomes increasingly important.”

Deep and narrow must be complemented by broad and deep-enough. Epstein goes on to write

“Work that builds bridges between disparate pieces of knowledge is less likely to be funded, less likely to appear in famous journals, more likely to be ignored upon publication, and then more likely in the long run to be a smash hit in the library of human knowledge.”

As a society we have over-invested in the depth of knowledge of our specialists. We need to catch up now by adding more emphasis on increasing the understanding of our generalists. But today that is counter-intuitive. Going deep and narrow has served us well for several centuries but we are now facing newer and more complex problems.

A last thought on wisdom and good judgment. Someone commented, “Good judgment comes from experience; experience comes from bad judgment.” In many cases today, we do not have the time or resources to gain experience the hard way.

This work draws on ideas from the following:

Ackoff, Russell. 1999. Re-Creating the Corporation. New York: Oxford University Press.

Epstein, Greg M. 2009. Good Without God. New York: Harper.

Kahneman, Daniel, Olivier Sibony, and Cass Sunstein. 2021. Noise: Little Brown.

Postman, Neil, and Charles Weingartner. 1969. Teaching as a Subversive Activity. New York: Dell Publishing.

Seneca, Lucius Annaeus. 2017. Letters on Ethics to Lucilius. Translated by Margaret Graver and A. A. Long. Chicago: University of Chicago Press.

Steinberg, Ira S. 1970. Ralph Barton Perry on Education for Democracy. Columbus OH: Ohio State University Press.

Tuthill, G. S. 1990. Knowledge Engineering. Blue Ridge Summit PA: TAB Professional Books.

[1] From http://www4.westminster.edu/staff/brennie/wisdoms/eliot1.htm#:~:text=Where%20is%20the%20wisdom%20we,we%20have%20lost%20in%20information%3F&text=Bring%20us%20farther%20from%20GOD%20and%20nearer%20to%20the%20Dust. Accessed on 10/14/2021.

[2] Taken from https://www.minitex.umn.edu/news/elibrary-minnesota/2021-02/misinformation-disinformation-malinformation-whats-difference. Accessed on 10/11/2021.

[3] This comment came from John N. Warfield’s website in the early 1990s.