Techniques and Knowledge, Goals and Exploration

A few months ago, I had the opportunity to attend a wonderful exhibition on neorealists in Rovereto (Italy). These artists (among which figured Piero Annigoni, Šiltjan and the Bueno brothers) believed in a form of art that was universal, comprehensible by everyone. They were looking for a renovated order and beauty, in contrast to the post-modern painters of the second half of the 20th century.

In this sense, painting techniques were not neutral for them, or at least they were not really thought as neutral. The choice of materials, colors and subjects in favor of the old renaissance ones found fertile ground among those in power, bringing Annigoni to be remembered as “the painter of queens”. This made me wonder what exactly is the relation between the relevance of techniques, also in other fields of human experience, walking through our own perceptions.

So, this time my inquiry revolves around the role of answers and questions in knowledge. As professionals at the intersection between business, organizational theory and IT, when we pose questions we aim to translate those questions into specifics and technical documents.This is what business analysis and requirements engineering are set out to do. The goal of these kind of practices is to translate a need into a usable representation, thus creating a structured requirement.

But at the same time, in axiological terms, we are not required to investigate where that specific need came from and what it represents. Instead, we generally apply interpretive frameworks and tools to different phenomena that affect information systems, the enterprise, individuals, a community, a society, and so on…

This is what separates business-oriented disciplines and science. So, I started pondering how achievable exactly is to understand something completely, to the maximum possible extent. Is there any real truth?

For at least a century, scientists, philosophers and sociologists have reasoned around this idea and got to the conclusion that we can only get better at understanding what something more certainly is not, but it is much harder to get a solid grasp of what something certainly is.

Rejecting logical positivism, Popper states that empirically verifiable statements can not be hold as true and cognitively meaningful due to the impossibility of achieving complete information.

In fact, an infinite number of experiments and observations should be required to completely label something as true and valid. This means that experiments and observations can never verify an hypothesis, but can only disprove it. One single anomalous instance is enough to logically falsify a claim.

Therefore, the more a theory holds up to falsifying observations, the more we can (temporarily) consider it true as they minimize the inevitable gap with reality, until an actual discrepancy arises. This is what Poppers calls Fälschungsmöglichkeit, or the possibility of falsifiability.

In other words, it is more accurate (and more elegant) trying to disprove oneself, rather than assert dominance into the knowledge space and state that your statements are just “right”.

Notwithstanding the complications of this vision in terms of epistemological inquiry, this approach has some interesting implications about how we commonly relate to knowledge, the unknown and change.

So, how should we deal with the change then?

Again, we can then consider what Karl Popper suggested about observing reality, as it is not enough to just observe, but we also need to know what to observe. Among all the different existing scenarios, only some carry actual meaning. To exactly discern what matters from what does not, learning and dealing with theory help us giving a frame in which our observations can move.

In fact, preexisting theory is always present in the mind of the observer and it may indeed create biases in the interpretation of reality, creating a psychological space for the possibility of verifiability.

Accordingly to Popper’s evolutionary epistemology, products of science (such as concepts and theories) are symbolical entities, subject to the same processes of natural selection that influence biological organisms. In this sense, best fitting concepts and theories are those that are better suited to resist selective pressures from scientific actors. Those concepts are retained, reproduced, transmitted and passed on until invalidated.

On the one hand, the presence of preexisting knowledge can fix and stiffen one’s mind, but on the other hand it provides the foundation for the three steps through which human knowledge proceeds: problematization, congecture, contradiction.

Problematization

Preexisting knowledge is put under strain by new questions. In this sense, a vision for change is socially created and mediated by different actors from different areas. Peter Miller expressed himself on the idea of problematization, that he interprets as stressing current concepts and symbolic devices so to create new meaning.

To use a practical example, in a 1998 essay Miller tackles the change of accounting and how it became to be what is known today as cost accounting, with all the influencing dynamics happening at its margins that put previous ways of doing accounting in the corner.

The term margins is used here to refer to that part of the terrain or surface of accounting that, at a particular point in time, is immediately within its boundaries. To attend to the margins of accounting is to emphasize that there are different margins at different points in time, and in different places. The margins of accounting change as the boundaries of accounting are redrawn. Claims that something could be done better in another way, or in other words, representing concepts differently.

“Everyone should be convinced that problems are related to a particular device rather than contingent, thus putting that device in an unstable position, ready to be discussed and dismantled.”

That is, problematization aims to find limitations, not possibilities.

In general, posing questions opens the scope of an issue to the development of a theory. Completely understanding something is a way of looking to all the possible answers, trying to have a clearer view of the sheer size of a matter or an issue. But what I really want to stress is that having all the possible answers is not something we can achieve, or something that we should want to achieve, for that matter.

In fact, I’d rather focus on all the possible questions that arise from a single issue. I don’t really want to talk about intension and extension here, but I believe that creating knowledge through questions is more valuable than creating knowledge through answers.

In this regard, posing questions actually forces oneself to reason obviously about the answer, but also about the question itself. A question could be wrongly put, or it can have other questions inside itself, as well as a history that brought to it.

This is indeed true for answers, but we often have quick answers also originating from the common perception of things. We live in a world where answers are readily available, technically justified and not contested.

Making my own assumptions, I believe that this phenomenon finds its roots in the legitimation of industrial disciplines oriented to profit, swapping religious beliefs for those ones that control our economy and the behavior of consumers.

Therefore, I would argue that this kind of popperian process of evolutionary epistemology also takes place in different contexts of applied economical knowledge that diverge from science, such as accounting, finance, information systems management, marketing, and so on.

Congecture

In this context, when new ideas are born, they come from a preexisting perimeter and tend to validate themselves.

This is equivalent to state that econometrics, accounting and management practices, with all their own underlying prospects of reality, are legitimized to “do their thing”, drag some conclusions out of their unvalidated assumptions and recommend actions (accordingly to that specific interpretive framework).

Being disciplines applied only for specific goals, professionals have tools, models, and techniques that are not completely neutral and that can only give certain answers.

In this sense, a mean gets portayed as a goal and crystalized in a theory and an interpretive framework. Tools are straight-forward answers that conceive meaning, portayed as value-oriented actions towards a goal.

Contradiction

Furthermore, unlike “canonical” sciences that are subject to the scrutiny of formal invalidation, these technical and applied disciplines more likely resemble a collection of techniques that bypasses the unification under a single metatheory. They lack falsifiability.

Scientific progress is not grounded on cumulative knowledge towards truth, but on discarding errors.

In this sense, these answers are applied tools that are a mere slavish imitation of the scientific method. The risk lies in the technical passiveness typical of scientific (and business-oriented) training, where questions are not completely investigated and answers take stage in a inductive setting.

Conclusions

I believe that contamination between disciplines is good and that techniques are necessary. In all of this, a right balance probably exists.

However, goals are always present. Specific goals within a specific framing must be identified before talking about applications and techniques. Knowledge exploration should not be oriented towards a specific goal, but rather be open to possibilities.

And on the other way around, using a critical approach on existing applications in a practical field is useful to dismantle crooked goals. Attacking practices and disciplines contesting what lies at their margins is an effective way to expose special interests.

This way can scientists effectively remain trustful toward the needs of whole humanity. Thus, only then will broader civil society be able to identify the line between the particular and the universal, be able to imagine change.