The Practice & Art of Thinking

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I normally would present the complete ‘picture’ – in this case, the ‘method’ for problem solving – and then explain what I mean by the individual components of the method. This assumes that the method consists of a combined set of components, which is the case here.

I am using this approach for the simple reason that I think the ‘journey’ (to use an over-used term) is important, allowing us to develop and visualise a personal version of the whole, which would be negated if presented with the conclusion upfront. I will add, many principles of the method have already been touched on throughout this blog.

The method consists of a mix of concepts and specific principles. In this post I will be looking briefly at aspects of the concept of ‘Reason’.

The notion ‘reason’ is important but we tend to park it in the ‘hard basket’ for the simple reason that it has connotations of ‘philosophy’ and such discussion can have the feeling of talking to someone who has forgotten to take their medication – it all seems a bit ‘random’ – as some New Zealanders would say.

Let us quickly look at why reason is important. A great example is that captured in one of Popper’s books (title at end of post), where he suggests that a healthy society is one that is open to ideas and reason. In contrast, non-open societies are (as Popper states) ‘barbaric’, with no capacity for sympathy or understanding for others and diversity of opinion (I could not agree more. We can currently see this happening in our world).

urlWithout the ability to reason, we cannot progress and understand the world around us. We reason to consciously make sense of things and to establish and verify facts. This is exactly what one needs to do to get to grips with any problem situation.

We tend to confuse the term ‘reason’ with logic and use them interchangeably but they are different. To explain, we can use the example of the difference between movement and locomotion. All locomotion is movement but not all movement is locomotion. A tree moves but it does not locomote because it is rooted in the ground. Likewise, all logic is reason but not all reason conforms to the standards of logic.

If logic is the map of what’s really “out there”, reason is the process of trying to read and follow the map. Using another example – reason is the application of logic to one’s perception of the real world, like engineering is the application of physics.

Simply put, reasoning is the actual process of evaluating information and applying logic to arrive at an appropriate (correct) conclusion.

It might now be clear to see why refining our skill of reasoning is essential to good problem solving. It should be considered as the overall concept of the method of problem solving – the balancing force.

I have used the metaphor of the spinning top before (see here in relation to design thinking). We could consider reason as the overall resultant force that keeps the spinning top performing at its optimum – in this case, good problem solving could be seen as a spinning top humming away, where reason is the element that feeds all the other forces and ensures they are performing at peak condition.

From this, it is not too difficult to see why it is vital that we are eloquent at reasoning and understand the importance of reason in relation to good problem solving practice. The cartoon below by Luiz Oswaldo Carneiro Rodrigues stresses the point that data should not be forced and distorted to do what you want it to do. One needs to use reason at all times.

Treat Your Data with Reason - Not With Force. Cartoon by LOR

Treat Your Data with Reason – Not With Force. Cartoon by LOR

I look briefly at reason and ‘listening to data’ shortly in the future.

Book: By Karl Popper – The Poverty of Historicism; The Open Society and Its Enemies. First published in London in 1945, Russia in 1992 and US 2013. This book was on the Modern Library Board’s 100 best nonfiction books of the 20th century. It criticizes Marx, amongst others, for relying on historicism to underpin their political philosophies.

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Is Visual Thinking a Science or a Pseudo-Science? Part 1

I will consider this question over two posts; I do this for the simple reason that long posts are difficult to read.

The first part will define the terms science and pseudoscience. The second part considers if Visual Thinking is a science or pseudoscience; after all, visual thinking could be nothing more than a flash in the pan.

The history of any discipline takes shape and emerges in various changing social and intellectual contexts. The boundaries are not predetermined. They are dependent on the conditions of their constitution and also on the developing relationship with other disciplines that are also, in turn, contingent on their own histories.

The history of science is fascinating and the beginnings of all disciplines are rather like a strange attractor forming around forces (contexts), people with like-minded interests and burning questions humans have at the time.

When we say ‘I think scientifically’, we are essentially referring to an objective process of putting claims to rigorous and systematic ‘test’ and to test if beliefs we have about the world are true or not. All scientific knowledge and theories are based on observation and consistent logic. A theory is a logical explanation for observations.

The term ‘test’ refers to a process of investigation of whether the real world behaves as predicted by the hypothesis.

The question is really about how to draw that line of demarcation – the ‘fence’ between science and pseudo-science. For instance, is astrology a science or a pseudo-science?


We might have a gut feeling or even a strong position, but how do we explain the difference in rational terms? Not in  ‘I believe’ terms, but in “I must explain logically” terms’.

Humans have a natural curiosity for understanding the reasons we behave the way we do but, more importantly, we need to be able to make decisions based on fact and we need to be confident that our theories about the world are correct. The reason we develop theories is so we can describe, explain, predict and control. We need to be assured that the knowledge we have is reliable for us in order to make decisions.

It is for this reason that we test and re-test until we start to be confident that the knowledge we have is reliable.

Why do we need to make a distinction? Well, I could state that I believe in fairies that live in the bottom of my garden. Do they? Because I make the statement that they live there – does it make them real?

The point is how do we make the distinction between science and pseudo-science?

image source modified by Rui Martins

image source modified by Rui Martins

The issue of objectivity and subjectivity is a difficult one and not one that we should be flippant about. Postmodernists would argue, as stated by Stephen Gould (evolutionary biologist and a non-Postmodernist) “Science is a social phenomenon… It progresses by hunch, vision, and intuition. Much of its change through time is not a closer approach to absolute truth, but the alteration of cultural contexts that influence it. Facts are not pure information; culture also influences what we see and how we see it. Theories are not inexorable deductions from facts; most rely on imagination, which is cultural.”

In other words, life has just become a little more difficult and not straightforward. Nevertheless, we still need confidence about what we know so as to move forward.

The traditional way to define science is that it is inductive. It builds from individual experiences to theoretical generalizations. This is correct. Science does proceed in this fashion but so does pseudo-science. It is a necessary condition but not a sufficient condition for something to be scientific.

Because of this, we need a better qualification to test between science and pseudo-science. The Vienna circle offered the notion of ‘verifiability’ as the mark of science.

What makes something scientific is that it is verifiable. Collected data or empirical evidence is required to verify the theory.

Karl Popper had a problem with this criterion as well. He thought it was too easy – “once your eyes were … opened, you saw confirming instances everywhere: the world was full of verifications of the theory”. Once you ‘got it’ one starts to see things and reinterpret them to verify one’s point of view. For instance, seeing Stonehenge and then stating that it was built by extraterrestrials, the same with crop circles etc.


Popper claimed that a theory must, in principle, be falsifiable in order for it to be valid science. A theory must make predictions that can be tested. For example, evolution is theoretically falsifiable. People keep on testing it and, while the results are significant, it remains a scientific truth.

However, at any point in the future, the current ‘truth’ can be falsified when more knowledge and resources (new experiments and technology) become available. In such a situation, if an observation contradicted the principles and falsified the idea of evolution, at first the observation is questioned and if future observations keep on falsifying the theory, the established theory then becomes suspect.

Even Charles Darwin stated: “if it could be demonstrated that any complex organ existed, which could not possibly have been formed by numerous, successive, slight modifications, my theory would absolutely break down.”

Taking the example of Astrology and Fung Shui for instance, both have a history of disciplines that cannot be disconfirmed. They do not set themselves up to be falsified. They are insulated by the way there have been set up.

Astrology, for example, is a theory that states that our destinies are controlled by the stars under which we were born. This theory has not been put forward in a way that it could be falsified; the history of astrology is not about a group of people looking for ways and tests to falsify the theory (i.e. looking for falsifications in order to look for better theories). Instead, it is a history of people making money from fortune-telling.

The way to build a pseudoscience is to build a theory that cannot be falsified. There is nothing that can be said or tested that can defeat the theory. Any argument can be rejected and deflected.

For instance, going back to the ‘fairies that live at the bottom of my garden’ – If I say the fairies are invisible and undetectable by any means that can be manipulated by mammals – there is nothing that can be said to disprove this statement. It cannot be tested by touch or CT scans. It is invisible to all mammals (humans are mammals – no argument). It cannot be falsified – it is a pseudoscience. Unfalsification has been built into the theory.

Another way to build a pseudoscience theory is to make it a moving target, where the theory changes slightly when scrutinized. An example is the Ptolemaic Astronomy theory of the universe – the planets and the Sun circle the Earth. However, this is easily falsified by simply plotting the motion of Mars across the sky – we see retrograde motion (observed backward motion of the planet). The theory then gets quickly modified to say that there are invisible pivots that circle the Earth around which planets turn and this appears to address the issue of retrograde motion.

The Ptolemaic system of the universe explained many things and defined which questions were legitimate and which should not be asked.

The Ptolemaic system of the universe explained many things and defined which questions were legitimate and which should not be asked.

Unfortunately, this theory does not fit careful observations of Mars either – oops! The theory is further modified by saying that the planet circles around a point that circles around another point that circles around the Earth. We can then keep on adding post hoc modifications to the theory. All this is the ideal making of a pseudoscience. If one does this often enough, the theory becomes unfalsifiable.

A footnote to the Ptolemaic Astronomy – the reason that people at the time expended so much effort in forcing this theory was that they were obsessed with their belief that the Universe could be described through elegant and beautiful mathematics, which in turn enabled them ‘logically’ to mathematically calculate and predict their future and when some event would occur. What is fascinating is that even Galileo is on record as having cast astrological maps for his children. That is how powerful a theory can be, even if false, on the way we live our lives.

For this reason, I think it is important that we seek to know that what we are basing our decisions on is as accurate as possible and not some falsehood that makes us build castles for the fairies living at the bottom of my garden!

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A Visual Essay

In this video, Paul Jenkins tells the story of a photograph. There is great skill in deconstructing meaning and putting the story together that is captured in the metaphors in the photograph.

The video is about 14 minutes long.

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Photographs And What They Say

I find this video fascinating and cannot resist sharing the lessons.

Paul Jenkins uses the International Mission Photography Archive to explore and analyse photographs. I particularly like the way he asks questions and visually answers them. The video is 29 minutes long – enjoy.

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Visual Data – The Humble Graph

In my quest to understand why visual thinking is important, and what the benefits are, I decided to explore further questions:

When we are confronted with data, why do we prefer to see it in a visual form rather than the raw data? Does the visual form enable us to produce new knowledge and gain new insights?

In my view, what emerges from the visual form is greater than the sum of the individual data elements.

Let’s use a very basic example. Firstly, what does raw data look like? I found this small set for the total population of the City of Lethbridge, Canada.

Population for Lethbridge, Canada - Raw data.

Population for Lethbridge, Canada – Raw data.

How easy is it to make sense of the data? We can see that the population has increased but do we get any more out of the figures without having to consult a calculator? Can we easily see what the trends are and what the rate of growth has been in the different areas (North, South, West) and years?

Below is the same data represented in Graph form.

Population for Lethbridge, Canada - graph.

Population for Lethbridge, Canada – graph.

The graph is a visual/pictorial means of representing relationships between various quantities, parameters and measurable variables. A graph summarises how one quantity changes if another quantity, that is related to it, also changes.

Graphs summarise substantial information into one visual. In some cases, graphs are the only way to represent data and make sense of the results. Often one does not know the exact relationships and interdependence between the various quantities that are being measured. By using a visual like a graph, one is able to comprehend how the variables change relative to each other. It provides a vivid image to “hang onto” in order to have some intuitive picture of the information and the dynamics between the data.

Hubbard explains … “There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.”

The magic is the synergy of information where meaning emerges and the observer can see and know the whole. Not only because it is immediate but because the attention is released from having to linearly digest the data to being able to postulate questions; explore explanations; and frame a story of meaning about the information. You are not caught up in the manipulation of the data.

In not a dissimilar way, I would suggest that this is what happens between text and an image that represents the content of a text. The raw data (to a degree) is the text and the graph is the visual. I will explore this further in the next post.

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Data Visualized

One can argue that the practice of visually representing information is ancient – that cave man did it on cave walls. However, there has been a new wave and fascination for data visualisation. The reason possibly is that we not only generate vast amounts of data individually, but collectively the data is daunting. How do we make sense of this data/information? How can we get our heads round this?

Information visualisation (one should really say data with meaning) is a powerful way to tell the complex stories embedded in data. I do think that once the data has been processed to produce a visual it already has meaning associations, even though it remains open to be recast for further sense making by the observer, it already has been shaped by a worldview. This is particularly true in the third example. With the first example, however, one could argue that the video is data rather than information.

The video below by Aaron Koblin shows map charts of air traffic over North America. Visually depicting data about aircraft models, flight routes and flight altitude. The video enables each observer to construct their own stories from the visual information, which would otherwise be difficult from the vast amounts of raw data.

The Flight Patterns visualisations are the result of experiments leading to the project Celestial Mechanics by Scott Hessels and Gabriel Dunne.

Other interesting examples:

The image below is a 3D spectrographic visualization of sound frequencies heard during real-time sound analysis. The image is computer-generated using digital signal processing techniques. In acoustics, a spectrograph converts a sound wave into a sound spectrogram.

Fast Fourier Radials. By Paul Prudence.

Fast Fourier Radials. By Paul Prudence.

The project below entitled Thursday is part of the “One Week of The Guardian Series” by Dave Bowker during 2007-2008. Bowker took the news from one week and visually represented it as a series of static visuals.

This visual was pretty much focused on the relationships created between headlines, authors, pages, and categories. I wanted to see how much of a mess the relationships could make if they were all surrounding one container ….” David Bowker. To read the full exploration see here.

One Week Of The Guardian. By Dave Bowker at Ultra Knowledge UK.

One Week Of The Guardian. By Dave Bowker at
Ultra Knowledge UK.