Thinking about Thinking 3

When we think about epistemology (theory of knowledge), then we are doing meta-thinking. That is, we are thinking about thoughts people have, which they think is “knowledge”.  Because there are many many wrong ideas, and very few right ideas, we must learn to think critically. Unless we do so, our thoughts will be captured by the enormous amounts of fake news which circulates on social media these days. Thinking about thinking, or Meta-Thought, is very different from the standard education which students receive. Instead of asking about the “models” in use, and assessing adequacy or failure of their “assumptions”, at the meta-level we ask how economists began to use these models instead of others, what kind of thoughts are promoted by such models, and what kinds of thoughts are blocked, because the models are incapable of expressing such ideas. This kind of higher-level thinking is completely missing from conventional textbooks.

To highlight the differences, we consider as an illustrative example, how Martin Osborne begins his textbook on game theory, and explains what game theory is about:

GAME THEORY aims to help us understand situations in which decision-makers interact. … the range of situations to which game theory can be applied: firms competing for business, political candidates competing for votes, jury members deciding on a verdict  etc. etc. etc. .

Next, note what famous game-theorist Ariel Rubinstein has to say about this issue: “Nearly every book on game theory begins with the sentence: ‘Game theory is relevant to …’ and is followed by an endless list of fields, such as nuclear strategy, financial markets, the world of butterflies and flowers, and intimate situations between men and women. Articles citing game theory as a source for resolving the world’s problems are frequently published in the daily press. But after nearly forty years of engaging in this field, I have yet to find even a single application of game theory in my daily life”  (see Quotes Critical of Economics).

There is a strong conflict here. Martin Osborne tells us that game theory helps us to understand a huge variety of different situations. However, Ariel Rubinstein tells us that he has not been able to find even one useful application of game theory in forty years. Which of these two thoughts is correct? How can we tell who is wrong and who is right? We need to compare and evaluate these two thoughts, which required meta-thinking. Also, we are concerned with evaluating knowledge claims – what do we know, and what we do not know. So, this is a topic in epistemology.

Of central importance to us in resolving these issues is the concept of a “MODEL”. What is a model, and how does it relate to reality? Here is what Martin Osborne writes: “Like other sciences, game theory consists of a collection of models. A model is an abstraction we use to understand our observations and experiences. What “understanding” entails is not clear-cut.” This last sentence is revealing. Economists do not understand what a model is, and how it helps us to understand the real world. You will find often repeated assertions that “models are simplifications of reality” and that “models are always false”. These maxims are not helpful in understanding models. Actually the “simplification” that models perform is of a very special type == models set out for us “what matters” and also exclude “what does not matter”. The variables and descriptors we use are the ones which matter. Anything which does not enter into the theory does not matter. This despite textual assertions to the contrary — what we are being taught in the economics textbooks does not lie in the words that are written — it is contained in the words that are not written. By not writing about compassion for the hungry, and social responsibility, we are told that these are not relevant concepts for the economic system – these things do not matter. So one function of models, not explicitly mentioned, is to tell us what is important and to separate these variables from the large numbers of variables which do not matter. The second function is to specify the chains of causation. Consumers have incomes and they make consumption decisions. Investors borrow money to invest. Firms make production decisions. All of these theories provide a strong causal sequencing about how things happen, what happens first, what happens next as a consequence. This actually sets up the exogenous variables and the endogenous variables, again without any explicit mention of causality. A third aspect of models sets up superstructures as well as constructing RULES which are used to evaluate models.  These we will discuss later, when we discuss the three major categories of models, in the next section.  Also of essential importance is the question of how models “explain” – how they “help us to understand” – reality. This will also be discussed in greater detail later.

RELATED POSTS: On the Central Importance of a Meta-Theory for Economics. and  Meta-Theory and Pluralism in the Methodology of Polanyi   This is the 3rd post in a sequence; The first two are:  Mistaken Methodologies of Science 1  and  Models and Realities 2  The NEXT post is  Errors of Empiricism 4 

One thought on “Thinking about Thinking 3

  1. Algorithmic comments continue. Yes, I agree, meta-thoughts are necessary, and models need re-interpretation even reformation. The following problem is: how to do?

    1. Meta-thoughts mean that a thought objectifies another thought while the latter runs in its own way, so it entails thoughtful particles and discreteness, just like atoms and molecules run in the space. Algorithm Framework Theory is designed to portray the picture. One Instruction processes two data, resulting in one data. The operations go one by one serially at a certain speed. This is how a person thinks. As any instruction, datum or operation is independent of another, a person thus is able to objectify another person or himself. Why meta-thoughts are eliminated by mainstream economics? Because the latter implicitly assumes infinitely fast speed, or zero thinking time, there is no any thought independent, and all thoughts must be fully integrated into one whole body at any time, and in any circumstance, and hence observers or analysts cannot effectively distinguish the actors’ ideas from their own. This could be the root of even all defects of the mainstream.

    2. Mainstream always seeks “models”, why? The above has given the answer. Because of the infinitely fast speed, or zero thinking time, mainstream has to illustrate perfections, accuracies and statics — as the results of thinking processes — while pretending to forget the thinking processes and the rest of the world, as mainstream has no way to explain why the latter exist. Mainstream actually can explain only some parts of the world, and cannot explain the world as a whole, just like explaining some islands in the sea while failing to explain why there is the sea. Once finite thinking speed & time introduced, the rested world will return to economic theories, such as subjectivities, pluralities, dynamics, complexities, chaos, uncertainties, developments, etc. I mean, the latter now revive not as exogenous assumptions, but as high-level “laws” or “regularities”. This Algorithmic model could be a huge model where mainstream models partially exist inside. This is also why I say earlier that Algorithmic economics do not resist differences and changes, but anticipate them. The problem is not the model itself, but what models.

    I wish my meaning could be understood. If not, any question is welcome.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.