The Fallibility of Models, the Ludic Fallacy, and Unpredictability within Complex Systems

Modeling can be a difficult process in itself, but one of the great flaws of artificial models is that when applied to real world complex systems, models of those systems are often oversimplified, and since you can never have a complete awareness or measurement of all the information present in a system and all the variables, the model and the predictions made within the model often fail to be accurate and are not successfully applied to a real world scenario.

    Often times the complexity of the variables of the scenario is too great and results in a great degree of unpredictability within the system that no artificial model, no matter how empirical the model is, can successfully apply to the scenario and flawlessly predict its outcomes. This is known as the Ludic Fallacy. The Ludic fallacy was first described by a statistician by the name of Nassim Nicholas Taleb. He describes it as "the misuse of games to model real life situations."

      Games are a foundational component of modeling systems and scenarios within a system. Taleb discusses the problem of games being narrow and lead to inaccuracies within the predictions of the model because of the gross oversimplification games create when applied to the real world. Often times the more messier and uncontrollable variables are ignored when a real world event is modeled on a game. The problem with this is those messy variables will still affect the outcome of the game and prediction whether you ignore them or not, leading to inaccuracies within the model and often a failure of the model

     Now lets apply this to two real-world applications of the Ludic Fallacy. The first application I will discuss is mental illness and the brain and the oversimplification of moods, emotions, and thoughts and beliefs in diagnosing and treating certain mental illness. This one is a bit personal, but I want to tie the Ludic fallacy concept into something unconventional.

   The brain is one of the most complex systems in the universe. Almost as complex of a system as the universe itself. The brain can imagine universes and comprehend other complex systems to a certain extent in its own right.  When it isn't working right, humans try to use empiricism and scientific approaches to categorize, label, and diagnose symptoms and conditions of the mind that go against socially accepted behavioral norms and decrease functionality of individuals afflicted with the brain disorder. 

       Often times, however, the models of the behavior of an individual or the models of a disorder oversimplify the complexity of the system of the brain to a significant degree at times. 

    Complex variables such as trauma, intelligence, the complex dynamics of mood and emotion, thought, and chemistry of the brain create a scenario that is hard to accurately predict within a simple model or dichotomous diagnosis such as bipolar disorder (manic\depression).  This is where the Ludic fallacy comes in. In an attempt to render a model of behavior out of a mental illness,  oversimplifications and a failure to account for the messier and less controllable variables often create innacuracies within the prediction and outcomes of a mental disorder. Factor in things like the complexities of human environments and relationships with other people, and the narrowness and oversimplification of models become evident in their failure to predict the progression and outcomes of mental disorders within patients, no matter how empirical the model is, because of the brain and the environment's sheer complexity.

       The second application is in regards to political systems and policy making.  Politicians and policymakers are notorious for gross oversimplifications in policies. In fact, narrow and simple laws almost always fail to account for messy and unpredictable variables in the problems they are trying to address, and as a result fail to adequately address many of them. Many policies have unintended consequences that can be detrimental to the objective of the policy or policy maker and may make waves in other areas of society and the nation that are often undesirable.  The problem with humans, is that many of us aren't capable of creating complex solutions to complex problems, and many of us are not effective at analysing and accounting for all the information of a situation or problem, nor can we adequately account for and adapt to all the variables of a situation or problem.

          In conclusion, the Ludic fallacy is an important thing to be aware of in dealing with complex systems, complex scenarios, and complex problems. Even with the usefulness of empiricism and the applicability of some models, many systems and problems are occasionally too complex for a rigid empirical procedure to adequately solve or address.