Games People Play: Game Theory in Life, Business, and Beyond

Recently, I completed Professor Scott P. Stevens’s 24-lecture course for The Great Courses © entitled Games People Play: Game Theory in Life, Business, and Beyond – Parts I & II. Though Professor Stevens is a Mathematician working at James Madison University, this course is taught under the Economics and Politics sections as these are the most frequent applications of game theory. Each of the 24 lectures is thirty minutes long for a total course time of 12 lecture hours. Professor Stevens presents this introduction to game theory as a survey course and often avoids complex mathematics (other than a few instances of basic calculus concepts) that is essential to the actual application of game theory to the problems discussed in the course.

Game theory has been a subject that crossed over into public fascination with the release of the Russell Crowe biopic film about Mathematician John Nash, a significant foundational game theorist. While Nash’s concepts were poorly described by the film’s writers, the significance of his contributions to the field was not. The beginnings of game theory start with another famous mathematician name John, this one the exceptional genius and polymath named von Neumann. He and an economist colleague, Oskar Morgenstern, wrote the modern masterpiece on the subject of games: Theory of Games and Economic Behavior published in 1944.

Professor Stevens defines game theory as “the study of strategic, interactive decision making among rational individuals.” “Any time,” he asserts, “people make decisions that affect others or in response to the actions—or even expected actions—of others, they’re playing a game.” Thus, ideas in game theory apply equally well to such mundane decisions as where to eat lunch as well as “earthshaking” decisions about the risk of nuclear war. Fundamentally, there are three components to any game: players, strategies, and payoffs. Throughout the first lecture, we learn that the concept of games applies to almost any facet of life. Professor Stevens presents various circumstances under which game theory can be applied in fields as diverse as the military, politics, biology, NASCAR, and business strategy.

To better understand games, the instructor presents a simple game. You are given $100 and a button that you can push. Another one hundred people are given the same and each of you is unknown to the other. If you or any of your competitors push your button every other player loses $2; if you lose money because others push their button, pushing your button will cut your losses in half. While it is rational for no one to press their button and take home the $100, studies show that most people will press the button. Another example of seemingly irrational behavior was demonstrated by Max Bazerman at Harvard Business School who taught Wall Street Investors to think ahead by auctioning off a $100 bill. The winning bid was $465.

Another classic example that applies to game theory is the Federal auction for licensing of the radio spectrum. Historically, the US tried many approaches to the sale of the radio spectrum that failed, in some cases miserably. Game theorists stepped in and created a multi-objective auction structure that successfully raised over $400 billion for the US Treasury in its first 5 years. This is one example of many, in which the application of game theory has shown to be advantageous in analyzing and approaching strategic decisions.

The basics of game theory are fairly simple to explain. Every game has three basic components: players, strategies, and payoffs. A player is a decision maker in the game. A strategy is a specification of a decision for each possible situation in which a player may find him or herself. A payoff is the reward or loss a player experiences when they follow their respective strategies.

Another distinction regards the type of game. For example, when all players may “move” simultaneously without knowing what the other player will do. Consider the simple childhood game, “Rock, Paper, Scissors”—this is a rather crude example of a simultaneous game. Sequential games are another variety. In a sequential game, one player moves first, giving other players some knowledge about their choice. A simple example of a sequential game is the familiar board game chess. A familiar term to many in the public is the “Zero Sum Game” which is also a type of game in game theory, although it is a bit different conceptually than what the common understanding might indicate. Zero sum games occur when all of the losses and all of the gains of all players are added up and equal zero. This is often evident before the game begins.

Other classes of games include: Constant Sum Games, Symmetric games, Perfect information games, Repeated games, Signaling games, Cheap talk games, Mechanism design, Bargaining problem games, Stochastic games, Large Poisson games, Nontransitive games, and Global games. Professor Stevens introduces many of these concepts (though not all of those listed) but only some are explored in-depth. To give my readers complete non-disclosure, these games can often be very complicated to understand but the instructor is very good at guiding one through the lecture. However, to truly understand these concepts, repeated listening and perhaps further reading might be necessary—they certainly would be for me!

The course expands upon these basics to examine more complex aspects of games such as strategies, threats, promises, brinkmanship, incomplete information, and chance. This array of factors in decision making, as presented in game theory, has applications in fields as diverse as climate change, voting, market entry, price setting, cooperative behavior and many more things that are beyond the scope of this review.

Without delving too deep into the topic, it might shed a little more light on the nature of the game theorist’s work by examining a few of the aforementioned complicating factors that inhabit even simple games. For example, strategies come in two varieties: pure and mixed. Pure strategies specify an action for every possible situation in the game. There is no random component to a pure strategy. Mixed strategies, however, does include some randomness as a probability is assigned to each pure strategy—and since probabilities are continuous there are an infinite number of mixed strategies available to the player. A variant of the mixed strategy is called the totally mixed strategy in which only positive values are assigned to every possible pure strategy.

The next concept we will examine is that of the threat. Professor Stevens explains that, in game theory, a threat is the equivalent of saying “Do what I want or I will make things worse for you than you would otherwise expect.” Promises, on the other hand, are the equivalent of saying, “If you make this choice, I will respond with a choice that you’ll like—something that you wouldn’t normally expect me to do.” Promises and threats are therefore, conditional.

Games of incomplete information are those in which not all of the players know the structure of the game—players might be uncertain about possible strategies or payoffs of other players. These require complex analysis and can have catastrophic consequences for some players. Finally, brinksmanship might best be illustrated by thinking about the Cold War—because this strategic element means to push dangerous events, such as the proliferation of nuclear arms, all the way to the “brink of disaster” (think about the Cuban Missile Crisis) in an attempt to achieve the most positive outcome in the game.

There are numerous topics in even a survey of game theory. A simple summary of such a survey is necessarily incomplete. However, I feel that I would be remiss if I did not include one of the most famous elements of game theory in my little muddled examination: the Nash Equilibrium. Professor Stevens explains that the way the movie A Beautiful Mind, starring Russell Crowe, explains the Nash Equilibrium is actually incorrect. The movie has Nash explain his equilibrium in terms of a dating conundrum among a bunch of competitive men. The solution the character in the movie comes up with is, unfortunately, not a Nash Equilibrium. So what is it? Well, first things first: what is an equilibrium in the game theoretic sense of the term?

An equilibrium implies some kind of balanced situation. In economics and other rational decision-making, equilibria are defined by their properties. British economist Huw Dixon as described three basic properties of equilibria: 1) Players’ behavior is consistent. 2) No player has any incentive to change their behavior. 3) Equilibrium is the stable outcome resulting within some dynamic process, i.e. the game under consideration.

The simplest explanation of a Nash Equilibrium is by example: John and Ted are in a Nash equilibrium if John is making the best decision he can, while also accounting for Ted's decision. At the same time, Ted is also making the best decision he can, while also accounting for John's decision. A definition of this concept is as follows: “[Nash’s] theory says that in non-cooperative games when there are two or more players, and each player knows what choices the other players face, there is a Nash Equilibrium if all players have chosen a strategy where they can't benefit by changing their strategy.” (from Nash Equilibrium in Economics)

One last important point is that Professor Steven’s lecture series is mostly conceptual and made for the intelligent layman. It ignores a lot of complicated mathematical proofs. To illustrate what I mean, here is an example of the mathematics involved in the proof of Nash’s Equilibrium. I tried to paste the mathematics, but the characters would not translate to the Blogger post, so please follow the link to the Wikipedia page just to see an example of how complicated the proof is for work like Nash's and why he deservedly received a Nobel for Economics for his work.

Likewise, there is a lot more complicated mathematics involved in computing the various probabilities in a decision matrix, finding the equilibria of various kinds in any non-cooperative game, and many other instances. This is fully disclosed by the instructor. Despite this, the Great Courses lecture series on Game Theory, Games People Play is fun, enlightening, and broadens the mind in the understanding of the complexity of decisions—particularly those facing our business and government leaders on a daily basis. While I was listening to it, I actually felt smarter! Then I began to try to summarize the material presented in the lecture series and felt the opposite effect! I will admit some might find it boring, but if you enjoy the topic of decision making or complex systems, or if you just enjoy an intellectual challenge, I can guarantee that you will benefit from at least a casual listen to this lecture series.
As always, happy learning! Work hard to get smarter every day. After all, that is what a learning life is all about!
I would love to hear any of your comments as always.

Philosophy of Science - Part III

Thomas Kuhn

Thomas Kuhn is probably best understood as a historian of science rather than a philosopher of science. His book, The Structure of Scientific Revolutions, however, is a significant text for an understanding of the philosophy of science. Prof. Kasser described a pattern Kuhn discovered in the history of science—“normal science punctuated by periods of revolution.” Kuhn, according to the lecturer, dealt logical positivism its most severe blow.

Popper and the positivists focused heavily on the scientific method and the rationale by which science increases understanding about the world. However, for Kuhn, the underlying method and logic was not nearly as important as understanding how scientific views are adopted and modified. Kuhn believed that the way to study science itself is to evaluate the activities that scientists spend most of their time doing. Science generally had been taught in terms of its success only. Kuhn described this history being taught to future scientists as similar to brainwashing. Thus, science textbooks are filled with heroes, hyperbole, and drama about experiments. Kuhn argued that science is governed by a paradigm:

1. A paradigm is, first and foremost, an object of consensus. 2. Exemplary illustrations of how scientific work is done are particularly important components of a paradigm. Scientific education is governed more by examples than by rules or methods.

Paradigms create consensus concerning the way in which work should be done in a particular field and this is unique to science. Puzzle-solving is the work of normal science. This paradigm “identifies puzzles, governs expectations, assures scientists that each puzzle has a solution, and provides standards for evaluating solutions. It is generally assumed to be correct and doing science involves fitting into the categories of this paradigm, observations about the behavior of nature.

Thus, the paradigm is a test for the scientist in that failing to solve a puzzle reflects poorly upon the scientist rather than on the paradigm itself. Sometimes, a crisis occurs in a particular scientific community when its members lose their “faith” in the paradigm. According to Kuhn, these crises often occur as a result of anomalies and puzzles that scientists have repeatedly failed to answer. Thus, this is a kind of crisis of confidence. Kuhn argued that Popper’s view was that this was the normal state of science. Not so, according to Kuhn, if this were true science would fail to accomplish anything. Sometimes, paradigms may be abandoned in favor of new ones. Kuhn argued that this is a good thing for understanding and for science as long as it occurs rather rarely.

A lot of Kuhn’s assertions can be boiled down to “his insistence that rival paradigms cannot be judged on a common scale. They are incommensurable. This means they cannot be compared via a neutral or objectively correct measure.” Therefore, changing paradigms resembles something of a “conversion experience.” Since individual psychology has a lot to do with how individuals “convert” to a new paradigm, Hungarian philosopher Imre Lakatos referred to Kuhn’s model of science as “one of mob psychology.”

Imre Lakatos was the first to try to reconcile the rationalism of the “received view” and Kuhn’s “historicism.” His methodology concerning scientific research attempts to incorporate both Popper’s openness to criticism and Kuhn’s attachment to theories. Methodological rules retroactively judge science research as either progressive or degenerative. Paul Feyerabend, another significant philosopher of science, views Kuhn’s model as dull, mindless scientific activity. “In arguments alternately sober and outlandish, Feyerabend defends scientific creativity and epistemological anarchism.”

Sociology and postmodernism have also provided some insight into science. One researcher believed that science was often reduced to semantic absurdities. He entered a bogus scientific “white paper” as a presentation to a scientific symposium. These are supposed to be reviewed for originality and quality. His phony, meaningless presentation was accepted and he went through with the ruse undetected, only to reveal the deception later in an attempt to bee constructive.

All right, at this point, I’m ready to wrap things up. However, there is still an immense amount of material covered in the lecture series that I haven’t even mentioned. There are arguments about how values and objectivity influence science. Most importantly there is a lot of discussion about language and how language influences our construction and understanding of reality. This has been a major movement within philosophy. Consider now that the Massachusetts Institute of Technology houses their philosophy and linguistics programs in the same department. Unfortunately, the limitations of my meager skills to reduce this material to something worthy of being called a summary prevent me from condensing this material.

While these subjects and others are vitally important to a full understanding of the philosophy of science, I choose instead to devote the remainder of my final installment to subjects with which I am more familiar due to my own academic background: probability and Bayesian Theory.

The history of probability is quite interesting: its basic mathematical theory came about only around the year 1660. This might have been because people did not consider probability something that could be theorized about effectively. It also might have been the result of the Christian notion that everything is determined by God’s will. However, it was the great Blaise Pascal who really got probability theory going when someone asked him to solve some problems concerning dividing up gambling stakes fairly. It quickly spread through the fields of business and law.

Probability is critical to the conception of evidence in the modern sense. Probability was first associated with testimony: Opinions were considered probable if they were “grounded in reputable authorities.” Probability gradually changed enough to come to bear on the “causes” of natural sciences like physics and astronomy and was further utilized in “low sciences” like medicine. Such sciences relied on testimony until the Renaissance when diagnosis was established to differentiate from authority and testimony on one side and dissections and deduction used as proof on the other.

The 19^th century saw the rise of probability and statistics thinking which undermined deterministic trends. Governments kept better records of births, deaths, crimes and began to see patterns that were predictive. Statistics moved from disciplines like sociology into the hard sciences like physics. This then gave rise to quantum mechanics which held that the universe is governed by statistical laws.

The mathematics that underlies probability theory is relatively straightforward. All probabilities are given as a value between 0 and 1. A necessary truth is assigned the probability of 1. If we say that event A and B are mutually exclusive, the probability that one or the other will occur is the sum of their singular probabilities. Thus, if there is a 30% chance that you will eat pizza for dinner and a 40% chance that you will eat spaghetti for dinner, there is a 70% chance that you will have either. It is more complicated when events are not mutually exclusive. So the chance that you will have pizza or spaghetti (when you might also eat both) is the chance of pizza plus the chance of spaghetti minus the chance of both.

As probability theory continues to build in complexity there are three ways to interpret the mathematics. Frequency theories put probability in real world context and this is the most common use of probability within a statistical context. “Probabilities could be construed as actual relative frequencies.” This, however, creates a problem that the probabilistic account is “too empiricist” in that it connects scientific research too closely to actual experience:

A coin that has been tossed an odd number of times cannot, on this view, have a probability of .5 of coming up heads. In addition, a coin that has been tossed once and landed on heads has, on this view, a probability of 1 of landing on heads. Such single-case probabilities are a real problem for many conceptions of probability. One might go with hypothetical limit frequencies: The probability of rolling a seven using two standard dice is the relative frequency that would be found if the dice were rolled forever. We saw an idea like this in the pragmatic vindication of induction. This version might not be empiricist enough. The empiricist will want to know how our experience in the actual world tells us about worlds in which, for example, dice are rolled forever without wearing out.

Logical theories use probabilities as statements about relationships for evidence of phenomena. Probability, thus, gives “partial” or “incomplete” evidence similar to the way deduction provides conclusive evidence. Just like with deduction, probabilistic evidence must be consistent. If we have assigned a probability of 0.8 to p then we must make a 0.2 to ‘not p.’ “Having coherent beliefs is not sufficient for getting the world right, but having incoherent beliefs is sufficient for having gotten part of it wrong. Probabilistic coherence is a matter of how well an agent’s partial beliefs hang together.” On the other hand, if the evidence does not present a reason to prefer one outcome to another they should be regarded as equally probable. “The mathematics of probability does not require this principle, and it turns out to be very troublesome. There are many possible ways of distributing indifference, and it’s hard to see that rationality requires favoring one of these ways.”

Bayesian conceptions of probabilistic reasoning combine a subjectivist interpretation of probability statements with the demand that rational agents revise their degrees of belief in accordance with Bayes’s Theorem. Bayesianism attempts to combine the positivists’ demand for rules governing rational choice with a Kuhnian interpretation of values and subjectivity. In the process, Bayesianism has revitalized philosophy of science with respect to confirmation and evidence.

Bayes’s theorem begins with a subjective interpretation of probability statements. These statements are of conditional probability, meaning that they characterize degrees of belief of the person. Partly it resembles gambling behavior: “the more unlikely you think a statement is, the higher the payoff you would insist on for a bet on the truth of the statement. Your degrees of belief need not align with any particular relative frequencies, and they need not obey any principle of indifference.” The main importance is coherence in probabilistic coherence.

The Dutch book argument is designed to show the importance of probabilistic coherence. To say that a Dutch book can be made against you is to say that, if you put your degrees of belief into practice, you could be turned into a money pump. If I assign a .6 probability to the proposition that it will rain today and a .6 probability to the proposition that it will not rain today, I do not straightforwardly contradict myself.  The problem emerges when I realize that I should be willing to pay $6 for a bet that pays $10 if it rains, and I should be willing to pay $6 for a bet that pays $10 if it does not rain. At the end of the day, whether it rains or not, I will have spent $12 and gotten back only $10. It seems like a failing of rationality if acting on my beliefs would cause me to lose money no matter how the world goes. It can be shown that if your degrees of belief obey the probability calculus, no Dutch book can be made against you.

However, some rather ridiculous beliefs can maintain probabilistic coherence. Bayesianism uses a theory of how evidence should be handled which helps it become a serious scientific theory of rationality. The first element of this theory is the idea that confirmation raises the probability of a hypothesis. “E confirms H just in case E raises the prior probability of H. This means that the probability of H given E is higher than the probability of H had been: P(H/E) > P(H). E disconfirms H if P(H/E) < P(H).” This is done in a subjective interpretation of probability.

The second element critical to Bayesianism is that beliefs should be updated in accordance with Bayes’s Theorem. Non- Bayesians acknowledge the truth of Bayes’s theorem but don’t find it as useful as Bayesians.

The classic statement of the theorem is:

P(E/H)×P(H)

P(H/E)=

P(E)

.

The more unexpected a given bit of evidence is against a given hypothesis and the more expected it is according to the hypothesis, the more confirmatory the evidence of the hypothesis.

The course began by asking what it is that makes science special from a philosophical perspective. It is unclear how much we would like to separate scientific theorizing from everyday theorizing. Unlike those who would dismiss philosophy, it is hopefully apparent that philosophical inquiry exists on a continuum with scientific inquiry. One is helpful in understanding, clarifying, challenging, and enlarging the other. It is quite obvious that controversy will continue to exist about this matter.

Course notes for the lecture conclude, quite eloquently:

Philosophy, especially philosophy of science, is hard. It compensates us only with clarity, with the ability to see that the really deep problems resist solutions. But clarity is not such cold comfort after all. As Bertrand Russell argued, it can be freeing. When things go well, philosophy can help us to see things and to say things that we wouldn’t have been able to see or to say otherwise. 

I know that this has been quite a saga, quite an undertaking for this insignificant little blog. However, I hope, at the very least that it would plant the seed in someone’s mind that science is a useful tool but not the end-all be-all of understanding. It rests on certain axioms about the material world which should never be ignored. Keep thinking. And, as always, happy learning!

I am so glad this one is over.

Philosophy of Science - Part I

Philosophy of Science

**WARNING: The following review of materials for a course in the philosophy of science is necessarily long and exhaustive, replete with the confusing jargon of both the fields of philosophy and science, as well as the unique jargon that emerges when the concepts of each field of study is unleashed upon the other. It will require patience and time to wade through these waters, but for those interested in this essential inquiry, the reward will be well worth the effort—S.I.P. Blogger. 

“Getting the Course” [Just skip the first 3 paragraphs if you only want to see material review.]

Around this time last year, my brother was looking for some intellectually challenging audio material to listen to during his daily commute, which is an hour and a half one-way. We’ve both been frequent listeners to audio books of non-fiction and literature; however, our true commute-driven audio passion has been for university lectures, particularly those produced by The Teaching Company under the titular series The Great Courses. I have reviewed other courses in this series frequently on this blog. Ironically, I discovered The Teaching Company and their excellent lectures in my last semester prior to graduating with my Bachelor of Arts degree.

Of course, I quickly introduced the lectures to my brother and we have been loyal customers ever since. At the time, The Teaching Company was the only source of recorded lectures readily available. These days, there are numerous sources of such lectures: The Modern Scholar, iTunes U, podcasts, and individual university offerings such as MIT’s Open Courseware—just to name a few. I mention all of this only to explain to you that neither of us is an amateur when it comes to consumption of recorded academic lectures and coursework. So, when my brother was looking for something challenging last year, we did some research and comparison and finally settled on The Great Courses’ Philosophy of Science. The outline indicated that the course addressed topics we had both encountered but not understood or studied in previous settings: logical positivism, the problem of demarcation, Karl Popper, axioms, a theory of everything, etc.

After getting the CDs, I waited about a week and then asked him how the course was going. Now, not to bloat his ego, but we’re talking about someone who has an IQ in the 160 range and a nearly eidetic memory. “It’s rough, man,” he responded. “I hate to say it, but I’m just going to have to quit it. It’s just too abstract and complex—I find it hard to follow.” So, he did quit it. The first time either of us had shied away from a course. I was thoroughly intimidated. The course just sat around for the next year. Then, finally, about a month ago, I decided it was time to slay this beast. “Good luck, man,” said my brother, when I told him of my intention.

“Experiencing the Course”

On 8/3/2014 I completed The Great Courses series on Philosophy of Science which was presented by Professor Jeffrey L. Kasser, PhD. He is an Assistant Professor of Philosophy at Colorado State University. His undergraduate degree is from Rice University and his doctoral study was completed at the University of Michigan. My completion where my brother failed was, however, a far cry from a celebratory occasion. Understanding the philosophy of science requires one to move in a circular (perhaps elliptical?) orbit around the same pertinent questions that have plagued the study from at lwawt 

At first, the 18 hours might sound slim for a full course on the philosophy of science. I can assure you it is not.

With the production style of The Teaching Company, ideas come quickly and elaboration even quicker. These lectures are planned and efficient. If you went to a university where the standard sixteen week course was 3 classes of 50 minute lectures per week, with alternating Fridays, then you remember very easily that this does not translate into the following relationship: (50 min x 3 days) + (50 min x 2 days) / 2 = a mean average of 125 minutes per week x 16 wks = 2000 min / 60 min/hr = 33.3 hours of instruction. That is quite a fantasy. I attended three state schools and five private colleges during my extended academic career and always found the same thing: At least the first 10 minutes were concerned with review of the previous lecture material. Another 15 minutes were typically used for answering student questions throughout the lecture or at the end of the course as well as various administrative matters (announcements, anecdotes, etc.) Finally, there were almost always two entire class sessions devoted to review of the midterm and final exams and two for the actual conduct of those exams.

All of this means that the typical classroom student loses (let’s be conservative) around 20 minutes of lecture/instruction time for each class—bringing the actual time down to 30 minutes per class session. Then, we must account for the total of 4 completely lost classes concerned with examinations (100 + 100 = 200). Thus, we arrive at the following calculation of actual time devoted to lecture/instruction in a typical 3 semester hour credit course: (30 min x 3 days + 30 min x 2 days)/2 wks = a mean average of 75 minutes per week x 16 wks = 1200 min – 200 min (the 4 days devoted to exams) = 1000 min / 60 min/hr = 16.7 or approximately 17 hours of lecture/instruction time in the typical course. This explains why we all had to study so hard and make outside office appointments with professors to review critical course concepts.

The course consists of 36 different thirty-minute lectures, each of which builds upon the last and is available as a set of DVDs, audio-only CD packages (our medium of choice), or audio download. Each lecture addresses a different aspect of the philosophy of science. Lecture titles include the following:

1)      Science and Philosophy, 2) Popper and the Problem of Demarcation, 3) Further Thoughts on Demarcation, 4) Einstein, Measurement, and Meaning, 5) Classical Empiricism, 6) Logical Positivism and Verifiability, 7) Logical Positivism, Science, and Meaning, 8) Holism, 9) Discovery and Justification, 10) Induction as Illegitimate, 11) Some Solutions and a New Riddle, 12) Instances and Consequences, 13) Kuhn and the Challenge of History, 14) Revolutions and Rationality, 15) Assessment of Kuhn, 16) For and Against Method, 17)     Sociology, Postmodernism, and Science Wars, 18) (How) Does Science Explain? 19) Putting the Cause Back in "Because,” 20) Probability, Pragmatics, and Unification, 21) Laws and Regularities, 22) Laws and Necessity, 23) Reduction and Progress, 24) Reduction and Physicalism, 25) New Views of Meaning and Reference, 26) Scientific Realism, 27) Success, Experience, and Explanation, 28) Realism and Naturalism, 29) Values and Objectivity, 30) Probability, 31) Bayesianism, 32) Problems with Bayesianism, 33) Entropy and Explanation, 34) Species and Reality, 35) The Elimination of Persons? and 36) Philosophy and Science.

I included this long list for a quite obvious reason: Simply looking at the titles of lectures in the course provides quite a bit of information about what you can expect as you progress through the 18 hours of philosophical and scientific material.

The first thing that stands out is that the title of the first and last lectures in the series are very similar, simply transposed. What you can deduce from this is that philosophy not only influences scientific practice but the relationship is “give and take” with science having a strong influence on developments in philosophy as well. Another glance at the titles will reveal some of the major names involved in the development of a philosophy of science: Popper, Einstein, and Kuhn. Finally, by looking at the last several lecture titles we can reasonably predict that probability, and particularly, Beysian probability figure prominently in the later trends of thinking in philosophy of science.

We often place an intrinsic faith in science seen in our acceptance and integration of technology into our daily lives. Yet we also know that science is sometimes done poorly and its theories proven to be accepted erroneously. So it’s good to think about science—how it relates to our society, culture, as well as to us individually. A course in the philosophy of science attempts to use the tools of philosophy to reflect on these things.

Furthermore, philosophy can be used to evaluate the assumptions upon which science is based. Should we accept as axiomatic the assertion that there is a material world and furthermore that we can know, that is, predict its behavior based on historical observations) anything about it?  Many scientists would obviously argue that we should and we can, based primarily on the value judgment that doing so has proven useful—that it’s pragmatic—based on the outcomes of scientific advancement.

In their recent book The Grand Design, physicists Stephen Hawking and Leonard Mlodinow (2011) argued that philosophy of science is dead. Indeed, Dr. Kasser allows that most of the philosophy of science was done prior to the 20^th century and what remains today is largely semantics. However, a truly curious and skeptical mind should be cautious about accepting statements like Hawking’s and Mlodinow’s.

Yes, our materialist perspective has proven very useful in examining our little corner of the universe, and yes, it is the best explanation we have now. Yet, failing to keep an open mind about the possibility that we are wrong (and there is always, always the possibility that we are wrong) can lead to the kind of dogmatism in science that has been so vehemently criticized in religion. The first time this really hit home for me was (no, not when I was watching The Matrix) several years ago when I happened upon Dr. Nick Bostrom’s (2003) paper, “Are You Living in a Computer Simulation?”Bostrom’s thesis is presented so clearly in the paper abstract, there could be no better summary:

This paper argues that at least one of the following propositions is true: (1) the human species is very likely to go extinct before reaching a “posthuman” stage; (2) any posthuman civilization is extremely unlikely to run a significant number of simulations of their evolutionary history (or variations thereof); (3) we are almost certainly living in a computer simulation. It follows that the belief that there is a significant chance that we will one day become posthumans who run ancestor-simulations is false, unless we are currently living in a simulation.

Note that the definition of posthuman is somewhat contentious. Bosterom generally refers to posthumanity in terms that it has developed the capability to exceed material and energy constraints due to technology. While this topic is a slight digression from the main focus at hand, the point I wish to make I that philosophy still has plenty to say about science and technology and their applications.

“Philosophers & Philosophy in Science”

Chances are, if you’ve ever had a course or series of courses in research methods, you will have had at least some exposure to our first prominent philosopher of science: Karl Popper. (Please resist the urge to call him John Popper, the singer/songwriter and supernatural harmonica player for Blues Traveller. Karl Popper was a teacher at the London School of Economics and he was originally from the lively intellectual city of Vienna. Popper’s unique insight was the concept of falsifiability. Inductive reasoning presented a difficulty in that no matter how many confirmatory observations a scientist makes, he or she can never prove something to be universally true, such as all ravens are black. However, according to Popper our hypothesis can be falsified. One observation of a white raven falsifies the hypothesis: All ravens are black.

This was also Popper’s answer to the demarcation problem—we’re doing science if and only if our hypotheses are falsifiable. This helps us to further distance genuine scientific inquiry from pseudoscience. Unfortunately finding this distinction continues to be a problem for those in the general public—such as people who buy “magnetic energy bracelets.”

In the concluding post, Philosophy of Science II, I will look at the following topics and how they relate to our basis of the philosophy of science: Einstein, Classical Empiricism, Logical Positivism (such as A. J. Ayer’s), Holism, Hume and Induction, Kuhn’s historical perspective, sociology of science, postmodernism, laws, reduction and physicalism, scientific realism, probability, Bayesianism, and entropy.

The Inexplicable Universe with Neil deGrasse Tyson

The Inexplicable Universe with Neil deGrasse Tyson

Recently, I completed viewing Neil deGrasse Tyson’s Teaching Company lecture series The Inexplicable Universe which is currently available on Netflix streaming. Dr. Tyson is one of the great communicators of scientific ideas to the general public since Carl Sagan. He evangelizes proper science frequently on television shows such as The Colbert Report. His most recent exposure to the public was in the form of the revamped, contemporary version of Cosmos: A Spacetime Odyssey, the original version of which was hosted by the aforementioned great astrophysicist Carl Sagan. Dr. Tyson has distinguished himself through his great willingness to make scientific ideas (and more importantly attitudes toward science) more palatable and relatable than they might otherwise be.

The Inexplicable Universe is divided into six 30-minute lectures: 1) History’s Mysteries, 2) The Spooky Universe, 3) Inexplicable Life, 4) Inexplicable Physics, 5) Inexplicable Space, and 6) Inexplicable Cosmology. As I said earlier, I watched this series on Netflix which means I could only view the lectures. Should you choose to purchase the course from The Teaching Company, it will, like all of their courses, likely include a course outline with more in-depth notes and bibliographical references for further reading. Of course, you choose your level of involvement, so it is not essential to complete the readings or view Dr. Tyson’s notes and comments to understand and benefit from the lectures.

I’ve seen Dr. Tyson lecture and sit for interviews numerous times and I must say that in this Great Courses series he is at his finest. With the first lecture, “History’s Mysteries,” Dr. Tyson reviews myriad problems from the history of science. These puzzles were only solved through the application of modern science and its focus on experimenting rather than pure reason. Dr. Tyson walks us through the solution to many of the mysteries of the past which were solved using science and have become almost mundane at this point. A great example is 18^th century scientists’ insistence on the existence of ether, an invisible substance through which sound waves travelled. This was later proven to be wrong. That is, scientific rigor in experimentation (specifically, the Michelson-Morley experiment) demonstrated that light travelled at the same speed all of the time; therefore, the ether that was supposed to transmit light in wave form didn’t do it.

Lecture 2 is titled “The Spooky Universe” and generally covers quantum mechanics and fundamental particles, explaining how fantastical many of our accepted concepts are. The third lecture, “Inexplicable Life,” talks about the uniqueness of human life in the universe and the conditions that allow life to flourish, as well as the possibility of life outside of our Earth-bound existence. Lecture 4, “Inexplicable Physics” might be the most interesting of the six-part series. Dr. Tyson reviews the development of the field of physics and the search for a unifying theory such as “String Theory.” The fifth lecture is “Inexplicable Space” and it reviews humankind’s search for understanding of the cosmos. The most fascinating bits in this lecture cover dark energy and dark matter as well as the theoretical experience of being at or near a black hole. The final and sixth lecture “Inexplicable Cosmology” goes into depth about the current edges of study in cosmology. The multiverse, antimatter, tachyons and other theoretical advances of the past few decades are covered in Tyson’s inimitable style.

So that is a brief review of some of the content of The Inexplicable Universe. I had been exposed to most of its ideas from other books, lectures, and even podcasts; however, I have to give a strong recommendation for this lecture series because of its accessibility. It is one of the few series that talk about such complex ideas that requires no previous exposure to mathematical or scientific ideas. All you need is an attentive and open mind and you will gleam something or many things from the lectures. As always, happy learning!

Understanding Complexity by Scott E. Page, Ph. D.

I recently completed Understanding Complexity from The Great Courses lectures produced by the Teaching Company which, as the title suggests, primarily concerns complexity science. The lectures were written and presented by Dr. Scott E. Page who has the fascinating title of “Leonid Hurwicz Collegiate Professor of Political Science, Complex Systems, and Economics” at the University of Michigan. So, how does one become an expert in complexity? Page completed his BA in mathematics at the University of Michigan, then an MA in mathematics at the University of Wisconsin, an MA in managerial economics from Northwestern University. He later earned a Ph.D. in Management Economics and Decision Science from Northwestern as well. I didn’t look up his dissertation but during the lecture series, he stated that his doctoral research was in game theory.

The course is divided into twelve 30-minute lectures and includes a course guide containing the professor’s additional notes and suggested further readings and resources. Since absolutely no one has suggested that I do so, I have decided to rank these source materials for SIP blog posts on a simple scale from 0 to 10, with 0 indicating I could find no redeeming value whatsoever in the course, lectures, book or other resource used as source material. On the other hand, 10 means I am prepared to form a cult based around these teachings. I would give the Understanding Complexity lectures a solid 7. 

Professor Page begins by making a distinction between system complexity and a system that is just particularly complicated. Four factors must be present to indicate that a system is complex: 1) It has a population of diverse agents that are 2) connected. They also exhibit behaviors and actions that are 3) interdependent and 4) they must demonstrate adaptation. 

One or the more insightful concepts of the course comes in the second lecture which describes evolutionary processes and the creation of diversity. In evolution new characteristics develop through mutation or sexual recombination. Since there is no intentionality in the process of evolution there is no bias for a particular search direction. Thus, evolutionary “search” takes place against the backdrop of an “evolutionary landscape.”

It is useful to think of each of the types of landscapes (simple, rugged, and/or dancing) as problems and the solution is to find the highest peak in a given landscape. Simple landscapes are like Mount Fuji—little variation of terrain, a steep slope straight up to a single peak. Rugged landscapes are like the Appalachian Mountains—there are many “local” peaks but finding the single highest peak will take some exploring and effort. Finally, a “dancing” landscape has local peaks and valleys (like its rugged counterpart) but it also changes with time. Dr. Page has us visualize being an extremely myopic hiker trying to find the global (or maximum) peak in the mountain and this serves as an allegory for evolutionary exploration. 

Now, I realize that the explanation I’ve given is neither clear nor concise but that is what’s great about Professor Page’s lecture series: He gives detailed elucidations with such clarity you almost think you understand the concepts until you start writing your blog posting and see that it was not as easy as he made it look. 

One last parting shot at communicating an idea that doesn’t seem like garbled lunacy. Emergence, in philosophy, systems thinking, and science, is how complex systems develop from numerous, much simpler component parts. An example of an emergent phenomenon from every day life can be demonstrated in the phrase “birds of a feather flock together.” Hundreds of birds follow simple, instinctive roles (maintain precise distance, stay aligned, avoid predators) and create this much larger, distinct thing: a flock. Dr. Page really got my attention when early on in the lecture series, he suggested that human consciousness might be an emergent property of the brain. No single neuron, synapse, or glial cell has any of the properties exhibited by the macro-level phenomena of human consciousness; however, the billions of these cells acting in concert do seem to be the building blocks of this emergent phenomenon that allows us to understand ourselves as a unique “I” operating at will within the world. 

The series touches on many other topics from several different domains. I think it is particularly useful for systems engineers and other engineers to keep this perspective about complexity. Unfortunately, this course is given in one of the shorter formats for Teaching Company lectures which was disappointing to me after I saw how enjoyable and applicable the series was. Part of this subject matter was germane to my dissertation in graduate school. Since then, I had lost a lot of enthusiasm for such topics and for decision science and operations research in particular. This series helped renew my interest and passion for the field. 

As always, happy learning! And keep pushing on!

Sci Fi Literature and Academic Lectures

In at least one previous posting I have mentioned my love for professionally recorded college lectures such as those provided by The Teaching Company. Another great source of professional quality audio and video lectures is from Recorded Books’ The Modern Scholar audio book series. I have listened to numerous courses from each company and find that almost without exception each course yields a profound intellectual experience. Although with this posting I intend to review the latest course I’ve completed, just for the fun of it I thought I would list those courses I’ve at least listened to, sometimes delving deeper into the accompanying bibliographies and suggested readings. Incidentally, I do not own most of these discs but held a state library card and was able to obtain many titles from there or other loans.

The Teaching Company list is the longer of the two, comprising 29 lecture series. In some instances I have given the brief title. I have placed an asterisk beside titles that I have found particularly interesting. America’s Religious History, The Old Testament, The New Testament, The Great Ideas of Philosophy, Your Deceptive Mind: A Scientific Guide to Critical Thinking*, A Skeptic’s Guide to American History, Christian Religion and Fundamentalism, History of the Bible, Argumentation: The Study of Effective Reasoning, Great Leaders: Winston Churchill, Historical Jesus, American Civil War, Machiavelli in Context, The Self Under Siege* (by Prof. Rick Roderick an awesome scholar who is now unfortunately deceased), Philosophy and Human Values, Nietzsche and the Postmodern* (also by Prof. Roderick), Skepticism 101 (by Michael Schermer from Scientific American), Philosophy of Mind, No Excuses: Existentialism and the Meaning of Life*, Elements of Jazz*, Doctors: History of Scientific Medicine, Early Christianity, Hitler’s Empire*, Perspectives of Abnormal Psychology, Biology and Human Behavior*, The Story of Human Language, Understanding the Fundamentals of Music, Will to Power: Nietzsche, and The Art of War.

The Teaching Company titles can vary in length and depth. For example, if memory serves correctly, The Self Under Siege (my favorite lectures of all time), consists of eight lectures each approximately 45 minutes. The American Civil War, on the other hand, has sixty thirty-minute lectures in the series. The Modern Scholar list has 20 titles. Each title has two one-hour lectures on each of seven compact discs, making these offerings far more standardized in format and presentation. Another difference is that Teaching Company lectures are presented to a live studio audience while Modern Scholar lectures are not. As an aside to the above comments, I have tried to listen to The Self Under Siege at least once per year since I first bought it on cassette tape in 1998.

The Modern Scholar lectures I have completed, with asterisks by the favorites, are as follows: Understanding Movies*, Astronomy I*, Anthropology of Religion, Crime Scene Investigation I, The Philosophy of Thomas Aquinas, Philosophy of Religion, The American Presidency, Big Picture MBA, The Cold War, The Dead Sea Scrolls, Ethics (by Prof. Peter Kreeft), Genetics*, Jazz*, Literary Journalism*, Rock and Roll History I, Native America, Principles of Economics, Rethinking our Past (by Prof. James Loewen, author of Lies My Teacher Told Me—an excellent book you should definitely read), World War I, and From Here to Infinity: An Exploration of Science Fiction Literature.

It is this last title, Science Fiction Literature that I most recently completed and would like to explore somewhat in depth in the current posting. I am always trying to expand my intellectual palate when possible, so obtaining these lectures was not necessarily a priority for me as I have never been a frequent sci-fi reader. This was more about learning what makes others sci-fi fanatics. The course is written and presented by Professor Michael D.C. Drout of Wheaton College.

Science Fiction has a focus on realism even when describing such seemingly impossible technologies such as interstellar travel. The roots of the genre go as far back as Shakespeare’s The Tempest and Mary Shelley’s Frankenstein. But Jules Verne was the first true, great science fiction writer, imagining technology that has been realized but only dreamt when Verne wrote. H.G. Wells was another early sci-fi writer who used 19^th century technology to project future science and society and the relationship between people and animals (such as The Island of Dr.Moreau).

The 1930s saw the rise of science fiction magazines that gave rise to a new crop of writers in the genre. Amazing Stories and great sci-fi editor John Campbell’s Astounding Stories. The 1930s also introduced H.P. Lovecraft who explored occult, horror and shock within the science fiction framework. Lovecraft created a mythos by linking disparate stories to create a larger meta-narrative.

The 1940s sci-fi, argues Drout, was significantly influenced by World War Two. He looks at Isaac Asimov’s The Big and the Little and I, Robot; John W. Campbell’s Who Goes There? and (as editor) The First Astounding Science Fiction Anthology; Lester del Rey’s Nerves; and Theodore Sturgeon’s Killdozer! Characters in these stories have a militaristic orientation and there is an emphasis on scientific wonders being treated as mundane. One of the lasting implications from Asimov’s writings are the famous three laws of robotics: 1.A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2.A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law. 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

In the late 1940s and the 1950s science fiction was dominated by what Drout labels as the “Big Three”: Robert A. Heinlein, Isaac Asimov, and Arthur C. Clarke. Each of these writers created masterpieces that shaped sci-fi literature for decades. Heinlein, however, eventually crossed over into mainstream literature and was influential not only in areas like the space program and science and engineering, as well as “children’s literature and the counterculture of the 1960s.” In 1974 the Science Fiction Writers of America gave their first Grand Master award for lifetime achievement to Heinlein. His works include The Moon Is a Harsh Mistress, The Past Through Tomorrow: Future History Stories, The Rolling Stones, Starship Troopers, and Stranger in a Strange Land.

Probably my favorite lecture in the series is on 1960s and 1970s science fiction because this covers my favorite sci-fi author: Philip K. Dick. Drout refers to this era as the “New Wave” period of sci-fi. A key New Wave element concerns the increase of entropy which leads inevitably to the “heat death of the universe.” This actual abandon perspective of cosmology held that the universe is kind of “winding down” since the Big Bang, because entropy always increases. Therefore, everything will eventually “be reduced to a uniform soup of cold, dark matter.” This pessimism informs most sci-fi of the period. Philip K. Dick was somewhat influential on William Gibson who wrote the seminal cyberpunk novel of the 1980s Neuromancer which is probably my favorite sci-fi novel. Many of Dick’s novels and short stories have been adapted for the screen, most notably his story Do Androids Dream of Electric Sheep? as the cult-classic Blade Runner. Dick’s story is more nuanced with subplots which Drout does an excellent job bringing out in the lecture.

Overall, the lecture series was very well-presented. Drout has a captivating cadence and a masterful command of the material. I was disappointed that he did not really address William S. Burroughs’ place in science fiction. Although not primarily a science fiction writer, Burroughs’ satire of science fiction motifs far pre-dates those of someone like Douglas Adams, whom Drout does discuss. Of course, don’t get me wrong, I love Hitchhiker’s Guide to the Galaxy, except for any film adaptation of it. Of course, I understand how it is difficult to discuss Burroughs’ work in polite discourse on sci-fi lit. It’s pretty hard to discuss Burroughs’ work with any other human being without feeling like you need to go to confession afterwards. If you don’t know what I’m talking about, maybe you should check out Naked Lunch. Just don’t tell anyone I told you to. Sorry for the excessively long post. Anyway, happy learning!