Videogames and Scientific Revolutions
As I discussed in a previous post, videogames tend to take a very deterministic view of technological development. Nowhere is this more apparent than in the concept of the “Tech Tree.” While dedicated players and modders are usually quick to point out other flaws or deficiencies in games (often holding them to an almost absurd standard of historical accuracy), this strong thread of technological determinism is generally left unquestioned. I attributed this lack of critique to the fact that technological determinism is so deeply ingrained into Western culture, especially the culture of tech industries like videogames. So while the fact that a spearman has a slim chance of defeating a tank in combat may incite a minor revolt in some online forums, the fact that every culture on the planet, even landlocked ones, will develop sailing, optics, and the compass (and always in that order) never gets a second glance.
While technological determinism may still reign supreme in popular culture, for most scholars of science and technology, being called a determinist is a pretty serious insult (though as I mentioned last time, there are some scholars who make very convincing arguments in favor of some forms of technological determinism). As deterministic theories fell short of explaining what actually goes on with science and technology, scholars began to formulate new theories to explain what goes on inside the lab (the idea of the “lab” itself is somewhat of a contentious issue as well, but that’s another story).
One of the most significant early critiques of determinism was made by Thomas Kuhn (1962) in his book, The Structure of Scientific Revolutions. Although most people probably haven’t read his book, they probably are familiar to some extent with one of its main concepts, the “Paradigm Shift” or scientific revolution. While the term became somewhat of a meaningless buzzword in the 90s, a paradigm shift in the Kuhnian sense is not merely a “really big change.” It is the transition as one set of accepted scientific principles is abandoned in favor of a new set that more accurately explains the physical world. These old systems, once rejected, are often no longer even viewed as science, but as superstition.
Kuhn’s theory was a dramatic departure from the more Whiggish and deterministic theories of the time, which saw scientific development as a continuous, cumulative process, in which every scientific discovery simply added to what was there before. From a Kuhnian perspective, the work that we call “science” and the work of Ptolemy and other geocentrists that we often dub “superstition” is fundamentally the same kind of inquiry. The difference is that now, having shifted to a heliocentric paradigm, geocentric models seem foolish and backward – clearly not the work of true scientists.
Revolutionary science, like that of Newton, Maxwell, and Einstein is in contrast to what Kuhn calls “normal science,” which is what the vast majority of scientists do. Normal science is concerned with taking the principles of the accepted paradigm and applying them to the physical world with ever-increasing precision. In other words, most scientists don’t start an experiment expecting something amazing to happen. In fact, most are fairly sure of what their results will be, they just want to see if they can prove it. Normal science is more like puzzle-solving, and a proper puzzle should be difficult, but have a easily recognizable solution. If you didn’t know what a solved Rubik’s Cube was supposed to look like, you would have a fairly hard time solving one.
While normal science is usually linear, cumulative, and predictable, it is an important part of scientific development. By challenging themselves with more and more complicated puzzles, scientists develop methods and instruments that are precise enough to detect anomalies – phenomena that the current paradigm is incapable of explaining. When enough scientists are able to observe these anomalies for themselves, the current paradigm can be challenged and a scientific revolution can take place.
Kuhn gives the example of the discovery of Oxygen. Before its discovery, chemists explained fire as the release of a substance called phlogiston. Combustible items like wood were considered to be rich in phlogiston, which was released into the air when they burned. To explain why flames burn out in closed containers, chemists theorized not that something in the air was being depleted, but that the air could only hold so much phlogiston before it became saturated. Phlogiston was essentially “anti-oxygen.”
As chemists refined their tools and experimented on new materials, they began to encounter anomalies. Magnesium, for example, becomes heavier after it is burned, though it has supposedly lost phlogiston. Some speculated that phlogiston might have some kind of “negative weight,” though this didn’t exactly fix all the holes becoming apparent in the phlogiston theory. As they devised new experiments to unravel this mystery, chemists began trying to create what they initially called “dephlogisticated air,” what we now call oxygen.
The discovery of oxygen demonstrates both the importance of normal science and how it differs from revolutionary science. It also complicates the commonly held notion of scientists as lone geniuses, having their “Eureka!” moments and single-handedly changing the world. While a number of eighteenth-century chemists seem to have created oxygen through their experiments, none of them recognized it as being anything more than really clean, breathable air. Even Lavoisier, the man who coined the term “oxygen” and realized that this gas disproved the phlogiston theory, didn’t quite get the process of combustion right. Who, then, “discovered” oxygen? Was it the man who first bottled it? The man who first named it? The man who first understood it as we do today? A Kuhnian model of science is far more messy than the tidy, deterministic models that inspired the videogame tech tree.
So what exactly would a game that used Kuhnian paradigms instead of tech trees look like?
Perhaps surprisingly, I actually think that such a game would look quite a bit like a game created back in 1993 – Master of Orion. Though it is often compared to Sid Meier’s more famous game, Civilization, which came out two years earlier, Master of Orion manages to differentiate itself in a number of ways. Perhaps most notable (at least, to an STS person like me) is the way that Master of Orion handles science and technology. As with most games of this genre, technological development is one of the key factors to victory (though I would concede that this perhaps less so in Master of Orion than Civ, due to the importance of diplomacy and fleet deployment). However, unlike in Civilization, the player is not given a nice, neat tech tree to follow. In fact, the technologies that she can research are different each time she plays.
In Master of Orion, technologies are divided up into six different categories, such as construction, propulsion, or weapons. Depending on the race of creatures you play as, you may be more proficient in one field of technology than another. Based on these proficiencies, you are given a certain number of research options for each field, chosen at random. The more proficient you are in a field, the faster you make discoveries and the more options become available to you.
Giving the player a limited, random selection of technologies each game has a number of interesting effects on gameplay. The player can no longer try to find an “optimal” way to progress up the tech tree, but must instead make due with whatever his scientists happen to have available. Additionally, when two fleets meet, they often have dramatically different ship capabilities based on the priorities and proficiencies of the player (or computer) in question.
Another interesting aspect of technology in Master of Orion is that while each new advance has a cost in research points, simply paying this cost isn’t enough to acquire it. Once the initial cost has been payed, your scientists have a small percentage chance of making a “breakthrough.” As you spend more resources on the technology, this percentage will increase until, at last, your scientists make a new discovery.
I see a number of similarities that the game shares with Kuhnian models of science and technology. The division between the linear, cumulative base research cost and the less predictable “breakthroughs” is not unlike the distinction between normal and revolutionary science. Likewise, the randomness and unpredictability of technologies in Master of Orion seems to a much better job of capturing the idea of competing paradigms arising out of experimental anomalies than does a fixed path on a tech tree.
While Master of Orion is a much better fit for a Kuhnian model of technological and scientific development than other strategy games, it is still far from a perfect fit. This should hardly be a surprise, since I doubt that the developers had Kuhn in mind as they were designing the game (of course, if any Simtex people happen to be reading this, I’d love to get your input). Rather, the unusual technology mechanics seem to be designed to encourage diplomacy and espionage, which feature much more prominently in Master of Orion than they do in Civilization. Also, while research may not function in a purely cumulative way, the discoveries themselves generally do. You will never find your scientists working on the science fiction equivalent of Ptolemaic astronomy or phlogiston theory. Old discoveries, while eventually becoming obsolete, are never “disproved” in the way old paradigms are.
Still, while Master of Orion may not be a perfect model of Kuhnian science, it would make an excellent starting point for someone to make a game that was. It’s a shame that its mechanics didn’t have the same cultural impact that the tech tree has had, as I think it might have inspired some interesting kinds of games. Given the game’s following, however, I hope there might still be a chance that some intrepid designers might follow its lead and try their hand at letting go of the tech tree.
Thomas Kuhn, (1962). The Structure of Scientific Revolutions.