One of the elements I find most interesting is the distinction between ideological critique and the algorithm, which Galloway, in particular, describes, but also seems to inform Friedman.

When describing playing Civilization, Galloway notes the “soft racism” and questionable God view that informs the game, like the problematic “attributes” given to civilizations–like how the Aztecs aren’t “industrial–or the absence and simplification of many civilizations. To Civilization‘s defense, subsequent additions have addressed some of these issues, like the inclusion of more civilizations, like Polynesia, and dropping essentialist attributes for more civilization-specific qualities.  But, things like the progress narrative, the valuing of military dominance, the potential simplification of ethnicities, and the role of commerce and territory still pose potential problems, ripe for ideological critiques.

Galloway moves from this into what he calls the “third level” of critique, “informatic critique,” which he describes as a “formal critique rooted in the core principles of informatics that serve as the foundation of the gaming format” (99). He asks, “whether it [Civilization] embodies the logic of informatic control itself” (101). Though I still had some trouble ultimately figuring out what Galloway meant by this, I think it reflects the way a phenomenon gets enacted by a computational system.

For example, when discussing history, he writes, “the more one begins to think that Civilization is about a certain ideological interpretation of history. . .  the more one realizes that it is about the absence of history altogether, or rather, the transcoding of history into specific mathematical models” (103). In other words, this informatic control is less about a specific human interpretation of history as it has operated in the world, and more about how a computer enacts the algorithm of history in its own medium.

Similarly, he writes on racial identity, “The construction of identity in Civilization gains momentum from offline racial typing, to be sure, but then moves further to a specifically informatic mode of cybernetic typing: capture, transcoding, statistical analysis, quantitative profiling (behavioral or biological), keying attributes to specific numeric variables, and so on” (102).  Here, race becomes translated into the systemic languages of computational technology, and as Langdon Winner might put it, such technology has a “politics.” The way a computer enacts systems (of race, history, etc.) lends itself to particular actions or manifestations.

In this way, as Galloway argues, “the game critic should be concerned not only with the interpretation of linguistic signs, as in literary studies or film theory, but also with the interpretation of polyvalent doing” (105). Again, I am still not quite sure I follow Galloway, especially with his sense that informatic critique is in some conflict with traditional ideological critique. Personally, I think that this “informatic control” still has a level of”procedural authorship” from the human designer as Wardrip-Fruin argues. In other words, the logic of computational systems has certain tendencies, but human authors also have flexibility within those systems. We see this with machine learning, for example, as the lack of people of color, or sensitivity to people of color, in design teams often results in racist algorithms, but this is not inherent to algorithmic culture.

These informatic systems, also, require the human player to enact them, a point Galloway stresses early on. But Friedman also analyzes this player-machine interface, arguing that it produces a mutual “cybernetic consciousness,” in which the human player begins to process like the machine. As he writes, “the pleasures of a simulation game come from inhabiting and unfamiliar, alien mental state: learning to think like a computer” (135).

I do not quite follow Friedman’s full point, but I think that this sort of play does create a particular player experience. Coming from rhetoric, I think this type of play creates a rhetorical relationship, in which the human player learns to work with the computer audience (the game procedures) to enact a certain goal (victory). In this way, one may need to “think like a computer” in a general sense. One may learn, for example, that certain actions lead to certain pre-programed responses, some simple and direct and others more complicated. Learning these patterns, one becomes a more rhetorically astute player, imputing certain actions to achieve certain ends.

As a fairly experienced Civilization player, I tend to have a clear sense for what I need to do, picking choices (including my civilization type) that will lead to certain ends. If I want a military victory, for example, I’d pick a civilization with military bonuses, pick the “Honor” civic track, build military wonders, build barracks, befriend military city states, etc. As Galloway may put it, I’ve learned the algorithm.

And in a game like Pandemic, one has fellow human players, requiring us all to play against the system–here the board pieces and rules. This adds another layer of rhetoric: engaging, as a team, with(in) the algorithm.

But in learning these algorithms, and enacting them for a “victory,” I am complicit in enacting the ideologies, informatic and cultural, that such an algorithm contains. I find this worth ending on, as I often have a hard time listening to or reading problematic texts, but as Friedman points out, the abstracted (and interactive) play of Civilization eases this discomfort. Also, while semiotic issues persist in games like Civ, and these are often easier to see, informatic or procedural issues may be harder to read. This requires a certain critical literacy, as Stuart Selber may put it, that reads both semiotic and interactive elements.