Green. Tea. Mojitos

For years, I've been meaning to try making iced green tea with mint and lime. The idea just struck me as a good one, and a quick internet search showed that it would work. Not sure why, but I never got around to actually brewing it until yesterday, and when I was looking up iced tea recipes to get a sense of proportions, I saw a couple of people with the brilliant idea to mix it with rum.

Wow.

I'm not sure I ever want to drink anything again, at least not when it's summertime.

First up, the tea mixture, which is pretty freaking delicious by its lonesome.

2 quarts water.
8 green tea bags
Several sprigs fresh mint (maybe 6 or 7?)
3 mid-sized limes
2/3 to 1 cup sugar (depending on preference)

Bring water to a boil, then remove it from heat and add the tea bags and mint. Let steep for 8 minutes or so, occasionally swirling the tea bags and mint sprigs around (I'm not sure this does anything, I just get impatient waiting). Remove tea bags and mint leaves with a slotted spoon. Juice the limes (you may need more than 3 if you don't have a juicer/reamer) and add the juice and sugar, stirring until the sugar is completely dissolved. Allow to come to room temperature and then chill.

Fill a lowball glass with ice. Add a shot of white rum and top off with the tea mixture. Enjoy many in the company of friends.

Games, Language, and Meaning

Note: This is my second (and final) paper for my cognitive science survey course. It is a response to Robin Clark's Meaningful Games. This is ~4300 words including lots of armchair prognosticating about language and rhetoric as well as plenty of complaining about the ideas Clark presents in his book. You have been warned.

Within five minutes of Professor Eisenberg mentioning Meaningful Games in class, I had placed it in my Amazon shopping cart. I am not certain I had ever been more excited about a book. I am positive that a book for class had never excited me as much as the idea of this one did. You see, Robin Clark’s book proposes to “explore language with game theory”, an idea that immediately intrigued me as a reasonable, if not immediately apparent, approach to a topic that we tend to treat with a highly analytic eye despite its undeniably human nature.

I will say right now that I see no good reason to look at language as something that’s biologically evolved or that can be universally described. We spent time in class looking at animal communication that we described as being somehow sub-linguistic. We noted that many species, especially more evolutionarily advanced ones such as primates, seemed to have developed distinct cries for denoting various circumstances in the environment -- leopards, snakes, etc. The tendency to vocalize and share information with the surrounding world, then, would seem to be evolved. I do not believe that language (the fusion of semantics and syntax) itself is, though.

Language seems, to me, to be more like a tool. The basic components of this tool -- those surprisingly varied vocal notifications that animals of many advanced species use -- are available to less evolved creatures. They use them in their simple way, just like otters cracking open sea urchins with rocks and chimpanzees fishing for termites with sticks. But humans are more advanced. We perceive more of the world and recognize relationships in the world more acutely. Just like we combine simpler physical resources into more elaborate contraptions, why wouldn’t we devise ways of combining vocal emissions to more effectively and efficiently relate truths about our surroundings -- in both the immediate and abstract senses. Would anybody say that (specific) tool use is evolved?

Would anybody claim that Japanese macaques have somehow become genetically predisposed towards washing their sweet potatoes? That seems downright silly. Why, then, would I have a genetic determination to recognize noun phrases and formulate clauses? Some people may point to the similar structures of languages across the globe as a suggestion that we are built to process languages in a specific way. I would say that even these similarities can be explained by the tool metaphor.

First of all, tool use is taught generationally. Successive generations, being taught how to make and use the tools of their forebears, do not have to waste their lives re-inventing the basics. Instead, they can move on to expand on existing technologies or invent new technologies -- including linguistic “technologies” -- previously unimagined. Over time, some tools survive and others are replaced. Some tools are simply better than others, and people with superior technologies of the moment tend to spread farther and subjugate those with weaker tools. In this way, the technological ecosystem evolves concurrently with our culture.

Linguistically, we expand and evolve our tools by inventing new ways of describing new experiences and more effective ways of describing old ones. Today we see this primarily through the invention of words, but that’s the microevolution of a language. It’s quick and dirty and gets the job done at the moment. Is it unreasonable to think of the addition, removal, and adaptation of grammatical structures as the macroevolution of a language? A more flexible syntactic structure is going to allow for more efficient communication, and thus ease education and cultural advancement in other areas. Just as multiple civilizations concurrently developed nautical and agrarian technologies that eventually converged to similar solutions, it’s reasonable to believe that grammatical structures across independently developed languages would also converge to similar standards.

Why would these structures be similar? Because they need to be processed in the brain. We live in a physical world, and the features of this world, including our biology, can be modeled mathematically. As such, there are logical structures, perhaps nested hierarchies like those often used to describe modern languages, that may simply coordinate better with the design of our brains. Just like we wouldn’t build a scythe that takes three arms to wield, we wouldn’t keep around a language for long if it did not make concessions to the way we focus our attention and process information. Over time, it’s very possible that we could select for traits that allow individuals to use an especially important tool more efficiently. Certainly, I operate in a mental space that is almost entirely linguistic, but I still see no reason to think that language itself is built into us any more than a tendency to build and drive automobiles.

I apologize for this protracted rant, but it’s necessary to explain my excitement over the prospect of Meaningful Games. If language is, as I see it, a socially constructed tool and not some sort of Platonic Form that has always existed, then it makes little sense to analyze language as something independent of communication. Communication fundamentally occurs between rational agents, and rational agents tend to be aware of one another’s rationality. When I hear the words “exploring language with game theory”, I presuppose an account based on this principle. I think of explanation that would account for the semantic richness of and the syntactic flexibility of languages from a perspective of the ways we use language; a perspective that respects the fundamentally social nature of the topic.

Clark’s preface to Meaningful Games suited to wet my appetite quickly. He touches on some of these very same issues I mention, especially the communicative purpose of language. He recognizes that language is defined by its use and that its use is defined by social circumstance. He talks about Tarski and Grice and logical models and meaning; he talks about truth making and algebras and grammars and what these things mean in a context of multiple rational agents. He talks about social context and developing techniques to describe language by its use -- to evaluate it, essentially, as a tool. He said all of the right words to get me excited about what he had to say.

Clark then begins his book proper by discussing the concept of “mentalese”, the sort of universal, Platonic “language” of thought. Mentalese, as Clark describes it, is basically a set of constructs that describe the interactions of objects and agents in the world as we perceive it. These constructs are expressed in a sort of predicate form, relating state transitions on individual objects and causal relationships between these transitions. For example, Clark gets hung up on the notion of what it might mean for A to “kill” B. He denotes a predicate kill(A,B), which suggests that A caused B to die.

We can imagine a complicated series of such predicates and the potential to conjoin and disjoin them and forming propositions of them in first order logic to express even more complicated relationships. These predicates can then be compared to the world we know and we retain those predicate pairings we know to be true. We can even conceive of what a world would be like if other predicates held true, as well.

The problem that Clark has with Mentalese is fairly simple: as Clark describes it, Mentalese effectively embraces the computational metaphor. Mentalese is an analytic thought form, only serving to hold a representation of the universe that is dependant on a detached, sensory experience that may or may not accurately resemble the world as it truly exists. Verbal language, under the assumption of mentalese, is simply a way of translating our own mentalese into an intermediate language that another person can then place back into their own version of mentalese. But this has two problems.

First, of all, we obviously do not operate simply on first order logic. We regularly use constructs like “most” or “many” or “often” that are vague and difficult, if not impossible, to construct into first order logic forms. But first order logic is the most complicated logical system for which we have correct and complete proof systems for. We cannot just be computers, then, because we cannot simply compute much of what we store and communicate. More troublesome for Clark is the simple fact that a world where we only work in mentalese is a solipsistic one, where individual understandings of reality are isolated, answering only to some higher standard. In the real world, though, it appears as though meaning is derived socially.

Clark lays these objections out in such a convoluted form that I am not sure either of us understands where his problem with Mentalese actually lies. He walks through the uncanny valleys of the Turing Test and the Chinese Room en route to an objection that is social rather than computational. And he never quite seems to resolve the two issues. Clark spends a chapter examining the social nature of meaning before taking time to describe game theory and the way we evaluate the design of games and strategies. By the time he actually starts to talk about linguistic games, suddenly people are computers once more, though he may not realize it.

Part of the problem is that the first linguistic “game” that Clark constructs is not really a game at all. It involves the verification or falsification of statements, the very thing Clark suggests Mentalese is designed to do. (In)Appropriately enough, Clark spends an extended amount of time discussing how we might translate statements into propositions in first order logic and how players might take turns stripping down the logical operators to check the truth of the statement against some publicly shared model of the world.

After nearly 60 pages, Clark acknowledges that this is a trivial game and not particularly useful. What he does not acknowledge is that his “game” fails to be a game. There is no actual strategy to be played, no matter what Clark might suggest. A proposition in first order logic is either true or false with respect to a model. The “winner” is determined not by player behavior but by the model over which they are playing. In the middle of all of this, Clark establishes more troublesome trends that will persist throughout the rest of his games. For one thing, his players are not communicating with each other. They are projecting information into and extracting information from a void. More important, none of Clark’s players behave in any less computational a manner than those in his verification game.

These problems become most clearly apparent when Clark starts talking about common knowledge. This chapter begins with an example of generals trying to coordinate an attack on a superior force. Not wanting to risk attacking alone, they send messengers back and forth between camps ad infinitum, believing that they cannot be certain that a confirmation was received until they receive a confirmation in turn.

Clark extrapolates this problem to individuals trying to discuss going to see a dance troupe when one performance has been cancelled and replaced with another. The problem, in this case, revolves around the definite description “the dance troupe” as opposed to specifying which troupe by a unique name. In our fantasy land, both players know about the cancellation, but neither knows what the other knows. They want to avoid confusion, but they also want to save effort of using the full name for the troupe that is actually performing. Clark suggests that this requires that they model each other’s mental states. That is, A needs to know about what B thinks A knows. Which means A needs to know about what B thinks A thinks B knows, and so on and so forth.

For asynchronous (or mono-directional) communication, this is a reasonable (if absurd) problem. We need to be aware of what our audience may not know and make concessions to ensure clarity. Direct communication between individuals, however, is inherently synchronized. When conversing, we may attempt to model one another’s knowledge, but we know that we can count on our partner’s awareness of their own knowledge to ease the burden. Individually, we can recognize when uncertainty enters the picture and make explicit reference to it. We can request clarification when we encounter confusion. Such active error correction may require more effort than simply knowing what referents are in play during a discussion, but it certainly requires less effort than infinite recursion.

This is what I mean when I say that Clark, despite his earlier complaints, continues to treat people like computers. We are communal creatures who operate on heuristics. We share information, including information about our own knowledge. Moreover, we generally do not build exact models or find exact solutions to problems as our first course of action. Rather, precision is a last resort once our estimations prove insufficient. Why would Clark even waste space talking about an effort to build a perfect representation of the cognitive world of others? This is not something we even attempt in indirect communication, as heuristics of charity encourage greater clarity than may be necessary. No model is perfect. The only perfect map of a territory is the territory itself. Anything else, by necessity, involves abstractions meant to communicate only the most significant details at the appropriate scale.

It is at this point that I started to get frustrated with Clark’s writing and began wondering if and when we would get to the meat of things. Was there ever a point where we would look at “games” that were concerned with something more elaborate than ambiguity? So I read. And I read. And I read some more. Eventually, on page 197, when Clark was still discussing types of copresence and their usefulness in resolving ambiguity in pronouns and definite phrases, he provided these two sentences:

(19) Because it was broken, I returned the plate I had just bought to the store
(20)Because the plate I had just bought was broken, I returned it to the store

Clark’s response to the variation in this sentence is as follows:
“The pairing of (19) and (20) immediately suggests another level of strategic decision making, one more allied to the general problem of stylistics and rhetoric. I leave this as an open problem for the reader.”

Suddenly everything that led to this point made sense. Clark is not concerned with communication strategies in the same way I am. When I think about use of language between agents, my concern, first and foremost, is with the rhetoric that Clark ignores. I am intrigued by strategies we use in our diction and our phrasing to affect the way our words are perceived by others. I am curious about implicature and subtler ways we make our ideas more or less palatable to listeners, and the ways in which we listen for these cues in an effort to reduce their impact.

Clark, on the other hand, is solely concerned with notions of clarity and economy. He looks at meaning in explicit ways, ignoring implicature in favor of understanding how sentence structure and “public information” (the very existence of which, Clark questions) can alleviate ambiguity. He invents quantifications of linguistic economy in an effort to explain our use of ambiguous phrases. He then justifies these efforts by making games to describe how we spare ourselves effort in our speaking and the risks that we take in doing so. Even in this regard, on a playing field of Clark’s own creation, I am not entirely certain how his “games” hold up.

Let’s look at an example involving pronoun use. We start out with two players, the speaker and the listener. We then have a statement. Clark uses the example “An undercover cop was observing a suspect. He stayed in the shadows.” In order to eliminate lexical cues, we could generically use “X ____ed Y. He ____ed.” In any case, Clark looks at this game as one of information states. The speaker begins in one information state, in which “he” refers to either X or Y, depending on the situation. His goal is for the listener to reach the same state. The speaker then has four options. He can use a proper name in place of “he”, or he can use “he” to refer to whichever of X or Y he intends for the listener to identify with the pronoun.

If the speaker chooses a proper name, then the listener has an easy choice: she can recognize the subject of the second sentence as the one directly referenced. Communication succeeds, both parties benefit. If the speaker chooses to use a pronoun, the listener gets to choose which of X and Y she believes the speaker to be referring to. A failure to choose the proper antecedent leads to confusion and both parties lose. Choosing the correct antecedent results in a benefit to both parties.

Obviously, to make this a game worth playing, the benefit for successful communication using a pronoun needs to surpass the benefit gained from using a proper name. As mentioned earlier, Clark is concerned with a concept of “economy” in language use. Since it takes more effort to generate a proper name (or a more descriptive phrase) than it does a simple pronoun, it is beneficial to the speaker to use the pronoun. Supposedly, it is also easier for the listener to process the shorter phrase. With this in mind, he devises a game that effectively looks like this, with the speaker’s options listed along the top and the listener’s options listed along the side:

	Proper reference to X	“He” referring to X	“He” referring to Y	Proper reference to Y
X	(1, 1)	(3.5, 3.5)	(-2, -2)	(-2, -2)
Y	(-2, -2)	(-2, -2)	(2, 2)	(1.5, 1.5)

Where do these values come from? Imaginationland, of course! That’s not quite fair. Clark does have some rules that he follows to create the rankings. Successful communication, obviously, carries the highest benefit and unsuccessful communication the highest cost. Encoding an element as a pronoun provides a larger benefit as opposed to using a full name. More prominent elements (such as the subject of an immediately previous sentence) are “cheaper” to encode, increasing the benefit of that encoding. Not immediately relevant is the fact that pronouns are cheaper than descriptions.

Continuing to ignore the fact that the actual values are wholly arbitrary, this is why the highest reward comes from using “he” when the speaker wants to refer to X. Playing the game backwards, we see that this is the choice the speaker should make if, indeed, he wishes to refer to X in the second sentence. If the listener hears “he”, she will be inclined to assume that there is a 50% chance that the pronoun could be in reference to either X or Y. X’s prior prominence makes it the safer option. As such, if the speaker wants to refer to Y in the second sentence, he ought to make the reference explicit.

Does this final decision make sense? Mostly, again assuming that the context fails to provide further lexical cues. What doesn’t make sense is the reasoning that led to it. Specifically, why is the pronoun beneficial to the listener? She has to take the mental effort not only to process the auditory emission, but to attach it to some other concept. Depending on the situation, this could be a lot more work than processing an exact name. Pronoun use is not symmetrically beneficial. It is selfish on the part of the speaker.

Of course, this is not the only game that Clark plays. He looks at situations where individual words create ambiguity by carrying multiple definitions. He also looks very lightly at implicature through the lense of sarcasm and hinting/politeness. In these cases, he suggests that we can design games that use social context, familiarity, and/or focal points to create probabilistic strategies. Prior experience as well as physical and lexical context dictate our initial response to a word’s definition when there are multiple options. Familiarity determines our likelihood at properly interpreting sarcasm or recognizing a hint as such.

Of course, with every situation being unique, we can’t devise universal games for these sorts of problems any more than we can for pronoun use. But Clark thinks that the approach is still useful in the way that it grounds our use of language in a particular context. I do not. I do not believe that games are at all a necessary construct in recognizing how we generate meaning. I am not even sure this central question of meaning is a linguistic one. The bigger issue, though, is this: does anybody actually think this way when speaking?

Here we find the real problem with Clark’s attempt to leverage game theory on topics of meaning and ambiguity. Game theory requires that its participants are rational decision makers who are, at some level, aware of the game that they are playing. In an ordinary, conversational setting, such as those that Clark describes, I do not think that human beings can be described as rational actors. We tend towards preoccupation. If we are playing a game, it is one of minimal energy expenditure, and over thinking every lexical decision we make is certainly not a winning strategy in that situation.

In order for game theory to be applicable to a given situation, there needs to be a reason for maximization. In order for human beings to behave as rational actors, there needs to be meaningful cost or reward. There needs to be risk. Under these sorts of circumstances, we are more likely to take the time to explore our options and try to improve our expected result. Typically, conversation is not such a situation. We are free to identify and correct misunderstandings. Any serious consequences are not immediate and irrevocable, and any direct consequences of poor communication are not overly costly.

If we are looking for a situation where people play games with language, designing (and responding to) rhetoric is exactly such a situation. When we engage in rhetoric, as a writer or an orator, we work with an agenda. We manipulate language as a tool to promote that agenda, and our ability to use language and anticipate the response of our audience is what determines immediately our success or failure. As an audience, we try to identify linguistic ploys and focus on facts. The game is plain, but, as an example, I suggest my experiences serving jury duty.

In the summer of 2010, shortly before moving to Colorado, I was under going voir dire in the Hennepin County court system. Since I was preparing to leave the state and had a lot of preparation to do, I did not want to actually sit on a jury. Effectively, the attorneys and I were locked in a game. They asked questions. trying not to violate procedure or give away the case they were building but still seeking jurors who would be sympathetic to that case. I phrased my answers in such a way that, without lying or being contemptuous, I could suggest that I would not be easy to sway or take kindly to their efforts at persuasion.

Both of us had something to gain and/or lose. I might have to risk days of my life hearing a case I really didn’t have time to hear, and possibly a boring one at that. The attorneys were trying to find people who would be willing to consider the story they wanted to weave. We played the game with language, leveraging various grammatical forms and semantic particularities to implant opinions and ideas without violating the constraints of the situation. By acknowledging and responding to their rhetoric, I pushed the situation towards one that was favorable to myself -- and which I believe was favorable for the attorneys.

So, rhetoric is obviously a game, and likely a better game than the ones that Clark creates in Meaningful Games. As much as this helps explain my frustrations, the fact that I would have preferred this as a topic has no bearing on the quality of the book itself. Even discounting these desires, though, Clark’s approach and his games did not do much to think about the way I think about language or say anything novel about meaning. Maybe I would feel differently if I were a linguist, but Meaningful Games mostly just left me frustrated with Clark’s insistence on treating heuristic bits of human behavior with such an analytic eye.

By my estimation, Clark seriously inflates the value placed on economy of speech. The best reason to do so is simply that it lends credence to his arguments, but it also means he overcomplicates the entire issue. There is also the problem of incessant tangents -- about mentalese, garden path sentences, focal points, logical proofs, and anything else Clark thinks of as mildly relevant. While fascinating in subject, the added value is of little comfort when the stated purpose of the book comes to so little.

Had I entered with lower expectations, I may have enjoyed Meaningful Games. Clarks’ writing is, for the most part, accessible, and his examples tend to be light and entertaining. It takes a joy in itself and manages to cover large swathes of ground, even if much of it is tangential. I would actually consider recommending Meaningful Games to people with no prior knowledge of any of the topics contained within it, but certainly not to a person looking for a serious read on topics of game theory, language, or meaning.

Work Cited:
Clark, Robin. Meaningful Games: Exploring Language with Game Theory. Camebridge, Mass: The MIT Press, 2012

Vikings Post-Draft

The NFL Draft occurred over the past few days, and I was watching pretty contently through the first four rounds. Generally speaking, I really liked what I saw.

Things started with a bang on the first night. We used the Browns' fear that another team would trade up and take Trent Richardson to move back a single slot and pick up 3 additional late round picks. Then we grabbed Matt Kalil as we had intended to for months, no matter what Rick Spielman wanted everybody to think. Kalil is the top left tackle prospect in years, and while he's not Jake Long or Joe Thomas, he's immeasurably better than what we had (Charlie Johnson) or even what we have had for ages (Bryant McKinney). He's an athletic blind side protector who is intent on doing things the right way -- whether it's technique on the field or building up power in the weight room to improve his run blocking. Almost as important, it lets us move Charlie Johnson inside to guard, where a lot of people suspect he's a better fit. Along with some off season moves we made, our O line is suddenly adequate if not legitimately strong instead of one of the top liabilities on the team.

Later, we used some of the ammunition we got from that early trade to move back into the first round to pick up Notre Dame safety Harrison Smith. Smith was the consensus number 2 safety in the draft, and last season made it incredibly clear that we had nothing at the position. Smith worked with our coaching staff extensively at the Senior Bowl, and they fell in love with him. Not only his talent and his positioning on the field, but his presence in meetings and his leadership. He should be a day one starter and provide a serious improvement in our secondary.

Our secondary saw further improvement with Josh Robinson, CB out of the University of Central Florida. Robinson set the fastest 40 time at the Combine, running it in 4.29 seconds. On top of that, he put up 17 reps of 225 lbs on the bench press, more than many larger, supposedly stronger backs. He should provide a powerful jam at the line of scrimmage, and he has the speed to recover if he gets burned and make plays on the ball from the other side of the field, and he's a willing tackler. He's an early entry from a mediocre program, so he may not be ready to jump in and start immediately is up to question, but he could develop into something special.

The fourth round saw a number of interesting picks. First being Arkansas wide receiver Jarius Wright. I watched a lot of Hogs games last fall with one of my roommates who comes from the state. Wright is small and best fit to line up in the slot, where we already have Percy Harvin, so a lot of fans may not like the pick. I've seen him play, though, and he's nothing like Harvin. He's possibly faster and more explosive, even if he doesn't have the strength or dynamic ability in the open field. Most important, though, he's a great route runner, which can't really be said about, really, anybody else on the roster. Combined with his speed, this makes him a great deep threat down the middle. I'm honestly excited about the potential to line Wright and Harvin both up on the slot or, better yet, Wright in the slot and Harvin in the backfield and play games with opposing defenses.

Later in the 4th, we picked up a second Arkansas receiver, Greg Childs. Childs is 6'3" and possesses ridiculous speed (clocked at 4.38 at his pro day). He produced extremely well while healthy, but he tore his patella tendon in 2010 and tried to come back too soon, hurting his 2011 performance. Because of this, I haven't seen as much of Childs, but he's a prototypical number 1 receiver in terms of size and ability. Friends who have watched him insist that he's a first or second round talent if not for the injury limiting his exposure last season, and scouts seem to agree. He was a steal who could pay dividends for years to come if he adapts well to the pros.

Between those picks, we made an incredibly un-glamorous but essential decision with USC FB/TE Rhett Ellison. With Jimmy Kleinsasser having retired, we were seriously lacking in supplementary blockers. Current top TEs Kyle Rudolph and John Carlson are great receivers but are only adequate at best in the blocking game. Ellison didn't have a lot of buzz in the media, but Spielman insists that there were other teams planning on grabbing him in the fourth round. Ellison is a hulking guy who was responsible for making holes nearly every time he was on the field last year, and he did it well, considering the high power of USCs offense. I'm sure the Vikings saw plenty of tape on him when they were doing their homework on Kalil, and this is a pick that should pay dividends with AP returning from knee injury and Toby Gerhart being a less dynamic runner in general.

In the top of the fifth, we made possibly our most questionable choice, drafting another DB from Notre Dame. I really haven't been able to find out much about Robert Blanton, other than the fact that nobody seems to see him as a CB in the NFL, meaning he may move over to Safety next to his past and present teammate. Considering the decisions made up to this point, though, I'm going to express faith in the pick. Time will tell, and everything is a crap shoot at this point in the draft, anyway.

We finally started the hunt for a successor to Ryan Longwell in the sixth, where we grabbed Georgia kicker Blair Walsh. Longwell had his worst season in ages last year, missing six kicks, and it's fully possible that he'll continue to regress as he pushes on towards 40. Blair might get knocked for inaccuracy after going 21/35 last season, but 10 of his 14 misses came from 40 or more yards as Georgia kicked more than any other team in the FBS. Kicks that long are always a crapshoot for college players, and he hit a long of 56 yards, so he's got the leg. NFL conditioning and coaching should help his accuracy. It could be an interesting camp for the old guard in special teams.

I honestly don't know much of anything about either of our seventh round picks (UNC linebacker Audie Cole and Cal DE/DT Trevor Guyton) except that several scouts had fourth round grades on the both of them and both play positions where we can always use depth. Along with the bevy of undrafted rookie free agents we've already reached agreements with, they'll fight for positions throughout training camp and provide perspective on our current crop of players.

In short, we've become a much better team over the past 48+ hours. I'm not holding out that we'll be truly competitive, but climbing back up as 6-10 is certainly possible. We've got potentially strong pieces in place at positions where we had nothing. We won't have nothing to work with coming into the draft next year, meaning we can focus on depth and a much smaller number of holes. I feel good about being a Vikings fan right now. Much better, certainly, than I was after that dark, dark Packers game in November.

Gamification

Goddamn, I hate gamification. I'll admit, part of it is because every time somebody tries to shove Jane McGonigal down my throat (which has happened a lot over the past 15 months), I feel pandered to and underestimated as both a person who plays games and as a rational human being who expects people to actually back up their arguments (Malcolm Gladwell: not a credible source, even when you're not misrepresenting him). Mostly, though, the whole thing just takes an ugly view of humanity.

Gamification presupposes that the only thing we care about is our own sense of achievement. It suggests that the best way to get people to do things is to promise them immediate reward and recognition. It basically works to eliminate language of servitude from our lexicon in favor of personal growth.

Personal growth is bullshit -- at least when it occurs in a vacuum. If we abstract away the actual purpose of our efforts, replacing it with an augmented reality veneer that puts ourselves at the center of every action, then we won't actually learn the lessons that make us more Godly. Instead of coming to grips with our own fundamental insignificance, with the incredible value of the people around us and of creation as a whole, we will only grow and grow in our own sense of self-importance.

So, yeah, fuck gamification.

Games and Art

Most videogames are not art. I don't just mean "most videogames suck". I don't mean Madden or Call of Duty or other series that rehash the same principles under an annual release lack soul. I don't mean repackaged upgrades/expansions like Super Street Fighter 4: Ultimate Championship Edition are just cheap cash-in attempts. I mean legitimately good games that I love -- games like Final Fantasy VI, Ocarina of Time, or Mass Effect 2 -- aren't inherently art.

That's not to say that these games aren't, in a way, artful. There is skillful work of all manner in play in these games and others. There's writing. There's composing. There are models and environments to draw and render and animate. There's A.I. scripting and software design. Years ago, I would feverishly point out to these facets of game design and insist that games must be art. This agglomeration argument doesn't work for me anymore, though.

Many games have moments where they reach the level of art. There are scenes of catharsis and closure in adventure games and RPGs of all generations that (due to limitations of writing or presentation if nothing else) would lose their teeth if not for the connection that control gives you to the protagonist(s), and thus the world they inhabit. There are points in Mass Effect 2 and 3 where your decisions catch up with you and you're stuck having to choose between options you don't like with no idea of how things will pan out. Then you remember that, so long as you've been consistently good or bad, you'll almost certainly get a dialog option -- eventually -- that lets you satisfy all parties. But that doesn't make the game, as a whole, art.

In order for anything to be art, it must take advantage of the inherent, or at least prevalent, characteristics of its art form. For games, this means delivering messages and fostering ideas and discussions that are most effectively conveyed through the participatory nature of the medium. Few games are dedicated to this task, but it seems like examples of this are increasing, and I think that has something to do with the fact that we're finally beginning to understand this medium as multiple generations of people who grew up with it are finally working together to determine its future.

I think it's fair to take into account the technological context of a game when deciding if it's art. The original Legend of Zelda, for instance, seems to have a better claim to being art than any of its successors. Why? Because the entire game is exploratory. You begin helpless. An unfamiliar old man cautions you and gives you a sword. And you find your way and unlock the mysteries of the world around you on your own. You bomb walls and burn bushes and stab octoroks and, through cryptic clues, slowly discover the intention of the designers with as little overt instruction as possible. Lack of instruction was a common thing in older games, but generally there were people who gave obvious directions or level design that limited your options and made things pretty clear (I can't go to the left, I guess I'll go to the right). The Legend of Zelda had none of this, and that's part of what makes it so thrilling and frustrating to go back and play today.

For similar reasons, I'd call the original Metroid (and maybe even Super Metroid, if only because of Metroid's relative obscurity at the time) art. Nearly any time a game asks you to play with it and not just play it, I'd call that art. This falls apart in more sandbox-y games like Sim[fill in the blank], where developer intent is minimal, but I'd generally classify those more as toys than games -- a discussion for another day. Unfortunately, this is increasingly hard to do as genre norms and design conventions create a context in which we can figure out what a game wants from us without a whole lot of explicit instruction. It's still doable (this is what Jonathan Blow is trying to do with Witness), but it's harder.

Another example of how games approach art is by abusing, rather than obfuscating, the goal oriented nature of a "game".

As an example: At various points in the end of the classic SNES RPG Earthbound (also known as Mother 2), the developers break the fourth wall to ask you, the player, your name. Come the end of the game, it turns out that your characters, no matter how well leveled, cannot defeat Giygas. Instead, you need to use Paula's "pray" ability until, eventually, you, the player, pray for Giygas to die, causing him to take massive damage.

As a good little Christian boy, the intent of this was lost on me. "Of course praying can defeat evil," I thought. What was really going on was this: Shigasato Itoi, the creator of Earthbound, was trying to be subversive. The only reason that Giygas dies -- the only reason that these characters and this world can be saved -- is because the player wants it. The player doesn't even have to want Giygas to die for the sake of the characters, but only because he or she wants to finish the game. At the climax of the game, Itoi sucks you out of the moment by fantastically breaking the fourth wall and asks you to come to terms with the time and effort you've put into this ultimately meaningless experience.

Does it work? Not entirely. Is it admirable? Yes.

It's a technique that is accomplished infinitely better by Shadow of the Colossus, one of the best examples of games as art that I can think of. Some of what makes SotC great are the exploratory elements. The only instruction available to you is the beam of light that will appear to direct you to your next goal if you hold your sword up to the sun. The game world is large and empty and filled with small spots of quiet beauty that you can find if you're willing to just wander aimlessly.

The entire game itself consists of 13 fights with enormous creatures who you only learn how to defeat as you struggle to survive against them. You're never told explicitly why you're doing this, as I recall. It's just suggested that you're taking the only course of action you know to revive your lost love -- whose body you place on a stone slab inside a gigantic temple at the beginning of the game.

It's also suggested that what you're doing is taboo, and as your progress through the game you begin to get a sense of why. Every time you kill a Colossus, you're not only extinguishing the life of a magnificent being that, other than your intrusion, has lived in peaceful solitude for time immemorial. You're unleashing palpable darkness that both enters physically into yourself and gives rise to discomforting shades in the temple that serves as your home base.

But you have no choice. The nature of the game is such that you either have to continue doing this or put it down or simply ride your horse around the barren landscape as you try to decide between the two.

At the end, your misgivings are proved correct, and while your love is brought back, it's to life alone in this now completely empty country.

It's powerful and beautiful and perhaps one of the greatest games ever made. People have complained about the awkward controls, but they're meant to be. You're not a God of War or any other sort of ultimate bad ass. You may be a great warrior, but you're still on your own fighting against living mountains. It's not meant to be easy or fluid. It's meant to be gut wrenching and panic inducing, and the moment of triumph as a Colossus collapses to the ground and dissolves into nearly nothing is meant to be as total as the moment of conflicted-ness following it as you again see something ominous penetrating your soul.

Maybe less powerful, but likely more important, are games that ask us to think about the norms in gaming. This is what I see happening more and more, especially in small, one-shot indie games.

One of the most famous individuals in game design is Peter Molyneux. This is the man created the "god game" in Populous and took it to new levels in Black and White. He tasked players with taking on the role of the villain in Dungeon Master, and attempted to create a game world that would respond dynamically to the player's behavior in the Fable series. The thing about Molyneux is that, as much as for his games, he's famous for over-promising, and also for making promises and talking about ideas that gamers as a whole often don't care about. The use of the Dog as a surrogate HUD in Fable 2, for instance, or his talk about creating a sense of "touch" by using Kinect in Fable 3 (a feature that disappeared long before the game saw release).

Molyneux's lofty and occasionally absurd ambitions have given rise to a brilliant Twitter parody known as Peter Molydeux. This is a guy who asks questions like "What if your avatar was afraid of you and you had to gain his trust?". Kind of ridiculous, but sometimes, you just need to run with ridiculous ideas and see the result. Fortunately, game developers all around the country agreed with that sentiment, and a couple of weekends, we got the Peter Molydeux Game Jam, in which hundreds of developers/development teams spent a weekend making a game/prototype based on a Molydeux tweet.

There are half a dozen games about talking suicidal businessmen off of ledges. There are games about being a bear who needs to hug people in order to breath, but you will kill people if you hug them for too long. There are games in which a pair of lovers need to parkour their way out of a city but become distracted/incapable if they are too far apart. Most impressively, there are games like Recidivism, where you need to continually watch the death animation of every enemy you kill until they fill up the screen and/or you die.

For better or worse, videogames are violent, and rarely do they ask you to confront that notion. Again, there are instances (such as the airport scene on Modern Warfare 2 or, better yet, having to deal with the zombies of every person you killed during one of the boss fights in Metal Gear Solid 3), but these are isolated. Making games, even short, tiny ones, that ask us to think about and stare at the things that games tend to force us to do is good. It gets us to question why these activities are the only ones we engage in, and it asks us to open up our minds to new approaches.

The interactive nature of games can make for powerful storytelling in the traditional sense, but traditional design concerns make it relatively easy for player to simply escape the stories that game makers may be trying to tell. The attitudes that most people take into games simply aren't conducive to articulating the sorts of ideas that we see in books and movies. This is why the agglomeration argument doesn't work and why storytelling isn't the measure by which we consider games as art..

What games are good at is confronting us with ideas about leisure and how we spend our free time. This, then, is how games become art: by building into their structure questions about how and why we play them and what their limitations are. A game is are art when it changes the way we play and think about games as a whole.

Events like the Molydeux jam give me hope that people will take time to think about games at this level and to make statements about the state of gaming through games more regularly going forward. The importance of the ideas being expressed may not make immediate sense to people outside the culture, but that happens with all art, and it doesn't matter. Art isn't about appeal. It's about truth. And we're finally reaching a point where we're willing to pursue that.

Vikings!

I'm going take an extended brain dump about the current state of the Minnesota Vikings. I'll be doing another one later about the Timberwolves. Sorry to those of you who don't give a crap.

The Vikings are coming off a terrible season. Their 3-13 campaign has landed them the third pick in the draft, and we have far too many needs to be competitive in a year's time. Many of my thoughts hold true with what I wrote after their incredibly depressing loss to the Packers last November. The chief exception is that I no longer value Lorenzo Booker higher than Toby Gerhart (a handful of well executed trick plays do not make up for an awful fumbling habit).

We're in a rough place right now, waiting to see how AP can recover from torn A/MCLs and if Ponder can watch enough tape and get enough time in with Musgrave to take a serious step forward after an increasingly worrisome debut. Personally, I'm optimistic on both counts, but, hey, you've got to be optimistic about something.

In terms of legitimate good news, we've actually made some savvy decisions this off season that should give us flexibility moving forward, and the draft is strong in the places we need it to be.

First up, Chris Cook was acquitted. Is it very possible that he beat his girlfriend and quietly paid her to recant? Yes. Does he need to be a perfect citizen to be an ascending cornerback, perhaps our position of greatest need? Nope. Sad, but true. I mean, Ray Lewis killed a man, and the city of Baltimore still loves him. Our secondary is a mess, but at least we have one of the positions set with a viable talent who will hopefully be committed to reaching his potential and staying out of trouble after this scare.

Second, we smartly re-signed Erin Henderson to a one-year "show me" contract and moved Fred Pugac back to linebackers coach. Pugac is, by all accounts, one of the better position coaches in the league. It's unfortunate that his stint as defensive coordinator didn't pan out, but we should be glad to have him back where he belongs. Chad Greenway took a step back last season under Mike Singletary, and Erin Henderson is a young player with very high upside if he can get a good teacher. If, under Pugac's tutelage, he can take the step forward everybody seems to think he can, we should lock him up longer term after the season and really solidify our LB corps moving forward.

Third, we've resisted the urge to make splashy moves that will cost us in the long run. There was some legitimate receiving talent available in free agency, but we refused to play ball with the inflated contracts that the young talent was demanding. 8 million a year for Pierre Garcon? No thanks. Similarly for defensive backs. 10 million a year for Brandon Carr and Cortland Finnegan? More tempting, but still too much. The draft is, by ll accounts, deep at DB -- especially since we play a scheme dominated by cover 2, where elite talent isn't as necessary as patience and good reads.

Instead, we've been trying to find value: players who flashed for a period but then regressed briefly or suffered injuries that deflated their marketability. Lots of one year and minimum contracts. Fill the camp with bodies, motivate people with a legitimate chance to win a starting job, and cut the ones who don't look the part. We've also been looking outside the NFL for players, including a pair of intriguing players from the Canadian and Arena football leagues.

Solomon Elimimian is slightly undersized as a Linebacker, but the kid's got wheels (4.6 40) and was named the CFL's defensive player of the year in his rookie season, and players voted him the hardest hitter in the league last year. That highlight video suggests he doesn't give up on a play, and in Tampa 2, where the MLB is responsible for the deep middle of the field, we need a guy who is a bit more athletic to cover the slot and, especially, the new breed of Tight Ends that are tearing up the game right now. Worst case, he's an effective contributor on special teams. Best case, he finishes rounding out the second level of our defense.

As much as an unknown as Elimimian is, even stranger is Nicholas Taylor. Taylor is a former Florida International point guard whom the Vikings grabbed on a minimum futures contract purely as an athletic prospect. Dude is 5'10" and runs a 4.27 40 and spent time last year playing defensive back in Arena Football. Zero risk, amazing upside if he can put that athleticism to use anywhere on the field (especially at corner or returner).

Neither of these are flashy acquisitions, but both of them show a front office that is serious about looking at all the angles while we start rebuilding. We should have money on the books next season once we've filled some of our holes and know where we need to focus our final effort before being truly competitive again.

What we spend this money on next year will be determined by this year's draft.

I'm assuming that we'll take Matt Kalil, an incredibly highly rated Left Tackle out of USC, with our first round pick. This one pick will do worlds for our offensive line. John Sullivan took an enormous step forward at Center last season (pro football focus listed him as one of the top centers in the league), Phil Loadholt still has all the tools to succeed at right tackle with the proper motivation. With Kalil in place at left tackle, we've suddenly got a competition between Charlie Johnson, Joe Berger, Brandon Fusco, and free agency pickup Geoff Schwartz at the two guard positions. Any pair of those guys would be a step up from the Herrera-Hutchinson combination from the last couple of years -- Hutch is an all-time great, but he's old and only just above average these days.

From there, we need to worry about finding starters at wide receiver and defensive back and insurance at linebacker and defensive tackle. In my dream world, Georgia Tech wide receiver Stephen Hill is still available at the top of the second round. This is made more likely by the Bears trade for Brandon Marshall and the cornucopia of receivers that San Francisco grabbed in free agency. I'm still not certain it will happen. Despite being relatively unknown 6 weeks ago, Hill is 6'4", ran a 4.37 at the combine, is an experienced and talented run blocker, and showed better hands and route knowledge than anybody expected at his pro day. The mock draft gurus have him ranked as the number three or four wide receiver available right now, depending on their opinion of Kendall Wright. The Broncos, Browns, and Texans are all possibly landing spots in the bottom third of round one.

If Hill is off the board, I think we pass on a receiver in the second round. There will be very solid prospects available. Alshon Jeffrey was considered a first round prospect for much of the season, and I'm really high on Mohamed Sanu. Both big guys with good body control. I wouldn't even grab a receiver in the early third round, where we could grab similar guys like Marvin McNutt or Nick Toon. These are all big, reliable targets who serve well in the redzone, but they're largely possession guys who won't bring the vertical dimension we need. We've got Michael Jenkins if you're looking for good hands and deceptive speed.

We need somebody who can consistently take the top off of defenses. Early in the fourth round, we should be able to pick up Miami's Tommy Streeter. The guy is a physical specimen on par with Hill but even more raw. I can deal with raw in this case. Sub 4.4 speed at over 6'4" is worth taking a risk on when we've already got Rudolph, Jenkins, Harvin, and now Carlson around for the underneath stuff. We need to make their lives, and Peterson's and Gerhart's, easier, and a guy like Streeter (or, better yet, Hill) can do that for us better than Sanu or Jeffrey much less McNutt or Toon.

Assuming Hill is gone, I'd use our round two pick on somebody like CB Alfonzo Denard. He's not a top tier player at his position, but he's big and physical off the line and plays the zone well. Depending on how the front office feels about Christian Ballard and Letroy Guion, the other option here would be to take advantage of the draft's depth at DT. Devon Stills, Jerel Worthy, and Michael Bockers could all still be available at this point, and while I'd like to have faith in the guys we've got in place, our defense always thrives on a strong rotation up front.

Beyond these picks, try to find value at safety. It would be great if we could trade to pick up extra picks and put ourselves in positions to grab guys like George Iloka and Markelle Martin where they're worth it. Look for insurance at linebacker, potential at WR, and depth along the line while we're at it. This isn't going to be a one year rebuilding, but the pieces are available for us to be somewhere near .500 next season. Considering the conference we play in, that would be absolutely thrilling.

Fiction Editing

Several months ago, I posted a blurb I wrote on a whim. I haven't had much time to expand on it, so I'm still trying to figure out where things go from there, but I've put it through a couple of rewriting passages as I try to figure the main characters out. Just to give a sense of how I edit things, here's the current draft. Hopefully I can actually expand on the story in the near future:


Darren groaned slightly as he woke up and tried to remember what day it was. Mostly, he just hoped it wasn’t Thursday. If it was Thursday, then his alarm would be going off in about 3 minutes. More pressing, today being Thursday would mean that Wednesday had actually happened. He could think of few ideas less appealing than that.

Wednesday had happened, though, and Darren knew there was no escaping it. Even knowing that, he continued to hope that it wasn’t Thursday. Maybe it was Friday and he would at least have some space from Wednesday’s embarrassment. Better yet, maybe it was Saturday and he wouldn’t have to face the consequences at all. Darren didn’t care if he’d slept through two days of work and gotten fired. He was good at his job. He could find a new one. What he couldn’t do was show his face to Angie.

Two minutes until the alarm and Darren’s imagination really started to run wild. Sure, it was almost certainly Thursday, but maybe there was some holday he’d forgotten about. Maybe 26 years ago, somebody had done something heroic. Maybe 43 years ago, somebody important had been born or died. Maybe there was some good reason that everybody got to stay home and sleep on this particular Thursday and he’d have time to nurse his wounds.

One minute until the alarm, and Darren crunched up his eyes and crossed every limb he could under the covers to no avail. History hadn’t re-written itself, time advanced normally, and the morning DJ promised a chilly commute accompanied by Darren’s favorite hits of yesterday and today. Darren cursed both of those days and dragged himself out of bed. This Thursday, even more than most, would need coffee.

Not remembering what he may have sitting around on the floor, Darren gingerly stepped across his one room studio to the cabinet and appliance adorned corner that served as his kitchen. Once there, he flicked on the light and, blinking a few times, let his gaze settle on the sack of fair-trade beans sitting prominently on the counter top next to a second hand French press. Today was going to be bad enough without his coffee trying to make him feel bad about his privileged existence. Besides, he’d decided that he didn’t really like that Guatemalan crap, anyway.

He pulled the traditional, drip pot and the can of grounds out from under the cupboard, where he kept them for family visits and days like this. He shoved the largest measuring cup he could find into the can, dumped the water into the pot, and hopped into the shower while the coffee brewed. Out of distractions, Darren finally let himself start running through the details of last night.

The problem wasn’t necessarily that he’d had too much to drink. Darren’s budget and conscience conspired together to pose a fairly strict three drink limit most nights. No, the problem was that nerves had led him to consume this allotment far too quickly. It had taken weeks to get Angela to admit that, in this instance, dating a coworker wouldn’t be the worst idea ever. They had fun together, and the potential for paperwork wasn’t enough to merit not giving it a shot. Now he wasn’t sure if she’d laugh at him or slap him when he inevitably ran into her at the office. He did know that he’d prefer the slap.

Outside of the warm steam of the shower, the apartment was still cold, and Darren felt the urge for coffee again as soon as he stepped out of the bathroom and back into the kitchen. He gulped down one cup before he even bothered to get dressed and another as a reward once he tracked down a clean pair of pants. Pouring the rest of the pot into a travel mug, Darren buttoned up his flannel shirt and headed down to the corner.

It was cooler than Darren had expected from the forecast, and he immediately questioned his decision to forego a jacket. He fastened another button and tried to ignore the cold while he waited for the bus. Ignoring one thing means thinking about another, though, and Darren continued to reflect on the events of the night before. It was Angela’s fault nearly as much as his. She’d caught him off guard. He’d intended to keep it casual, but then she came to the door with her hair up and wearing a skirt. She’d put in effort. She cared. He never had a chance to recover from the surprise, pleasant though it was.
He saw Roger’s grin as soon as he boarded the bus. Darren sat down across from him and took a swig from his mug, knowing full well what was coming next.

“So?” Roger asked.

“‘So,’ what?” Darren was not looking forward to this.

“Dinner. With Angie. How did it go?”

“Less well than it could have.”

“That’s not saying much. How, particularly, did it stray from the ideal?”

“I may have propositioned her during dinner.”

“May have?”

Darren glanced around and lowered his voice, “There was an awkward silence. Some part of me thought it would be smart to break it by asking what I’d have to do to get fucked that night”.

The dirty look he received from the octogenarian sitting ahead of them suggested that he hadn’t lowered his voice enough.

“Well, that was much less awkward.” Roger’s eyebrow was thoroughly cocked.

“It was a joke!” Darren insisted, “I said it in a funny voice and everything!”

“Could she really be that offended? I mean, I’m sure she didn’t think you meant it. It’s far from the first time she’s met you”

“She must have been disgusted. Made an excuse to duck out as soon as she finished her chicken. Left half of her baked potato right there on the plate.”

Roger paused but couldn’t bring himself to change the subject, “...what on Earth were you thinking?”

“Obviously, I wasn’t.”

“...well, it’s not like she’s the only cute girl in the sea.”

Darren pulled up a picture of Angela on his phone and thrust it in Roger’s face. “That, and she’s a Raven’s fan, AND she loves Bruce Campbell.”

“That sucks, man.” Roger knew he was defeated.

“That it does.” Darren took another swig of coffee and questioned his decision not to put a drop or four of whiskey in it.

Mass Effect 3 and the Stories We Think We Tell (Spoiler Free)

Finished Mass Effect 3. If you're an active resident of the internets, you've probably heard that a whole lot of people aren't just displeased with the ending, they actively hate it -- to the point that Bioware is caving and preparing an alternate ending (try searching around if you want to know more). I'll admit that the ending feels a little contrived at points (and the post credits scene is laughably bad), but it could be waaaay worse.

Here's the thing to know: in the minds of the game's creators, the message of this series was never simply about survival. For them, the whole of the series was about organic vs synthetic life (and the presumed deficiencies of organics). In that light, the ending makes perfect sense.

Unfortunately, this overarching "organic vs synthetic" plot line was never made nearly as explicit as the "fight for survival" that dominates the rhetoric of the characters. Yes, the synthetic nature of the Reapers makes them a unique sort of enemy, but it's their unknowable-ness (a combination of their origin, their age, and their limited appearance), not just their unnaturalness that makes them daunting.

You could just as easily have had an advanced organic race that shows up every several thousand years to check in on the modern races and assimilate or destroy them as they see fit. The Reapers didn't need to be synthetic to be effective, they just needed to be insurmountably powerful. Being synthetic is one path to that. Simple sci-fi technobabble is another.

It would be hard to do more with just the Reapers themselves to enhance the clarity of the message that the writers were trying to deliver, though. They need to be somewhat remote so they can remain effective boogeymen. Besides, Sovereign and Harbinger both bring out the whole "gaaah, you are puny organics, we are your future, cower! COWER, I SAY!" rhetoric on those rare occasions where you do get to communicate.

In order to make this story work, you need to have a world that's built around paranoia about the limitations of organics from the start. You need to have the advanced races terrified about the technological and cultural plateaus that they've been sitting at, sometimes for millennia. Humanity has only been part of the interstellar scene for about 30 years by the end of Mass Effect 3, and yet we're as advanced as any other species in the galaxy.

You need to have more incidents of failures to contain or control artificial intelligence, possibly all having gone and merged with one another to form some heterogeneous variation on the Geth. You need to have these scarier Geth floating around the edges of "civilized" space before things ever start, using their unique intelligence to devise technologies and solutions and threats that we've never conceived of. The Reapers need to not be the only threat, but the biggest and most sudden. The Reapers need to be a realization for the existing fears that are already plaguing the population.

Instead, we have a peacetime galactic government that is focused on politics as usual and just the one incidence of failed A.I.. Worse, the Geth don't seem to be improving much upon the same technologies everybody else in the galaxy is using, and once Legion shows up to provides a mouthpiece for them, they suddenly become more accessible -- making it seem like collaboration could be a legitimate option if organics are willing to set aside their (limited) fears.

Fixing these problems of setting would be an important step, but the rest of the problem is harder to address. Part of the reason the basic survival narrative seems so dominant is because it's next to impossible to provide a gameplay goal built around anything else. This stripped down story was always going to engage the player's attention because surviving is what they spend roughly half of the game doing. The only solution I can see is to make fights with synthetics lifeforms more imposing. Make sure that they are so much harder to kill than simple security robots. Make these fights feel distinct and more tense. Don't just send Shepard and friends off to kill them in droves, but let a handful of Geth be a significant challenge.

With these (not insignificant) changes, I'm sure people would have still complained about the ending because it's an ending and it's never going to satisfy everybody (and there are some contrived elements to it). But the complaints would have been for different reasons and could at least have been in line with what the writers were envisioning. As it stands, I'm glad to know what I know and I'll be glad to let that knowledge shape how I play through the game in the future. It was a fun trip, even if I'm not certain it was as strong as either of the first two games.

Games, Education, and Exploration

Generally speaking, I don't believe in educational games. That's not to say that I didn't learn a lot of facts from games like Number Muncher or Mario's Time Machine, but games like that are glorified flash cards. I think that we can add an engagement factor and arbitrary context for learning strictly declarative knowledge just fine. What I don't believe in is games that help, by their very nature, in learning procedural knowledge or higher level relationships between concepts.

This wouldn't be an issue if I wasn't currently taking a course that is, theoretically, about making games to serve just this purpose. Twice a week, I get to sit and listen to stories about all of the funding that my professor has earned from various institutions trying to make these sorts of games.

There are two simple reasons that I don't believe in educational games. One is transference. Virtually all games, especially games exploring abstract concepts, employ some sort of metaphor. This means that whatever skills or concepts are being taught, ultimately, are being learned with regards to the metaphor. Knowing what you're supposed to actually learn, then, requires additional interaction with the domain that the lessons are supposed to be applied to. Moreover, it requires an active effort to identify the pieces of the analogy in place. All of this means that it's going to be very hard to make the game itself educational unless it's included as a piece of a larger, directed education plan. Either that, or the game needs to actively mix in these elements, which risks breaking engagement.

Second is that, my professor, at least, seems to lack any sense of distinction between "play" and "playing a game". Play is self-directed and exploratory. It's a matter of expressing and recognizing and responding to patterns that we've observed in an environment where we have complete control. This lets us experiment with ideas and see where the rabbit hole leads us (even if it leads us astray). This is incredibly useful in learning because learning is an exploratory activity. On the other hand, games, by their very nature, are goal based.

The purpose of a game, in the mind of the player, is to complete the game. This can mean gaining mastery of the systems in play, or it can mean butting your head against it until something works and then moving on. In cases where a game requires real world knowledge, people are willing to play lip service to that knowledge without taking it to heart (just like students are willing to put the answer the professor wants on a test or a paper without believing a word of it). In short, all we want to learn from a game is how to beat the game.

Play is educational. Playing a game is not. What we need aren't educational games, but educational toys. Toys can be used in the construction of games to push people towards a specific goal, and games can have their purpose subverted and turned into toys to promote experimentation, but they are very different things.

Inventing Recipes: Huevos Rancheros Burger

If you've ever had a burger topped with a fried egg, then this variation should come as a no-brainer: top a black bean burger with a fried egg, some avocado, and salsa. This may be one of the most delicious things I've ever had. It's been knocking around in my head for ages, but my last couple of efforts to make black-bean burgers hadn't fared too well. A recent bout of falafel making gave me some ideas to fix that, though. This may be the best thing that has come out of me going vegetarian for lent.

Huevos Rancheros Burgers (feeds four):
Patties
2 15 oz cans black beans
1/2 large white onion
3 large cloves garlic
1.5 tsp salt
2 tsp cumin
1 cup frozen corn
3 Tbsp flour

Mince the garlic and onion; drain and rinse the beans. Mash the beans thoroughly and then fold everything together. Form into 4 large patties and grill, 5 minutes on a side, or cook in a pan with a bit of oil somewhat longer.

Salsa
1 15 oz can "fire roasted" tomatoes
2 large cloves garlic
1 large jalapeno pepper
2 Tbsp Cider Vinegar
Salt, Cumin, Coriander to taste (be somewhat generous with coriander and more restrained with cumin)

In a small, non-stick fry pan, roast the garlic (unpeeled) and the jalapeno. This should take 10-15 minutes over medium high heat. Turn everything on occasion. Once the garlic is a pleasant brown and the pepper is lightly charred on all sides, peel the garlic and remove the stem from the pepper. Add everything to a blender and liquify, seasoning as desired.

Others
1 avocado
4 buns
4 large eggs
Shredded cheese

Halve the avocado and remove the pit. Then, with the rind still on, slice perpendicular to the rind into strips without cutting through the avocado. If the avocado is sufficiently ripe, you should be able to remove slices with a spoon.

Fry the eggs to your desired done-ness (something slightly better than over medium works well), ideally keeping them individual. When you flip the eggs, top them with cheese so it melts.

Toast the buns. Then stack them with a black bean patty, an egg, slices of avocado, and salsa. Consume with great vigor.

Thoughts from the Half-Way Point: Mass Effect 3

Unless I opt to move my 360 into my room, the NCAA tournament is going to put a massive damper on my ability to play Mass Effect 3 over the next several days. As such, I figure this is as good a time as any to sit back and reflect some on the experience so far. I'll try to avoid spoilers, but at this point, so much of the game depends on what you've done before, that there are only a few plot points that would obviously follow no matter what your Shepard has done.

That's really the first mark in the game's favor. After so many decisions in ME1 seemed to be largely without consequence beyond the cosmetic in ME2, everything you've done before suddenly takes on added significance. More important, the blatant good/bad dichotomy has lessened remarkably, as the bulk of decisions seem to be much more grey. To this end, even the Paragon/Renegade divide has been diminished, with many decisions simply serving to enhance your "reputation" -- a catchall that contributes to both scores. I finally have a compelling reason to revisit Mass Effect 1 and alter my decision making at certain junctures just to see how certain quests change and how that will affect my ability to prepare the galaxy at large.

The increased value of your decisions wouldn't matter if they didn't continue to contribute to strong storytelling, though, and I'm happy to say that they do. The overarching plot is, of course, a bit generic (help prepare an army to challenge a seemingly unstoppable enemy), but the power is in the setting and the bond that each player gets to establish with it. There are so many characters at this point and so much history that we've been exposed to that it's hard not to feel an attachment when a familiar face pops up or when you get closure from a character or event that you expected to be left by the wayside. Of course, not every character can be included in a satisfying way. Some additions are brief and seem forced in as nothing more than an excuse to let some secondary or tertiary character saunter by as a reminder of their existence and then contribute unseen to galactic readiness (this holds especially true of any character that showed up exclusively in DLC). But, we can't expect miracles from the writers, and satisfying everybody was never an option.

Honestly, I only have two real complaints about the story so far. First of all, too many characters have changed or accomplished too much since the end in Mass Effect 2. The game tells us that it's been six months since Shepard turned him/herself in for trial on Earth. How in the hell have some of these people picked up the positions they have since then? Grunt, Jack, even Garrus: I'm looking at you. Second, the game really needs to give a better glimpse into Cerberus' motivations. It sounds like that's going to play a much more serious role going forward. For those of you farther into the game than I, a certain major plot event just took place on the Citadel. I get that it's not meant to make immediate sense from the perspective of the player/our characters, but there's no coherent attitude/belief system of which the player is aware that would allow the event to make sense. People make choices for reasons other than "wouldn't it be dramatic if...", and that's the only attitude that could possibly seem to be driving the Illusive Man at this point.

With the important part out of the way, it's time to talk briefly about gameplay.

In terms of controls, we're mostly looking at a fine tuning of the systems in place in Mass Effect 2. Gunplay sometimes feels a bit loose, but that happens with most 3rd person shooters. The improved mobility is nice, and I find my infiltrator using his cloak to sprint up and beat down fools as often as to pick out a careful headshot. The changes made to armor sorts of abilities -- each carrying the option to purge the added defense in order to gain some other temporary advantage -- are fun and make them seem more active. I also like that these armor abilities (along with the infiltrator's cloak) don't incur their cooldown until they are purged or their period ends. It makes it a lot easier to use traditional powers in conjunction with these prolonged effect abilities. Combat, in general, is as fun as it's been, and that makes multiplayer a much better option than anybody would have expected.

First, though, I have a couple of complaints about things at the design level. The least important but most glaring of these is the new resource collecting system. You run around star systems using your sensors in an attempt to ping for things that could be useful in the preparations you're supporting. This isn't so bad by itself, but each time you run a scan, you make Reapers more aware of your activity in the region. Do it too often (basically, 3 times), and they're off and chasing you and you need to get your ass out of the system! Except...you don't. The game autosaves each time you enter a system. There's no good reason not to just go around firing off your scanners like crazy, determine where everything is, Reapers be damned, let them catch you, and then have that autosave reload so you can fire off your scanners in the two or three places you need to to collect everything from a system. It's a silly waste of time that tries to add a sense of high stakes and consequence where there are none.

Slightly more annoying is a shift in combat similar to some things I complained about in Dragon Age 2: namely, inexplicable waves of enemies. Reinforcements will jet pack in or jump down from balconies or come through otherwise sealed doors at every opportunity, just to inflate challenge. It makes it nearly impossible to develop any high level strategy the way that you sometimes needed to at the upper difficulties of Mass Effect 1 and that were occasionally beneficial in Mass Effect 2. It keeps the action going, and things are fun enough that I don't mind too much at the default difficulty, but I'm going to be cursing up a storm during my inevitable Insanity attempt. In the prior two games harder difficulties just started to feel natural once you adapted to what they expected of you. I don't see that happening here because the source of difficulty is different.

Finally, the designers seem to have responded in the worst possible fashion to the complaints that Mass Effect 2 lacked side quests. There are now dozens and dozens of meaningless fetch quests you can go on (largely connected to the new resource system) and lots of time consuming, fluffy interactions available at the Citadel (and possibly other hubs if there are any). The fetch quests remind me a lot of Dragon Age 2 and the various weird things you would find while you were going about your adventuring only to suddenly know that somebody would give you money/experience for them. In this case, at least you overhear conversations about the things to know that you're looking for them, but it's similarly arbitrary. The more traditional quests, while at least providing some sort of context, but they mostly involve talking to a sequence of people/terminals and then getting some sort of payoff when a tertiary character from some previous sidequest in a previous game shows up at the end.

The good news is that, other than establishing mood, all of these serve simply to increase the resources you can bring to the fight with the Reapers, meaning they can be avoided without consequence if you just sink some time into the multiplayer!

I haven't done much with the multiplayer so far. Spent an hour or so going through a few rounds with Andy before I'd really gotten into the single player. I'm looking forward to going back. For the most part, it's class-based horde mode with unlockable persistent upgrades in the form of both level gaining and new equipment. Each player gets to control a stripped down version of one of the base classes, each with three hotkeyed abilities and two weapons (or at least the Sentinel only gets two weapons, maybe the Soldier gets more?). You're dropped in hostile territory and confronted with a series of randomized enemy waves and objectives and asked to survive as many as you can, up to 10. The longer you last, the more experience you get and the more you improve the ability of the galaxy to fight off the Reapers. Good stuff, and I'm eager to do more once I buy a Gold subscription again (note to MS an EA: the 2-day pass you shipped with the game succeeded in ensuring that I'll reup for a full year in short order after letting my account lapse).

All said, I'm roughly 20 hours in, and I'm thoroughly enjoying Mass Effect 3. There are decisions that confuse me and a lot of additions that seem to exist purely to occupy your time, which is frustrating after 2 was so tight and focused. Still, I love this setting and these characters. I'm eager to see how the story of Commander Shepard wraps up in each of the four iterations I've created for it. I'll be sad to see it come to an end.

Computers, the Cortex, Prediction, and Intelligence

**Warning: This is a response to the book On Intelligence by Jeff Hawkins. It was originally written for a Cognitive Science course. Ahead lies 4000 words worth of historical computer science, bumbling neurobiology, and a bit of armchair philosophy. Read at your own peril**

Jeff Hawkins, author of On Intelligence has a bone to pick with both Artificial Intelligence researchers and neuroscientists: neither group, he claims, seems to be concerned with determining the nature of intelligence. For their part, computer scientists have long been resistant to the notion that the structure of the brain is important in promoting intelligent behavior. Neuroscientists, meanwhile, have not put forth as much energy as Hawkins would like into putting forth any sort of unified theory or framework of cognitive function.

The sins Hawkins accuses computer scientists of committing can seemingly be attributed to an over-reverence for Alan Turing. If it is true that a Turing Machine can compute anything that can be computed, and if any we believe that one of the primary functions of the brain is to compute, then it seems perfectly plausible to suggest that the brain is nothing more than a biological implementation of a Turing Machine. Since all Universal Turing Machines are effectively equivalent, then it further seems reasonable to insist that digital computers ought to be a perfectly suited to playing host to intelligence.

Hawkins also argues that Artificial Intelligence researchers were led astray from the very beginning by the Turing Test. Turing lived at a time when psychology was still dominated by behaviorism: the notion that intelligence could only be determined by action. The Turing Test endorses this thinking, and while it is not a benchmark that researchers seriously pursue, virtually all testing of machine intelligence that has followed in its wake is also focused on this input-output driven benchmarking.

The largely fruitless results of historical AI research suggest that maybe this is not the right way to do things. We have made programs and algorithms that can do all manner of seemingly complicated activities from playing chess to approximating optimized configurations for complex systems. The “simple” things that we would really like computers to do, though (vision, language acquisition, motor control) have made only minimal progress. If the brain is following formal, procedural algorithms in the fashion of a turing machine, we obviously have not found them. More likely, though, is that the brain does something different.

Hawkins suggests that the brain, while obviously capable of traditional computation, must also do something more elaborate, and we ought to try replicating that process if we want to create computers and/or programs that exhibit intelligence. Computer Scientists came up with this same idea decades ago and it led to the idea of Neural Networks. This was a good start, but it was not taken far enough. As soon as toy three-layer networks produced some interesting results, researchers returned to navel-gazing instead of taking further steps to mimic brain behavior. But who can blame them when we still understand so little about the brain?

This leads us to Hawkins’ frustrations with the neuroscience community. Chiefly, he thinks that we simply have not put in enough effort to determine how the brain, and specifically the cortex, works. We have gathered reams of experimental data about brain activity. We have rough maps of where all sorts of phenomena are processed in the brain -- from linguistic syntax to motor control to immediate optical stimulus. What we do not know is really anything concrete about how these signals interact to produce what we think of as intelligence.

This is not really surprising in itself. The brain is an incredibly complex and sensitive organ, and it is very hard to perform any sort of accurate experimentation on it. All of our current methodologies necessarily sacrifice either spatial or temporal resolution, and we really need both in order to say anything meaningful. Still, Hawkins would encourage boldness. We cannot spend all of our time simply collecting data without anything to use that data for, and our current theories are too low-level and low-risk to be of interest. We need a theory that can explain the phenomenon of intelligence as a whole, both in order to understand ourselves and in order to imbue this property on future generations of machines.

To this end, Hawkins suggests an overarching theory to describe the nature and purpose of brain function as it relates to intelligence. Such a theory, while likely flawed, would give direction to our research and change the way we think about our work, both in neuroscience and A.I.. Ultimately, On Intelligence is Hawkins’ attempt to lay out such a theory: the Memory Prediction Framework.

In short, the Memory Prediction Framework suggests this: The function of the brain, as leads to intelligence, is not simple computation. Computation would suggest nothing more than stimulus-response pairings. Instead, Hawkins claims that the human brain strives to use previously identified patterns in order to predict and change the future.

For Hawkins, the seat of what we think of as intelligence -- agency, intentionality, adaptability, even creativity and consciousness -- is the cortex. The cortex is not exclusive to humans, but the most notable difference in brain structure between us and other mammals is the sheer size of ours, thanks to the evolutionarily recent expansion known as the neocortex. Since humans are so far beyond other animals in our ability to understand and control our environments and pass on our knowledge to subsequent generations, this enlarged cortex ought to play the primary role.

Hawkins proposes that the chief function of the cortex is to contain a model of the world as we have experienced. At its most abstract, ignoring all of the biology involved, this is accomplished by forming what Hawkins calls invariant memories. We recognize patterns that occur together -- the shape of a hand, the sensation of heat on our skin, the sound of a musical interval -- and group the sensations together into a single mental concept, recognizable even when specifics -- the starting pitch, the orientation of the hand, the location of the burn -- change.

From these patterns, we construct composites of patterns. From letters we pick up words and phrases and stories. Eyes and nose and lips become a face. Intervals expand to phrases combine to make songs. Simple patterns, universally, become building blocks for more complicated concepts, both in the abstract or the specific. As we experience a pattern more, it becomes more accessible and more foundational to creating new patterns. In a world where we often encounter combinations of stimuli that seem completely unrelated, these models help us come to reasonable conclusions about our surroundings. If you hear an animal roar but look around and see that you are still in your kitchen, you don’t assume that a bear got into the house, but that somebody has the television on too loud.

The power of these models is apparent: if we know what follows from what we are experiencing right now, we know how to respond. We see a bottle teetering on a table and we can steady it before it falls. We see an old wounds threatening to reopen during an argument and we preemptively make peace. We build tools to initiate a chain of events that lead to a desired goal, whether that is an improved harvest or a man setting foot on the moon. By predicting how the environment will respond to our actions or what state naturally follows from the current one, we exhibit control over reality in a way that simple organisms simply cannot. We nudge the trajectory of the world to be more favorable for us.

What is even more remarkable is that we can create invariant “memories” about things we have never witnessed. We have developed tools, notably language, that allow us to pass on our experiences to others, providing them the ability to respond appropriately to situations before they have ever encountered them. Further, for lack of a better term, we have the ability to imagine. We can create mental worlds rooted in the model of reality that we have built but distinctly different. We can tweak parameters, ask ourselves how things would change if certain patterns coincided in a new way. We can test the outcome of a course of action without taking on the risk ourselves. This gives us our unique capacity for invention in both the practical and artistic senses.

All of this is well and good, and we can provide ample anecdotal evidence to convince ourselves of it based purely on reason. The question is, can it be supported by biology? Unfortunately, there is still so much about the brain, and especially the cortex, that is a mystery to us that little can be said conclusively. Hawkins does, however, offer up a description of what is known about the cortex and how this could endorse the Memory Prediction Framework. This is where my expertise wanes, but I will relay Hawkins’ lesson to the best of my ability:

Physically, the cortex is a thin coating of brain matter, consisting of “grey matter” (neurons) and “white matter” (axons connecting the neurons), surrounding the evolutionarily old brain. The cortex is divided physically into six layers of neurons. Each neuron is connected at many points to the neighbors in its own vertical column as well as to neurons in its neighboring columns and a plethora of other neurons distributed throughout the whole of the rest of the cortex. It is well known that, in the visual regions of the cortex, these connections form further topological hierarchies, and Hawkins thinks it natural that this should also be the case for other regions, as we will see. Signals begin in the lower levels of these hierarchies and then collect and travel upwards as more elaborate relationships between signals are processed.

These upwards connections have been studied widely, but the first important thing that Hawkins focuses on is the fact that there are actually more feedback connections traveling down the hierarchies than there are transmitting data forward. Most theories of the brain seem to discount the importance of these connections, but we will see shortly that they take on prominence in the Memory Prediction Framework.

There is one other important feature of cortical design that we have to discuss first. I already mentioned that the cortex is consistent in its physical makeup across its entirety. In the late 1970’s, this led researcher Vernon Mountcastle to put forth a theory that has largely been dismissed ever since: that there is no significant functional differentiation in the cortex. That is, all regions of the cortex, whether they process sight or language or movement follow some universal algorithm. This, in part, is why Hawkins assumes logical hierarchies within all regions of the cortex and not just the regions that process vision.

As evidence for this claim, Hawkins offers up two arguments. First, the extreme plasticity of the cortex. We know, for example, that violinists have larger areas of their cortex dedicated to controlling the movement of the fingers on their left hand. Individuals born deficient in one sense seem to have larger regions devoted to their others. In one particularly shocking experiment, a man turned blind was able to regain “sight” be having a camera send electrical impulses to his tongue. This somatosensory information was processed in the visual regions of the cortex.

Second, there is no reason to believe that the brain has any reason to process different senses differently. The brain itself is without any sense, after all, and all senses can ultimately be described in the same way. Whether it is a collection of light rays collecting on the retina or longitudinal wave colliding with the cochlea, all of our perception boils down to spatio-temporal patterns. If the brain is just processing spatio-temporal patterns at every turn (as the Memory Prediction Framework already suggests it does), then it should not matter what the input mechanism for these patterns is, just that the pattern is delivered for interpretation.

From here out, I will adopt this theory that all inputs to the cortex are equivalent. I may use language that seems pertinent to the way we perceive a particular sense, notably sight, but please understand that I am referring to any generic sense.

Most of what researchers have observed in the brain has been how these signals are propagated upward through the (logical) hierarchy. A particular image or impression is received from the sensory organs and is transmitted to the cortex. A subset of neurons immediately connected to that sense fires in accordance with the received image and, in firing, pass a signal upwards. The next layer receives this input pattern exactly as the lower layer did and again fires off a subset of its member neurons. This continues until the signal reaches layers high enough for us to make conscious sense of what is being perceived. These groupings of firing neurons, notably the particular groupings that result in recognition, embody the patterns that constitute our invariant memories.

What is interesting is that, while the lowest regions are rapidly modulating due to constantly changing input (because of the saccadic motion of the eye or the continuous flow of sound through the air or whatever else), higher regions -- regions where things in the world are recognized -- stay active for much longer. Obviously, then, these higher regions respond to increasingly general patterns. Hawkins also suggests that there are specific temporal patterns, that is, sequences of spatial patterns, to which these regions respond, and that they will remain active for as long as they receive the same expected repetition of spatial patterns.

Tying into the importance of these temporal patterns, Hawkins now comes back to the significance of the feedback connections, the ones connecting logically higher layers in the hierarchy to those closer to the actual perceived input. In short, Hawkins claim is that, once a pattern has been recognized at a higher level, it tells the levels below which input it is expecting to receive next. In effect, we prime ourselves to see what follows from what we are currently seeing, and we begin responding to it before it can even occur. This is the “prediction” element of the Memory Prediction Framework.

When the actual input defies the expected input, we are jarred out of the current pattern and the image once again propagates normally until we can replace our previous pattern one with one that more accurately represents what we are truly seeing and resume along a more appropriate course of action.

All of this feedback and neural priming predisposes us to see patterns with which we are already familiar. This can help us resolve ambiguities in the environment and perform on-the-fly error correction, but it can also cause us to gloss over seemingly unimportant distinctions. We see this any time we automatically correct a minor spelling or grammatical mistake or even when we try our hands at a “spot the differences” exercise. We are very good at seeing what we want to see because that makes our lives easier and our processing swifter.

So, we now understand how memories are activated and how they are used to predict the immediate future. But how are they formed? Hawkins endorses a simple mechanism known as Hebbian Learning. Simply put, when neurons fire at the same time, the synapses between them are strengthened. This means that each member of a neuron pattern firing increases the odds of the other neurons in the pattern firing as well. These patterns identify an element of a “memory”, and the patterns themselves are stored in the synapses. The more we see a pattern, the more likely we are to see it in the future, even if not all of the elements of that pattern are available in the immediately presented image.

Hawkins has a lot more to say about how the brain operates: the significance of the columnar alignment of neurons as a processing unit; the nature and method of inhibition between neurons and columns; role of the hippocampus as the topmost hierarchical element of the cortex; the importance of the thalamus as a gateway between cortical regions. This is where nuance that is beyond me comes into play, though, and I cannot hope to do all of it justice. I take Hawkins at his word in these arguments, in part because, he offers a number of testable hypotheses that need to be confirmed in order for the Memory Prediction Framework to stand up.

For instance, Hawkins suggests that we will eventually be able to identify the downwards cascades of “predictive” activity through neural hierarchies that should coincide with sudden understanding. Novel events, on the other hand, should be seen propagating upward toward the hippocampus. He identifies specific sorts of cells that should exist in particular cortical layers and which should show excitement in anticipation of an input or respond differentially depending on whether its input is expected or unexpected.

Either because of a lack of interest or continuing limitations in our monitoring technology, it would seem that none of Hawkins’ hypotheses have been either confirmed or refuted in the years since he wrote On Intelligence. If Hawkins really wants to promote his theories or provide some evidence of their correctness without waiting for technology to catch up, the best route might be through implementing them successfully in technology. To this end, Hawkins has already started a company called Numenta, with the goal of producing machine learning packages that model a variation on what he calls Hierarchical Temporal Memory -- a learning architecture that mimics his theories about the design and behavior of the cortex.

Hawkins talks about future generations of machines that utilize Hierarchical Temporal Memory to process patterns and make predictions about any phenomena imaginable. Computers are already better than we are at processing large amounts of data. The electrical signals that travel through a microprocessor are orders of magnitude faster than the electrochemical impulses that drive neural activity. There is no telling what we could discover with intelligent machines churning away and making “informed” predictions based on all of the information we could feed into them.

This is especially apparent when we consider the sorts of input such machines could process. We have already committed to the notion that senses are arbitrary and interchangeable, so why should machines be limited to making decisions based on our senses? Imagine computers that operate and make extrapolations based on input from novel senses, like sonar or barometric pressure, as easily as we do sight. Such computers would drastically increase our ability to, say, predict weather patterns or plan unmanned spaceflight. And that is just the beginning. Imagine how much more effective the approach could be if we actually had computer architectures that integrate memory and processing the way the brain seems to.

But one important question remains: would such a machine be intelligent? This is where we need to start holding Hawkins accountable for some of his early rhetoric. For all of his grand talk early going about the superiority of the brain, Hawkins still appears to believe that intelligence can be replicated by digital machines. This would not necessarily be human intelligence, complete with all of the intangible qualities that make life fascinating, but at least the pattern-driven, future predicting intelligence that he believes is the key to our success as a species. So, whether he commits to it directly or not, Hawkins ultimately believes after all that the brain is nothing more than an augmented Turing Machine; a Turing Machine optimized for the sorts of feedback driven, memory intensive algorithms he has described, but Turing Machine nonetheless.

Moreover, for all of his complaints about behaviorism, Hawkins is ultimately insisting that behavior is the ultimate benchmark of intelligence. He simply shifts the scale from the macro (measurable action) to the micro (method of signal processing). If prediction is the defining measure of intelligence, does the implementation matter? It seems unreasonable to suggest that it is, in which case Hawkins is not really offering us anything new. Prediction, of a sort, has been the goal of A.I. all along. Big Blue was able to “predict” the correct move at each juncture to beat Kasparov. In the abstract realm, the Chinese Room is able to “predict” an appropriate response to a written inquiry in an unknown language. We already have all kinds of learning systems, ranging from traditional Neural Networks to Bayesian modeling, that seek to make predictions based on previous observations without making any effort at faithfully modeling the cortex. Why are these implementations less capable of intelligence than Hawkins’?

Truly, as regards prediction, Hawkins’ solution is different only in approach. This approach may have advantages, it does not give us intelligence by itself. Since prediction alone would appear to be insufficient (unless we suddenly want to change our minds and ascribe intelligence to existing implementations (actual or theoretical) of A.I.), we need to look for another primary feature of intelligence and ask whether that is fundamental to the Memory Prediction Framework and Hierarchical Temporal Memory.

Off the cuff, I would argue this defining feature of intelligence is willfulness -- the ability to direct (if not select) our thoughts, to forge mental connections of our own volition rather than programmatically. Truth be told, I am not certain that the Hierarchical Temporal Memory can provide that or that the Memory Prediction Framework can explain it. Certainly, Hawkins does. He suggests that consciousness is simply “the feeling of having a [sufficient] cortex”. But, while his description of the brain and the neural connections within the cortex certainly provides mechanisms and conduits through which thought could be consciously directed, the driving force is nowhere to be found.

So, if Hawkins’ framework cannot successfully explain intelligence in individuals, we cannot expect it to imbue intelligence on machines. Hierarchical Temporal Memory does not create any stronger argument for understanding than passing the Turing Test. That does not mean his model is useless. The feedback and priming systems that Hierarchical Temporal Memory contains seem well suited to monitoring and making predictions about real time systems, whether it be vision or other crucial signal monitoring. Hawkins’ work may not be any less artificial than other routes that we have taken, but it is still a potentially beneficial supplement.

For the neuroscientist, Hawkins ideas would seem to posses more significant value. The importance of feedback, pattern recognition, and pre-conscious prediction in cognition make a world of sense at a cursory glance, even if the mechanisms that guide it may not uniform throughout the cortex. Even if we limit the Memory Prediction Framework to being a description of cortical function and not intelligence as a whole, though, Hawkins still runs into hot water. For one thing, he discounts the importance of the old brain in intelligence far more than can be acceptable. More than that, though, there has to be a reason that Mountcastle’s theories of universal cortical function have not gained more traction over the past 30-some years.

I may be willing to accept that uniformity could well be the norm for processing sensory input. Patterns in where we process the senses are easily explained by nerve connections from those senses, and all of the signals ultimately are translated into the same sorts neural firings. How does this explain issues like Brocha’s area, though? Why would virtually all humans process linguistic syntax, something with no direct connection to a single sense or the outside world at all, in the same region of the cortex? There does not seem to be an easy “path of least resistance” explination available here.

Since this, ultimately, is Hawkin’s goal, I have to end by giving him credit. His goal was never to provide a definitive answer to these problems, but a starting point. On Intelligence does provide and intriguing, if likely flawed, account of what intelligence could be. I suspect it will not stand the test of time, but it may well provide a useful stepping stone. By taking the risk of proposing not only a theory but standards by which it can be tested, Hawkins has left future researchers with the ammunition to tear apart his framework and iteratively replace it with one that lies closer to the truth. That risk can only lead us closer to the truth.


Bibliography
Hawkins, Jeff. On Intelligence (New York: St. Martin’s Press, 2004).

Hebb, D.O. The Organization of Behavior (New York: Wiley and Sons, 1949).

Mountcastle, Vernon B. “An Organizing Principle for Cerebral Function: The Unit Model and the Distributed System” in The Mindful Brain (Cambridge, Mass: MIT Press, 1978).

Legacy Content. Numenta. http://www.numenta.com/legacy.php. Accessed March 6, 2012.