SynapticNulship

Right now I’m reading an architecture book from the 1970s called The Timeless Way of Building.  So far it has to do with theories of how towns and buildings and other things seem more “alive” than others, and how to achieve this quality—the “quality without a name”.

This of course goes far beyond merely architecture; indeed this book was brought to my attention not by an architect but by people in the UX (user experience) design community. Anyway, this blog post only covers a couple pages out of the book.

The author, Christopher Alexander, says that we have come to think of buildings, towns, and works of art as “creations.” And that “creation” is thought of as a monumental design task, “brought to birth, suddenly, in a single act, whose inner workings cannot be explained, whose substance relies ultimately on the ego of the creator.”

I would interject that the creator might understand the inner workings, but even then, for a complicated project attempted in a process with this mindset, the end result would probably not be completely understandable by the creator. More on that in a minute…

As Alexander writes:

The quality without a name cannot be made like this.

Imagine, by contrast, a system of simple rules, not complicated, patiently applied, until they gradually form a thing. The thing may be formed gradually and built all at once, or built gradually over time—but it is formed, essentially, by a process no more complicated than the process by which the Samoans shape their canoe.

And if you’re thinking that this sounds very much like how biology works, then you have predicted the next key statement on the same page:

The same thing, exactly, is true of a living organism.

An organism cannot be made. It cannot be conceived, by a willful act of creation, and then built, according to the blueprint of the creator. It is far too complex, far too subtle, to be born from a bolt of lightning in the creator’s mind. It has a thousand billion cells, each one adapted perfectly to its conditions—and this can only happen because the organism is not “made” but generated by a process which allows the gradual adaptation of these cells to happen hour by hour….

And Alexander claims that there is no other way. Of course, as a transhumanist and a roboticist and an occasional cognitive architect (oh, maybe there is architecture here after all!) I want to be able to create and modify life forms. I want to make artificial organisms, and interfaces between the organic and the non-organic.

However, I have enough experience with software development and project management to know that what Alexander says is true. I.e., I believe it based on my experience and observations.

So I have two immediate responses when I read this part of the book:

1. Examples of systems that look complex, but evolved and/or iterated via simple rules.

For instance, the cellular automata popularized by Stephen Wolfram in A New Kind of Science create complexity and even randomness from ridiculously simple rules. Behavioral robotics, which started in the 1980s (although there were a few examples long before then), embraced the artifical organism in the environment concept. They had simple programs and no traditional internal models.

If you’ve ever made any kind of robot, or a software agent in some environment, you may have discovered how complicated and or unplanned the behavior becomes so easily.

The adaptability and flexibility of organisms has not yet been matched by artificial creatures. I’ve discussed some of this before in my article “Softer, Better, Faster, Stronger: The Coming of Soft Cybernetics“.

If you’ve ever made a mobile robot or any other electromechanical system, and expected it to work perfectly as designed, you have probably encountered a rude awakening. It never works “out of the box” (unless you went through many cycles before putting it in the box). In fact, engineering in general is more of a building out of existing working things. And then your specific project still has to have cycles of test and/or integration, etc. And that brings me to response two: the meta.

2. The Meta: Development Methodology

The meta aspect is management of projects and what process the “creator” and his/her team uses. I don’t particularly care how similar a process is to biology…although biological evo-devo is quite interesting. I’d love to find ways of doing things that are totally alien to biology.

It’s just that I’ve found that cycles of development (“iterations” or “sprints”) have to happen. And it’s much better if there are feedback loops between testing with contexts. And contexts are environments, other artificial equipment, users, and so on.

Iterative development processes almost always work better than sequential types like Waterfall. In fact, I’ve never seen a sequential development process work out well. Others have discovered this to. It’s probably part of the reason why Agile software development processes are becoming the most popular.

Anyway, comments about why generative and iterative processes work in our version of the universe are welcome.

It’s certainly not new to propose recursion as a key element of the human mind—for instance Douglas Hofstadter has been writing about that since the 1970s.

nested recursion

Michael C. Corballis, a former professor of psychology, came out with a new book this year called The Recursive Mind. It explains his specific theory that I will attempt to outline here.

The Recursive Mind

As I understand it, his theory is composed of these parts:

1. The ability of the human mind to generate concepts recursively is what causes the main differences between homo sapiens and other animals.
2. A Chomskian internal language is the basis for all external languages and other recursive abilities. (See this blog post by Corballis for a summary of an internal language as a universal grammar).
3. External languages evolved on top of the recursive abilities primarily for storytelling and social cohesion.
4. External languages started with gestures, and most likely were followed by mouth clicking languages before vocal languages emerged.

You’ll notice that toolmaking and other modern human capabilities are not mentioned in my list there. That is because those are considered to be evolved/developed after the recursive mind appeared and after rudimentary language based on recursion appeared. The author talks about how the ability to build multi-part tools and using tools to make tools probably depends on recursion, but he thinks that came after a certain amount of language development.

recursive construction

A host of abilities might be dependent on recursive thinking, even things we take for granted like story telling. Planning, talking about the future, and making fictional stories all might be dependent on recursive processing.

primitive gestures

Corballis has been doing research on gestures for a long time. By gestures we mean both bodily and facial. It certainly sounds plausible based on the evidence we have that gestures might have been the first real external language. Corballis claims that the discovery of mirror neurons added support for this theory. A primate watching another one perform an action has mental processing similar to actually doing the same action itself. Corballis proposes here and in previous works that sign language with grammar and syntax appeared long before it was mainly replaced with the cultural development of vocal speech.

(As a related aside, see this TED video about the power of communication via dance.)

Conclusion and a Warning

The Sierpinski Triangle

It’s certainly an interesting theory, and I can buy that recursion is part of, if not the single key element, of a general protocol in the mind. Even if we forget the linguistic aspect, the power of recursion seems to be a fundamental ability of the mind at some level.

Fortunately, as a computer programmer (amongst my many roles), I don’t have to limit myself as academics love to do when talking about the sole “language of mind” or the single important algorithm or type of algorithm needed to turn an pre-human mind into a human mind. I can easily imagine lots of protocols (I think that is a better word than “language” for system communications) at all kinds of arbitrary levels, in many relationships to each other. I think it’s kind of silly to assume there’s only one universal protocol and that it underlies all the others. Even in a digital computer (of which most computers are), the only “general” protocol that underlies all others is the fact that information is represented with binary. You have to go to another level above that to describe anything else, and it won’t be completely general. And a digital computer is much simpler than the brain. But what about the fundamental difference between humans and other animals? Well, again, recursion seems to be a good candidate, but it wouldn’t surprise me if it’s only one of several intertwined informational abilities that make human minds different than others.

Postscript

Based on comments on Science 2.0, I may have made this summary too thin. So why exactly would recursion be of interest to single out? Isn’t it just one of many run-of-the-mill features of information processing? Basically, Corballis proposes this:

Generative functions require recursiveness. Episodic memory requires generative functions. Episodic memory may be unique to humans. Planning future events and making fictional stories requires episodic memory. Communication of future events and storytelling–which in turn requires ways to communicate the time component–may have co-evolved with human external language abilities.

References

[1] Corballis, M.C. The Recursive Mind. Princeton University Press, 2011.

Image Credits

Inception Chair by Vivian Chiu
book cover, Princeton University Press
Derek O’ Reilly
Rhys Davenport (found via Sean Williams)
Sierpinski Triangle, public domain

I just published version 2 of my Enactive Interface Perception essay over on Science 2.0.

It’s now called “Enactive Interface Perception and Affordances”.

Games are not just for fun anymore—and indeed “fun” is not a good enough description for the psychology of gameplay anyway. Designers are trying to “gamify” applications which traditionally were not game-like at all. And this isn’t limited to just the Serious Games movement that’s been around for several years. This is a type of design thinking that has spread from the gaming world and is now merging with the User Experience Design / Interaction Design world.

Beyond the hype and mistakes of gamification that might be going on right now, there does seem to be a design thinking emerging with the intention to increase engagement and motivation of products. I assume the business angle is that this of course can result in more users and keeping users longer.

Dustin DiTommaso, experience design director at Mad*Pow, presented “Beyond Gamification: Architecting Engagement Through Game Design” yesterday. As I already mentioned, he says how “fun” is not a good definition. His main psychological theory (at least for this presentation) is Self-Determination Theory (SDT). What follows are my notes based on DiTommaso’s presentation (hopefully I haven’t butchered it too much).

Games keep people in intrinsic motivation. There are three intrinsic motivation needs (these terms are directly from SDT):

1. Competence
2. Autonomy
3. Relatedness

Competence

This is about meaningful growth. Good games achieve a path to mastery. The user experiences increased skill over time. There are nested short-term achievable goals that lead to success of the overarching long-term goal.

The experience should be that of a challenge. If you’re familiar with Csíkszentmihályi’s Flow, it is similar (or perhaps exactly the same) as that.

As with most good interaction design, there has to be feedback. Specifically, there has to be:

1. Meaningful information
2. Recognition
3. Next steps

Action-Rules-Feedback loop

On the meaningful info item: Progress should be made visible. But, rewards have to be meaningful. Rewards for meaningless actions are not good in the long term—-users will hack (or “game”) the system if they get bored and/or detached.

Screenshot from Rockband 3 (developed by Harmonix)

DiTommaso says that you should strive for “juicy” feedback. For example, the interface for the popular video game series Rock Band is entirely “juicy” feedback. Visual Thesaurus is a good example of juicy feedback that is less flashy than Rock Band.

Failure should be allowed in a graceful manner if it provides an opportunity to learn and grow. This might sound weird for interaction design where usually you don’t want users to fail at all. Mad*Pow supposedly has done research to back this up.

Autonomy

The game belongs to the user. Choice, control, and personal preference lead to deep engagement and loyalty. There has to be the right feedback for the type of autonomy for a given user. Experience pathways can be designed “on rails” to limit or give the illusion of freedom.

To motivate sustained interest the game should provide opportunities for action. For example, on a ski mountain, there are literally multiple pathways, and multiple levels of difficulty.

Relatedness

This is about mutual dependence. We’re intrinsically motivated to seek meaningful connections with others.

A game should provide meaningful communities of interest. The users should somehow be able to value something in the game beyond the mechanics that run the system. The users should get recognition for actions that matter to them. And they should be able to inject their own goals. An example of a system that allows user-customizable goals is Mint.com.

It’s also worthwhile to think of non-human relatedness. Dialogues between user interface avatars and humans actually matter and affect motivation. They are a type of relationship. So scripts, text, tones, etc. are very important.

Conclusion

This is my rough interpretation of DiTommaso’s “Framework for Success” intended for designers and related professions.

1. Why gamify? Consider the users and the business cases.
2. Research the player profile(s) (perhaps game-oriented personas?). This research can and should inspire the design. What are the motivational drivers? Is it more about achievement or enjoyment? Is it more about structure or freedom? Is it more about control of others or connecting with others? Is it more about self interest or social interest?
3. Goals and objectives: What’s the Long Term Goal? What steps? Etc.
4. Skills and actions: consider what physical, mental, and social abilities are necessary. Can the skills be tracked and measured?
5. Look through the lenses of interest. The concept of “lenses of interest” comes from Jesse Schell. The list of lenses provided by DiTommaso are:
   • Competition types
   • Time pressure
   • Scarcity
   • Puzzles
   • Novelty
   • Levels
   • Social pressure/proof (the herd must be right)
   • Teamwork
   • Currency
   • Renewals and power-ups
6. Desired outcomes: What are the tangible and intangible rewards? What outcomes are triggered by user actions vs. schedules? How do users see and feel incremental success and failure on the way to the Ultimate Objective?
7. Play-test and polish: Platforms are never done. This isn’t really specific to gamification. I would say this is about the general shift from waterfall to iterative development methodologies (which I have used successfully in my own work). This can even extend out to the actual end users—they can be involved in the loop and even expect updates for improvement.

Image Credits:
1. Nightrob
2. Dustin DiTommaso / Mad*Pow
3. IGN
4. Mount Sunapee