Content/Internalism Space and Interfacism

Posted in artificial intelligence, interfaces, philosophy on December 29th, 2013 by Samuel Kenyon

Whenever a machine or moist machine (aka animal) comes up with a solution, an observer could imagine an infinite number of alternate solutions. The observed machine, depending on its programming, may have considered many possible options before choosing one. In any case, we could imagine a 2D or 3D (or really any dimensionality) mathematical space in which to place all these different solutions.

Fake example of a design/solution or analysis space.

Fake example of a design/solution or analysis space.

Of course, you have to be careful what the axes are. What if you chose the wrong variables? We could come up with dimensions for any kind of analysis or synthesis. I want to introduce here one such space, which illuminates particular spectra, offering a particular view into the design space of cognitive architectures. In some sense, it’s still a solution space—as a thinking system I am exploring the possible solutions for making artificial thinking systems.

Keep in mind that this landscape is only one view, just one scenic route through explanationville—or is it designville?

This photo could bring to mind several relevant concepts: design vs. analysis, representations, and the illusion of reality in reflections

This photo could bring to mind several relevant concepts: design vs. analysis, representations, and the illusion of reality in reflections

Content/Internalism Space

In the following diagram I propose that these two cognitive spectra are of interest and possibly related:

  1. Content vs. no content
  2. Internal cognition vs. external cognition
Content vs. Internalism Space

Content vs. Internalism Space

What the Hell is “Content”?

I don’t have a very good definition of this, and so far I haven’t seen one from anybody else despite its common usage by philosophers. One aspect (or perhaps container) of content is representation. That is a bit easier to comprehend—an informational structure can represent something in the real world (or represent some other informational structure). It may seem obvious that humans have representations in their minds, but that is debatable. Some, such as Hutto and Myin, suggest that human minds are primarily without content, and only a few faculties require content [1]:

Some cognitive activity—plausibly, that associated with and dependent upon the mastery of language—surely involves content. Still, if our analyses are right, a surprising amount of mental life (including some canonical forms of it, such as human visual experience) may well be inherently contentless.

And the primary type of content that Hutto and Myin try to expunge is representational. It’s worth mentioning that representation can be divorced from the Computational Theory of Mind. Nothing here goes against the mind as computation. If you could pause a brain, you could point to various informational states, which in turn compose structures, and say that those structures are “representations.” But they don’t necessarily mean anything—they don’t have to be semantic. This leads to aboutness…

Another aspect of content is aboutness. “Aboutness” is an easier to use word in place of the philosophical term intentionality; “intentionality” has a different everyday meaning which can cause confusion [2]. We think about stuff. We talk about stuff. External signs are about stuff. And we all seem to have a lot of overlapping agreements on what stuff means, otherwise we wouldn’t be able to communicate at all and there wouldn’t be any sense of logic in the world.

So does this mean we all have similar representations? Does a stop sign represent something? Is that representation stored in all of our brains, thus we all know what a stop sign means? And what things would we not understand without in-brain representations? For instance, consider some sensory stimulus that sets off a chain reaction resulting in a particular behavior that most humans share. Is that internal representation, or are dynamic interfaces, however complicated, something different?

Internal vs. External

This is about the prevailing cognitive science assumption that anything of interest cognitively is neural. Indeed, most would go even further than neural and limit themselves just to the brain. The brain is just one part of your nervous system. Although human brain evolution and development seem to be the cause of our supposed mental advantages over other animals, we should be careful not to discard all the supporting and/or interacting structures. If we take the magic glass elevator a bit down and sideways, we might want to consider our insect cousins in which the brain is not the only critical part of the nervous system—and insects can still operate in some fashion for days or weeks without their brains.

I’m not saying here that the brain focus is wrong; I’m merely saying that one can have a spectrum. For instance, a particular ALife experiment could be analyzed from the point of view of anywhere on that axis. Or you could design an ALife situation on any point, e.g. just by focusing on the internal controller that is analogous to a brain (internalist) vs. focusing on the entire system of brain-body-environment (externalist).

Interfacism

Since there has to be an “ism” for everything, there is of course representationalism. Another philosophical stance that is sometimes pitted against representationalism is direct realism.

Direct realism seems to be kind of sloppy. It could simply mean that at some levels of abstraction in the mind, real world objects are experienced as whole objects, not as the various mental middlemen which were involved in constructing the representation of that object. E.g., we don’t see a chair by consciously and painstakingly sorting through various raw sensory data chunks—we have an evolved and developed system for becoming aware of a chair as an object “directly.”

Or, perhaps, in an enactivism or dynamic system sense, one could say that regardless of information processing or representations, real world objects are the primary cause of information patterns that propagate through the system which lead to experience of the object.

My middle ground between direct and indirect realism would, perhaps, be called “interfacism,” which is a form of representationalism that is enactivism-compatible. Perhaps most enactivists already think that way, although I don’t recall seeing any enactivist descriptions of mental representation in terms of interfaces.

What I definitely do not concede is any form of cognitive architecture which requires veridical, aka truthful, accounts anywhere in the mind. What I do propose is that any concept of an organism can be seen as interactions. The organism itself is a bunch of cellular interactions, and that blob interacts with other blobs and elements of the environment, some of which may be tools or cognitively-extensive information processors. Whenever you try to look at a particular interaction, there is an interface. Zooming into that interface reveals yet more interfaces, and so on. To say anything is direct, in that sense, is false.

For example, an interfacism description of a human becoming aware of a glass of beer would acknowledge that the human as an animate object and the beer glass as an inanimate object are arbitrary abstractions or slices of reality. At that level in that slice, we can say there is an interface between the human and the glass of beer, presumably involving the mind attributed to the human.

Human-beer interface

Human-beer interface

But, if we zoom into the interface, there will be more interfaces.

Zooming in to the human-beer interface reveals more interfaces.

Zooming in to the human-beer interface reveals more interfaces.

And semantics will probably require links to other things, for instance we don’t just see what is in front of us—we can be primed or biased, or hallucinate, or dream, etc. How sensory data comes to mean anything at all almost certainly involves evolutionary history and ontogeny (life history) and current brain states at least as much as any immediate perceptual trigger. And our perception is just a contraption of evolution, so we aren’t really seeing true reality ever—it’s a nonsensical concept.

I think interfacism is possibly a good alternate way to look at how cognition, be it wide or narrow—at any given cognitive granularity, there is no direct connection between two “nodes” or objects. There is just an interface, and anything “direct” is at a level below, recursively. It’s also compatible with non-truthful representations and/or perception.

Some might say that representations have to be truthful or that there are representations, for instance in animal behaviors, because there is some truthful mapping between the real world and the behavior. With an interface point of view we can throw truth out the window. Mappings can be arbitrary. There may be consistent and/or accurate mappings. But they don’t necessarily have to be truthful in any sense aside from that.


References
[1]D. D. Hutto and E. Myin, Radicalizing enactivism: basic minds without content. Cambridge, Mass.: MIT Press, 2013.
[2]D. C. Dennett, Intuition Pumps and Other Tools for Thinking. W.W. Norton & Company, 2013.


Image credits
Figures by Samuel H. Kenyon.
Photo by Dimosthenis Kapa

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A World of Affect

Posted in artificial intelligence, interaction design on August 2nd, 2013 by Samuel Kenyon

Back in the fall of 2005 I took a class at the MIT Media Lab called Commonsense Reasoning for Interaction Applications taught by Henry Lieberman and TA’d by Hugo Liu.

Screenshot from Affectworld

For the first programming assignment I made a project called AffectWorld, which allows the user to explore in 3D space the affective (emotional) appraisal of any document.

The program uses an affective normative ratings word list expanded with the Open Mind Common Sense (OMCS) knowledgebase. This norms list is used both for appraising input text and for generating an affect-rated image database. The affective norms data came from a private dataset created by Margaret M. Bradley and Peter J. Lang at the NIMH Center for the Study of Emotion and Attention, consisting of English words rated in terms of pleasure, arousal and dominance (PAD).

To generate the interactive visualization, AffectWorld analyzes a text, finds images that are linked affectively, and applies them to virtual 3D objects, creating a scene filled with emotional metaphors.

The image files were scraped from a few places, including Eric Conveys an Emotion, in which some guy photographed himself making every emotional expression he could think of and then started doing requests. I used OGRE for the 3D graphic engine.

Screenshot from Affectworld

Screenshot from Affectworld

So what was the point? If I remember correctly, somebody asked that in the class and Hugo interjected that it was art. Basically the emotional programming looks to an outsider like a pseudo-random image selector applied to cubes in a 3D world…well, that’s not completely true. With a lot more pictures to choose from (with accurate descriptive words assigned to each picture), I think that one could make a program like this that does give some kind of emotional feel that’s appropriate from a text.

Certainly stories are a kind of text that explicitly describe affect: the emotions of characters and the environments enveloping the characters. AffectWorld programs would never be perfect though, because stories themselves are just triggers, and what they trigger in any given person’s mind is somewhat unique. This is perhaps the realm that film directors using published stories live in—creating a single visual representation of something that already has thousands or millions of mental representations. But in an AffectWorld, I simplify the problem but assuming from the beginning that the visual pictures are arbitrary. It is only the emotional aspects that matter.

At the time of the demo, some people seemed momentarily impressed, but that was partially because I made them look at a bunch of boring code and then suddenly whipped out the interactive 3D demo. Otherwise, my first version of AffectWorld was just a glimmer of something potentially entertaining. I started another project for that class which I will talk about in a future blog.

Screenshot from Affectworld

Screenshot from Affectworld

Part of the reason why I took the class was because I was skeptical of using commonsense databases, especially those based on sentences of human text. During my early natural language explorations I became suspicious of what I learned later was called the “hermeneutic hall of mirrors” by Stevan Harnad—in other words, computer “knowledge” dependent on English (or any other human language) is basically convoluted Mad Libs. However, I did witness other students making interfaces which were able to make use of shallow knowledge for unique user experiences. Just as Mad Libs lends itself to a kind of surprising weird humor, so do some of these “commonsense” programs.

An example of mad libs in action.

An example of mad libs in action.

This is somewhat useful for interaction designers—in some cases a “cute” or funny mistake is better than a depressing mistake that triggers the user to throw the computer out the window. Shallow knowledge is another tool that is perfectly fine to use in certain practical applications. But it’s not a major win for human-level or “strong” AI.

The Semantic Web is a similar beast as far as I can tell. Despite recent good-intentioned articles full of buzzwords, the Semantic Web has been around for a long time, at least conceptually. Seven years ago I went to an AI conference where Tim Berners-Lee (the inventor of the World Wide Web) told us about how the Semantic Web was the new hotness and its relationship to AI (AAAI-06 Keynote Address). OWL, the web ontology language standard, had already been started. And now the semantic web is apparently finally here, sort of. Companies that rose to power since the concept of OWL like Facebook and Google have made massive semantic networks out of user data. These are great enablers and we probably have not even seen the killer apps to come out of these new semantic nets. And in some narrow contexts, semantic net powered apps could be smarter than humans. But they do not understand as human organisms do. Sure, there could be a lot of overlap with some level of abstraction in the human mind, and it is not necessarily true that all knowledge is grounded in the same way or at the same level.

Someone will probably post a comment along the lines of “well that is ultimately how the brain works, just a big semantic net in terms of itself” which skips the issue of the nodes in computer semantic networks that depend on human input and/or interpretation for the meaning. Or somebody might argue that the patterns have inherent meaning, but I don’t buy that for the entirety of human-like meaning because of our evolutionary history and the philosophical possibility that our primitive mental concepts are merely reality interfaces selected for reproductive ability in certain contexts.

Epilogue

Screenshot from Affectworld

Screenshot from Affectworld

At the time of the commonsense reasoning class—and also Marvin Minsky’s Society of Mind / Emotion Machine class I took before that—a graduate student named Push Singh was the mastermind behind Open Mind Common Sense. Although I was skeptical of that kind of knowledgebase, I was very interested in his approaches and courage to tackle some of the Society of Mind and Emotion Machine architectural concepts. His thesis project was in fact called EM-ONE, as in Emotion Machine 1, dealing with levels of cognition and mental critics. I didn’t know him very well but I talked to him several times and he had encouraged me to keep the dialogue going. I recall one day when I reading a book about evo-devo in the second floor cafe at the Harvard Co-op bookstore, ignoring all humans around me, Push happened to be there and made sure to say hello and ask what I was reading.

One day I went to his website to see if there was anything new, and found a message from somebody else posted there: Push was dead. He had committed suicide. Below that, stuck to my computer monitor, lurked an old post-it note with a now unrealizable to-do: “Go chat with Push.”


Image credits:


Mad libs example by Becca Dulgarian via Emily Hill

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What is a Room?

Posted in artificial intelligence, interfaces on February 5th, 2013 by Samuel Kenyon

We all share the concept of rooms. I suspect it’s common and abstract enough to span cultures and millennia of history.

a room

a room

The aspects of things that are most important for us are hidden because of their simplicity and familiarity. (One is unable to notice something because it is always before one’s eyes.)
—Wittgenstein

Rooms are so common that at first it seems silly to even talk about rooms as an abstract concept. Yet, the simple obvious things are often important. Simple human things are often also quite difficult for computers and artificial intelligence.

Is there a such thing as a room? It seems to be a category. Categories like this are probably the results of our minds’ development and learning.

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The Timeless Way of Building Software, Part 1: User Experience and Flow

Posted in interaction design on May 31st, 2012 by Samuel Kenyon

The Timeless Way of Building by Christopher Alexander [1] was exciting. As I read it, I kept making parallels between building/town design and software design.

Architecture

We’re not talking any kind of architecture here. The whole point of the book is to explain a theory of “living” buildings. They are designed and developed in a way that is more like nature in many ways—iterative, embracing change, flexibility, and repair.

Design is recognized not as the act of some person making a blueprint—it’s a process that’s tied into construction itself. Alexander’s method is to use a language of patterns to generate an architecture that is appropriate for its context. It will be unique, yet share many patterns with other human-used architectures.

This architecture theory includes a concept of the Quality Without a Name. And this is achieved in buildings/towns in a way that is more organic than the popular ways (of course there are exceptions and partially “living” modern architectures).

User Experience

Humans are involved in every step. Although patterns are shared, each building has its own appropriate language which uses only certain patterns and puts them in a particular order. The entire design and building process serves human nature in general, and specifically how humans will use this particular building and site. Is that starting to stir up notions of usability or user-centered design in your mind?

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