Wednesday, 25 April 2012
The thought machine
Computers allow the information-processing paradigm, which has profound implications on both cognitive science and artificial intelligence. Information processing seems to have played for cognition the role that the microscope played for biology.
For a long time I thought that the stumbling block which makes people consider intelligent machines as not truly cognitive was not consciousness, but intentionality. Machines don't have their own goals, they can't choose for themselves to take another path than the one the programmer has endowed them with, neither can they come up with problem-solving skills and methods that haven't been put there by a human.
Processing information for a goal seems to be the defining quality that characterizes living systems, which can brings about cognitive behavior and processes which we don't see in machines.
Yet something is missing from this picture. Sometimes we forget that actually organs keep functioning automatically, just by being alive. That them being alive means they keep attempting to fulfill their function. So the function of our brain might be to process information, be it with a goal or not. It might be in its programming to do so, independent of if the owner has that as a goal or not.
This is where curiosity, as a human/animal trait comes into play. Many humans go out of their way to obtain information which couldn't possibly affect their survival. Yet the drive to acquire more information, to compare it to the previous one, to patch the types of information together, can feel as important for these people as eating (or more, at least until they get really hungry).
So it might be that the information-processing machine is simply in overdrive for some people. That it takes over. And of course they are survival advantages in that (if you are in the right job to manifest that talent, and if you can make a difference to the community through what you are processing).
Perhaps we should also ask ourselves why it is that our information-processing machine seems to always be on. Do we really need to do that much information processing? Is that an inherent part of the human condition, that we would have needed to develop this constant stream of thought/awareness?
Of course we feel that our thought machine sleeps at times - we zone out and can't think of the things we would like to think of, can't solve the things that we would like to solve.
Sometimes our minds seem blank and sometimes our ability to focus is slippery. Our machine can't seem to come to terms with what we want to direct it towards, and escapes our goal, while swimming heavily in its own purposes and plays at information-processing. It keeps on asking us questions we don't want or have the time to answer then and there, instead of helping us solve what we put in our schedule as a priority. It keeps focusing on things that seem unrelated to our task, albeit interesting for the context of our lives or the way we understand the world and universe and things.
That is one of the reasons for which some people use diaries. It is not because they need to constantly say what they did that day. But because they need to give their information processing machine a place to express its concerns, and process all those things that are in the back of our head, and that otherwise would stand in the way of our normal productivity. And they are questions in our head that we can't escape, that dominate our mental landscape in such a powerful way, that the old advice applies "the only way to escape a temptation/desire is to fulfill it".
In this context, the only way to get over that preoccupation that our mind has for certain subjects is to give it free rein to think about them at will and in a focused manner, so that we can then direct it at will ourselves after it has settled into having the answers that it needed, or being closer to them.
The mind-body system might not be a dualistic machine, but our own mind can be one at times, and we can remark and reflect on the difference between the things that we want to think about and the things that seem to "think us".
Our information-processing machine is not a completely tamed one, and perhaps it shouldn't be. As it knows better what our deep goals, interests and questions are than our daily task planner ever could.
Back to the intentional/non-intentional debate, I think there that our information-processing device just plays at times. It is a ludic device that takes pleasure (and rewards are significant for motivating behavior) from being active and trying to think and "solve" the world around us.
This can be easily seen in perception illusions, where we can't help ourselves but to solve certain patterns to some known common pattern. Or we can experience it when we look with no purpose at some patterns on the wall while thinking of something else and realize after a few minutes that our mind has kept on trying to arrange those patterns in various configurations.
The major implication of that thought is that it means we are more machine-like and less intentional than we thought. And that many times it is the machine that drives us forward, not the intention.
So if information processing is a function, and our brain can't help but do it, where does that leave the debate on the importance of intentionality as being a main feature that differentiates human cognition (our benchmark) from machine cognition?
First of all having this ludic information processing machine is not an easy process to replicate in itself. I don't know of any artificial cognitive machine that just keeps on adding random observations and drawing random conclusions and inferences out of them. Are they rules or general guiding principles which apply to our mental play? To be found out.
Second, our intentionality - our goals - might predispose us to gather information about how we can solve those even during our ludic time. We might be collecting information on the weird way the patterns are distributed on the wall and associate it through some far analogy to one of the important problems we are struggling with (and which is goal related) - in fact my research focuses on this process.
Second, there is a definite degree of independence, free will and randomness (read uniqueness if you like) that comes with this ludic information-processing machine, and probably defines the human cognitive experience. To be constantly only goal-directed is, after all, what we imagine machines to be. (very funny that we think that, but we also think that us having goals and free will is what makes us human).
Third, our experience in the world and in our thoughts is sometimes what makes new goals emerge. Which is not an experience replicated by a machine yet. And I don't mean refining goals purposefully - like in the case of creating subgoals in ACT-R. I mean simply thinking about some random things then suddenly deciding some possibility is attractive enough to be worth investigating, or experiencing things and then deciding to make something our goal just because we like it (or without particular knowledge of what cognitive goal that investigation might serve).
Therefore I don't see the idea of our brain being an information-processing machine that does just that all day long cause it likes to and that is its function as something that makes intentionality less important. Perhaps it is just bridging a little bit more the gap of our minds being mechanisms that have their own function, and drive us with the expression of this function, rather then other way around (us setting goals, and constantly directing our machine forward).
How would a neural implementation or model of either intentionality or ludic information processing look like? That is what I would really like to see.
Wednesday, 15 February 2012
Throwing away main results - the collateral benefits hack
Do motivated people really have their eyes on the prize? Yeah, probably, but you might be surprised about some of their actions. They might just throw away what you thought was the main benefit of their actions, and the goal you thought they were pursuing.
And it might not even be that they are behaving irrationally. But that you misunderstood their goal.
I was just thinking about this kind of behavior, from a personal perspective. They are moments when you finally got your lot organized, you know what you have to do the next 50-200 steps to get to your goal, things are finally making sense. You are content: you managed to subdivide a problem that seemed very hard to achieve into manageable subgoals, and all you need to do, in theory, now that you traced a path to your goal, is to keep walking (disclaimer: no encouragement for (a certain brand of) whiskey consumption has been intended here, but c'mon, they do have a cool ads!).
Yet it doesn't happen. You don't get on with it. You don't move to the goal, although it's finally manageable. And its not cause you are lazy - you just discover that now that you finally defined that threatening problem in terms of manageable steps, you can focus on other things, that are far more important to you for some bizarre reason.
Point taken, the managerial part of your mind is now pissed off with u. And for a good reason: you've been terrified by this problem for so long, and now that finally your brain has provided the solution, instead of defeating the monster you just.... start working on a different task? How uncool is that?
But sometimes you need to trust that your brain knows what it's doing (it got on with keeping your body alive without that much input from you quite well and for quite a while). That you might not be that dedicated to the goal you just mentally solved. That knowing you can achieve it was the main benefit, the thing that helped you move deeper into what it's actually important for you to do.
And sometimes - rarely, but it happens - you might need to just be tolerant with throwing away most of what seems the result of your action. It might be that those results where not what you where there for in the first place, but some collateral benefit, which was a necessary resource for one of your other goals.
I was just thinking about this when I stumbled across a great description of that exact situation in a book chapter by Klahr(1):
But to all of you out there that think about yourselves as highly determined people, yet cringe at seeing yourself throwing away main results of what you worked for - relax. Try to understand the bigger goal. And see how smart your brain has been in pursuing it. Don't instill forced discipline just to satisfy your managerial mind - because you came up with too good of a plan to drop it just now. That part of your mind shouldn't be the master. It is just a tool. A costly tool, that takes lots of pride in itself, and likes its own work, but finally just a tool for your deeper goals.
You might be interested to know that some of the most creative minds of the history have done exactly that: hacked into problems, thrown away what to others seemed the main benefit, kept pursuing their task using lateral thinking tools until they got all the little pieces of the puzzle that they needed. And then a solution seemed to emerge out of nowhere (to others).
Just make sure what you are throwing away doesn't have a dangerous impact on your life or others. Other than that, you can keep on playing. It's what problem-solving is all about.
The juggling metaphor of solving tasks is well known: one has too many tasks on one's hands (wonder if one could have to many hands on one's task) and can't possibly cope with everything in the same time. Yet one copes by giving big pushes to the tasks, making them go into a sleeping cycle, when they don't need attention. It's about dealing with emergencies just before they happen. And it is very stressful, although it does imply the somewhat borderline satisfaction of dealing with more than you can.
But this collateral benefits hack is more like what a trapeze artist does. You are not throwing balls in the air, but throwing yourself into goals, being in motion, hoping that the trapeze you just landed will (while still in motion) meet up with another one that will take you a bit closer to your goal, or closer to something that can take you to your goal, or closer to something that is closer to something that can take you to your goal, recursive reasoning for the win!
Part of the path you might have taken might not be intended. It might not be meaningful. It might just be the search for that trapeze which moves you in the range of your dreams, at whatever recursive depth is still exciting for you and still makes you feel near them. And sometimes you might take a path that involved days of tasks just cause you needed the equivalent of a paperclip out of there. But it might be a paperclip without which you can't go any further.
The price that we pay for various parts that we need in our problem-solving might be completely unscaled to what we get from an action. But adapted to the importance getting that thing has for our goals and dreams.
And sometimes taking a path which seems not yours, not meaningful, which seems to take you away rather than towards your goal, is a painful thing (imagine what AI programs must feel when you force them out of their local optima). Yet some paths must be taken, filtered for that paperclip and thrown away. Don't try to keep everything. Drop some balls on the floor. Don't clutch onto them in despair, throw some out there in the world and see what comes back. And find your paperclip!
The creative mind has reasons that the reasonable mind doesn't have...
(1) Klahr,D. (2000).Exploring Science: The cognition and development of discovery processes - Ch.2 Scientific discovery as Problem Solving. Cambridge, MA: MIT Press
I was just thinking about this kind of behavior, from a personal perspective. They are moments when you finally got your lot organized, you know what you have to do the next 50-200 steps to get to your goal, things are finally making sense. You are content: you managed to subdivide a problem that seemed very hard to achieve into manageable subgoals, and all you need to do, in theory, now that you traced a path to your goal, is to keep walking (disclaimer: no encouragement for (a certain brand of) whiskey consumption has been intended here, but c'mon, they do have a cool ads!).
Yet it doesn't happen. You don't get on with it. You don't move to the goal, although it's finally manageable. And its not cause you are lazy - you just discover that now that you finally defined that threatening problem in terms of manageable steps, you can focus on other things, that are far more important to you for some bizarre reason.
Point taken, the managerial part of your mind is now pissed off with u. And for a good reason: you've been terrified by this problem for so long, and now that finally your brain has provided the solution, instead of defeating the monster you just.... start working on a different task? How uncool is that?
But sometimes you need to trust that your brain knows what it's doing (it got on with keeping your body alive without that much input from you quite well and for quite a while). That you might not be that dedicated to the goal you just mentally solved. That knowing you can achieve it was the main benefit, the thing that helped you move deeper into what it's actually important for you to do.
And sometimes - rarely, but it happens - you might need to just be tolerant with throwing away most of what seems the result of your action. It might be that those results where not what you where there for in the first place, but some collateral benefit, which was a necessary resource for one of your other goals.
I was just thinking about this when I stumbled across a great description of that exact situation in a book chapter by Klahr(1):
"Consider the problem faced recently by an unnamed psychologist in getting from an office at Carnegie Mellon University to a conference room at Colorado resort in order to present a talk about scientific reasoning. The "difference" was one of distance, and among the set of distance-reduction operators were flying, walking, biking, and so forth. Flying was the operator that would most rapidly reduce distance, but it could not be applied to the initial condition: that is, one could not fly directly from one office to the conference site. This presented the subproblem of creating conditions for flying (i.e., getting to an airport). Getting to the airport could best be done via taxi, but there was no taxi at Carnegie Mellon. The sub-subproblem involved making a phone call to the cab company. But all the university phones were out of order for the day during a transition to a new system: only the pay phones worked. An even deeper subproblem: make a call on a pay phone. But a lack of coins made it impossible to apply that operator (no pun intended). However, a Coke machine was handy, and it accepted dollar bills and gave change. So the problem solver bought and discarded a Coke (our emphasis) in order to get on the solution path to transport himself to Colorado."Well ok, you will say, but I might have thrown away more than a Coke. So what? Solving some problems involves exactly that kind of lateral thinking. The only thing you need to watch for is not to get trapped in too many lateral thinking loops, not to end up throwing away too many portions. Not to end up living in a lateral loop that was supposed to be a life hack and just doesn't take you to your goal anymore.
But to all of you out there that think about yourselves as highly determined people, yet cringe at seeing yourself throwing away main results of what you worked for - relax. Try to understand the bigger goal. And see how smart your brain has been in pursuing it. Don't instill forced discipline just to satisfy your managerial mind - because you came up with too good of a plan to drop it just now. That part of your mind shouldn't be the master. It is just a tool. A costly tool, that takes lots of pride in itself, and likes its own work, but finally just a tool for your deeper goals.
You might be interested to know that some of the most creative minds of the history have done exactly that: hacked into problems, thrown away what to others seemed the main benefit, kept pursuing their task using lateral thinking tools until they got all the little pieces of the puzzle that they needed. And then a solution seemed to emerge out of nowhere (to others).
Just make sure what you are throwing away doesn't have a dangerous impact on your life or others. Other than that, you can keep on playing. It's what problem-solving is all about.
The juggling metaphor of solving tasks is well known: one has too many tasks on one's hands (wonder if one could have to many hands on one's task) and can't possibly cope with everything in the same time. Yet one copes by giving big pushes to the tasks, making them go into a sleeping cycle, when they don't need attention. It's about dealing with emergencies just before they happen. And it is very stressful, although it does imply the somewhat borderline satisfaction of dealing with more than you can.
But this collateral benefits hack is more like what a trapeze artist does. You are not throwing balls in the air, but throwing yourself into goals, being in motion, hoping that the trapeze you just landed will (while still in motion) meet up with another one that will take you a bit closer to your goal, or closer to something that can take you to your goal, or closer to something that is closer to something that can take you to your goal, recursive reasoning for the win!
Part of the path you might have taken might not be intended. It might not be meaningful. It might just be the search for that trapeze which moves you in the range of your dreams, at whatever recursive depth is still exciting for you and still makes you feel near them. And sometimes you might take a path that involved days of tasks just cause you needed the equivalent of a paperclip out of there. But it might be a paperclip without which you can't go any further.
The price that we pay for various parts that we need in our problem-solving might be completely unscaled to what we get from an action. But adapted to the importance getting that thing has for our goals and dreams.
And sometimes taking a path which seems not yours, not meaningful, which seems to take you away rather than towards your goal, is a painful thing (imagine what AI programs must feel when you force them out of their local optima). Yet some paths must be taken, filtered for that paperclip and thrown away. Don't try to keep everything. Drop some balls on the floor. Don't clutch onto them in despair, throw some out there in the world and see what comes back. And find your paperclip!
The creative mind has reasons that the reasonable mind doesn't have...
(1) Klahr,D. (2000).Exploring Science: The cognition and development of discovery processes - Ch.2 Scientific discovery as Problem Solving. Cambridge, MA: MIT Press
Sunday, 2 January 2011
What happened to our cognitivism? (II)
Activity theory, a concept defined by Alexey Leont'ev, presupposes that through engaging with their environment, humans create production tools that are exteriorized forms of mental processes. In my previous blog I was defining cognitivism as a tool which abstracts away information-processings itself (Leont'ev would be proud).
The question is, although cognitivism seems reasonable for allopoietic systems which have as a goal the production and transformation of information, can it still be reasonable in autopoietic systems, where information is not predefined as a valuable product, but its value comes through the valence it has for the system itself? Put in a simpler way, a computer is an allopoietic system, it is created to store, process, retrieve, present information to it's user. But the information is not the computer itself. In a human mind, there is no necessary bonus for acquiring random information, we have to dictate and decide ourselves what information is important enough to be worth attention and resources, and that information changes the structure of our future enquiries. Also the context of various pieces of information might change the meaning of the information itself - and it's meaning that we are interested in, not information-production and manipulation. Information production and manipulation is just a second-order goal to that of understanding and defending and ultimately surviving and accomplishing other goals. Information acquiring can be a purpose in itself for curious natures, but even then the curiosity of the system is biased in certain directions that are specific for it, and the nature of the receiving neural networks, their previous informational content and preoccupation will bias the meaning that is gathered in abstract pursuits.
Still, if we abstracted away the tool of information processing in cognitivism, there is a good chance that that is what we do in our heads, even if it isn't our primary goal. And if information-processing is partially what we do, we must ask ourselves what is the impact that the context and meaning of the information that we process has on the information-processing? It's impact might change a few details in the information-processing activity, but it might also move our cognitive house in a completely different realm of existence. It might mean that we fail to understand the most important things, while we do understand some details that are not as fully relevant for knowledge formation. Until we determine exactly the importance that the meaning and the context of the information presented to us has on the information-processing, we can't say to know much about how cognitive processes work in a human brain.
If we are to talk about partial truths of human cognition, there is also connectionism. What I always enjoyed in connectionism is it's focus on emergence. Connectionism says - yes, there is information processing, but what emerges beyond the activity of small units that do this information processing transcends in some way the processing. If connectionism would study more how the temporality or the succession of information that runs through a system influences the result of the processing, the philosopher of mind in me would be interested to see the results. We have yet to build more complex connectionist architectures that monitor context and are not there just to fulfil a predetermined simple computational task.
In short, if connectionism would become less computational and more oriented on monitoring systems and the encoding and interaction of larger spaces of knowledge, I think we might find results that are more realistic and in tune with human cognition.
That is to say I don't think we need to model human cognition perfectly in our artificial neural networks, but we need to model more complex neural networks and interactions between them, and switch our focus to that level of processing.
Copyright - Ana-Maria Olteteanu 2011
The question is, although cognitivism seems reasonable for allopoietic systems which have as a goal the production and transformation of information, can it still be reasonable in autopoietic systems, where information is not predefined as a valuable product, but its value comes through the valence it has for the system itself? Put in a simpler way, a computer is an allopoietic system, it is created to store, process, retrieve, present information to it's user. But the information is not the computer itself. In a human mind, there is no necessary bonus for acquiring random information, we have to dictate and decide ourselves what information is important enough to be worth attention and resources, and that information changes the structure of our future enquiries. Also the context of various pieces of information might change the meaning of the information itself - and it's meaning that we are interested in, not information-production and manipulation. Information production and manipulation is just a second-order goal to that of understanding and defending and ultimately surviving and accomplishing other goals. Information acquiring can be a purpose in itself for curious natures, but even then the curiosity of the system is biased in certain directions that are specific for it, and the nature of the receiving neural networks, their previous informational content and preoccupation will bias the meaning that is gathered in abstract pursuits.
Still, if we abstracted away the tool of information processing in cognitivism, there is a good chance that that is what we do in our heads, even if it isn't our primary goal. And if information-processing is partially what we do, we must ask ourselves what is the impact that the context and meaning of the information that we process has on the information-processing? It's impact might change a few details in the information-processing activity, but it might also move our cognitive house in a completely different realm of existence. It might mean that we fail to understand the most important things, while we do understand some details that are not as fully relevant for knowledge formation. Until we determine exactly the importance that the meaning and the context of the information presented to us has on the information-processing, we can't say to know much about how cognitive processes work in a human brain.
If we are to talk about partial truths of human cognition, there is also connectionism. What I always enjoyed in connectionism is it's focus on emergence. Connectionism says - yes, there is information processing, but what emerges beyond the activity of small units that do this information processing transcends in some way the processing. If connectionism would study more how the temporality or the succession of information that runs through a system influences the result of the processing, the philosopher of mind in me would be interested to see the results. We have yet to build more complex connectionist architectures that monitor context and are not there just to fulfil a predetermined simple computational task.
In short, if connectionism would become less computational and more oriented on monitoring systems and the encoding and interaction of larger spaces of knowledge, I think we might find results that are more realistic and in tune with human cognition.
That is to say I don't think we need to model human cognition perfectly in our artificial neural networks, but we need to model more complex neural networks and interactions between them, and switch our focus to that level of processing.
Copyright - Ana-Maria Olteteanu 2011
What happened to our cognitivism? (I)
Cognitivism started it's life with a very basic, elegant assumption - that our brain might do exactly what a computer does - process information in the form of representations. As it usually happens with elegant assumptions due to the fact that they are easy to keep in mind, use and apply, the hypothesis picked up. Still the faults started showing soon - the new mind as a processing-information machine metaphor could not explain some very important things: consciousness, phenomenology, meaning.
It seems to me that in the future, postcognitivism might look back at older disciplines like semiotics and hermeneutics, or not-so-old ones, like communication studies, and borrow in some of their metaphors and objects of study to fully mature itself.
What are the crevices and to-be-patched zones of cognitivism?
First of all, argue post-cognitivists, there is context to be taken into account in whatever information-processing matter. We can't speak of information-processing without considering the effect that the information has on the system, as the system might not encode information at all, but meaning. The exact difference between humans and machines, no matter how performant they are at information processing, lays here - information makes a difference to humans, but not to machines. If information is irrelevant for a human being, it fails to excite interest therefore gather attention and other resources needed to be processed.
We should look at information-processing the right way around, which is we created information-processing machines by abstracting a feature that the human mind has away from the human body - rather how we created robotic arms through abstracting away from the mechanics and functionality of the human arm. That doesn't mean that robotic arms can explain all the functions of the human arm.
Still, it's easier to analyse the things and features that we abstracted away, by the simple fact that we can look at them, observe them, talk about them with greater ease - as we are detached from them. And sometimes these objects are a useful source of backwards reflection and analogy, however we should avoid falling in the trap of considering them all explanatory for
all human thinking.
In human thinking, the process of information processing is called upon mostly because the information is relevant in some way. There is lots of previous information in the system, which colors the new processing, or even the questions that are enquired, the direction of the processing itself. And even partial results might invoke massive changes in the brain's state, as a result of the meaning that possible interpretations might have for the system.
Then there is the inherent problem of the basic cell that information processing is performed upon: the representation. Representations, unlike cells in biology, are a theoretical construct, and a slippery one at that. They take the role of more complex symbols upon which actions are to be performed. But unlike computer memory, the human memory is not that keen in making very detailed representations, carrying them around and manipulating them. Rather the human brain is particularly good at carrying around smaller cognitive loads, and using them in a flexible manner, more appropriate for online requests upon a cognitive processing system.
Representationalism and the idea that there is such a thing as representation came to the fore to complete the analogy of information processing - which must happen on something.
The question of imperfect representation calls to the fore the reality of what human representation might be like. If it is based on meaning, experience and continuous reconstruction of perception according to possible or previously encountered species of meaning and experience, then representation becomes a rather very biased tool.
Considering what it has been said before, it striking that cognitivism wants to talk about perfect cognition in a sense that is not necessarily true for humans, but might only be true to machines.
So if we would consider the principles of cognitivism as being part of an attempt to abstract away perfect cognitive principles and perhaps instantiate them in thinking machines, cognitivism would seem to hit the mark more, rather then with explaining to us human cognition.
But it gets better, in a sense that our perfect view of cognition as information-processing might not be that efficient after all.
A detailed description of that on the next post.
Copyright - Ana-Maria Olteteanu 2011
It seems to me that in the future, postcognitivism might look back at older disciplines like semiotics and hermeneutics, or not-so-old ones, like communication studies, and borrow in some of their metaphors and objects of study to fully mature itself.
What are the crevices and to-be-patched zones of cognitivism?
First of all, argue post-cognitivists, there is context to be taken into account in whatever information-processing matter. We can't speak of information-processing without considering the effect that the information has on the system, as the system might not encode information at all, but meaning. The exact difference between humans and machines, no matter how performant they are at information processing, lays here - information makes a difference to humans, but not to machines. If information is irrelevant for a human being, it fails to excite interest therefore gather attention and other resources needed to be processed.
We should look at information-processing the right way around, which is we created information-processing machines by abstracting a feature that the human mind has away from the human body - rather how we created robotic arms through abstracting away from the mechanics and functionality of the human arm. That doesn't mean that robotic arms can explain all the functions of the human arm.
Still, it's easier to analyse the things and features that we abstracted away, by the simple fact that we can look at them, observe them, talk about them with greater ease - as we are detached from them. And sometimes these objects are a useful source of backwards reflection and analogy, however we should avoid falling in the trap of considering them all explanatory for
all human thinking.
In human thinking, the process of information processing is called upon mostly because the information is relevant in some way. There is lots of previous information in the system, which colors the new processing, or even the questions that are enquired, the direction of the processing itself. And even partial results might invoke massive changes in the brain's state, as a result of the meaning that possible interpretations might have for the system.
Then there is the inherent problem of the basic cell that information processing is performed upon: the representation. Representations, unlike cells in biology, are a theoretical construct, and a slippery one at that. They take the role of more complex symbols upon which actions are to be performed. But unlike computer memory, the human memory is not that keen in making very detailed representations, carrying them around and manipulating them. Rather the human brain is particularly good at carrying around smaller cognitive loads, and using them in a flexible manner, more appropriate for online requests upon a cognitive processing system.
Representationalism and the idea that there is such a thing as representation came to the fore to complete the analogy of information processing - which must happen on something.
The question of imperfect representation calls to the fore the reality of what human representation might be like. If it is based on meaning, experience and continuous reconstruction of perception according to possible or previously encountered species of meaning and experience, then representation becomes a rather very biased tool.
Considering what it has been said before, it striking that cognitivism wants to talk about perfect cognition in a sense that is not necessarily true for humans, but might only be true to machines.
So if we would consider the principles of cognitivism as being part of an attempt to abstract away perfect cognitive principles and perhaps instantiate them in thinking machines, cognitivism would seem to hit the mark more, rather then with explaining to us human cognition.
But it gets better, in a sense that our perfect view of cognition as information-processing might not be that efficient after all.
A detailed description of that on the next post.
Copyright - Ana-Maria Olteteanu 2011
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