why cog sci never lived up to its expected potential

cognitive science initially faced two fundamental issues: cognition and consciousness. the theory of consciousness is subsumed by philosophy of mind, which is an utter quagmire and in which few inroads, either via philosophy or science (neuroscience in particular), have been made to solve the mystery of consciousness. on the other hand, cognition, as a theoretical school, replaced psychoanalysis and behaviorism. the theory was that by reducing input-output to a certain level, the problem of the mind as being a "black box" in the behaviorist approach would be eliminated, and we could have a thorough conceptual and functional understanding of cognition. however, the problem was as follows: by reducing the timeframe and localizing and/or simplifying stimuli, the results would also be interpreted at approximately the same level both in cognition and behavior. the more you reduced, the more inapplicable the results and their implications seemed to be to "real-world" phenomena. in theory, if you reduced everything infinitely, then assuming a 100% mind-brain/body correlation -- in essence assuming the mind-body problem to not exist -- you would have an infinite amount of data and cognition would be solved. a further implication of this is that because you would have an infinite amount of data and fully understood cognition, consciousness would also be solved; if consciousness were not able to be solved, then you would still have a finite amount of data due to the lack of 100% mind-brain/body correlation and cognition would not be solved.

to escape this probably impasse, cognitive science placed faith that artificial intelligence would reach a stage at which it could bridge the gap between having a finite amount of data and having a processing machine capable of intelligently forming connections among the finite amount of data, which in turn allowed for an infinite number of possibilities. by reaching infinity this way, researchers figured the problem of cognition could be solved, and consciousness, if it could not be understood to the point of being created, could at least be adequately explained so as to have eliminated the mind-body problem. however, ai still has yet to remotely approach this expected level, and as such, after decades of research we have simply been left with a mountain, albeit it a finite one, of data and virtually no way to integrate it successfully on a macro level. furthermore, we have all this data and no overarching theory to tie it all together in a meaningful way.

so, where do we go from here? well, to tie it together in a meaningful way means that we have to have an underlying theoretical framework for cog sci. first, we have to determine an even more fundamental question: is cog sci a natural science, a social science, or some other classification such as "brain science"? well, first of all, if you've read my previous post, you should be informed about what i consider hard science to be. in normal hard science, the objects of study are ontologically objective, but in cognitive science, the objects -- or "subjects", as we should refer to them -- are ontologically subjective. however, john searle has stated that epistemic objectivity does not preclude ontological subjectivity. so, "brain science", or cognitive science can be a hard science in theory. however, this only occurs in the first-person ontology, as all philosophy of mind is done starting with one's own intuitions to form premises and then analyzing things from there. so, for cognitive science -- with the emphasis on the *science* part -- it can only be hard science if an experimenter does an experiment on himself, even if that includes using computers and other devices to run the experiment on him as a subject. since most cognitive science research has not been done in this fashion, and has included more than one person in the process of conducting an experiment, then cognitive science has been mostly a social science in practice. so, to restate things, cognitive science in theory is hard science, but in practice is social science.

now, i have defined that cognitive science, as a process, is in theory a hard science, but in practice a social science. now that this matter has been resolved, we can attempt to adopt a theoretical framework for cog sci to operate in. in theory, by reducing all stimuli and timeframes infinitely, you would have an infinite amount of data and could ultimately solve the puzzle of cognition, and with the help of theoretical ai (as opposed to where ai stands currently), possibly explain consciousness and fill in any gaps in defining cognition if the amount of data was not quite infinite (but still extensive and incredibly reductionist). as a result, cog sci would become a meta-social science of sorts. however, in reality, you cannot reduce everything infinitely, the puzzle of cognition remains incomplete, and ai has not reached a point where it can even approach explaining the mystery of consciousness. the underlying goal of social science is to attempt to explain *why* people make decisions -- social science theory makes some inferences and leaps in its theoretical frameworks in order to cover up the fact that it actually does not know why people make decisions -- but cog sci basically attempts to explain *how* the decision making process occurs, and ultimately thought it would get to the *why* -- it only does in theory when it reaches the "meta-level" -- but never actually did. in trying to explain the *how* more than the *why*, cognitive science resembles an approach closer to that of hard science than social science. and, as mentioned in the previous paragraph, *in theory* cognitive science could be practiced as a hard science, thus eliminating the qualia obstacle that faces social science as i outlined in my previous post. so, how can we reconcile a discipline which as a process is hard science in theory but social science in practice with a theoretical framework that is social science in theory but hard science in practice? here is my solution. earlier in this paragraph i mentioned that "social science theory makes some inferences and leaps in its theoretical frameworks in order to cover up the fact that it actually does not know why people make decisions" -- fair enough. cog sci can, at present, and probably to a much better degree in the future, help fill in those gaps in social science's theoretical frameworks that are currently occupied only by inferences and leaps. i'm just starting to learn a bit about john searle's philosophy of society, and i think that there is a fundamental discord between cog sci and the social sciences because social science theory is mostly rooted in postmodernism, whereas cog sci is rooted in an analytic approach. as such, cog sci will probably fit more neatly into the gaps in social philosophy than social science theory, but i do believe that it can, with a few tweaks, still be compatible with social science theory. and just for clarification, my use of the term "cog sci" in the past few sentences refers only to the cognition aspect of cog sci, not consciousness; the issue of consciousness remains firmly rooted in the analytic area of philosophy of mind with no theoretical framework from the postmodernist perspective. i believe that once social scientists explore how to incorporate cog sci findings into their theoretical frameworks instead of dwelling on cog sci's failures, shortcomings, and quagmires that cog sci can make a notable contribution to improving the theoretical frameworks of social science, and in turn, improve the scientific aspect of inquiry in the social sciences.