Graeme Boy's Personal Website

Towards Internationalism

Graeme — Thu, 23 May 2013 21:13:37 +0000

The accident of being born in a poor rather than a rich country is as arbitrary a determinant of one’s fate as the accident of being born in a poor rather than a rich family in the same country

- Thomas Nagel, The Problem of Global Justice, p. 126

Send Letters of Commiseration

Graeme — Thu, 23 May 2013 20:55:34 +0000

Always when in doubt please do send letters of commiseration; at the very least they will be appreciated and at the best they may even succeed in their apparently futile ambition of lightening the burden of bereavement.

- Christopher Hitchens, Hitch-22, p. 156

12 Professional CSS Buttons

Graeme — Mon, 25 Jun 2012 02:41:15 +0000

I slaved away for a few hours and created nice buttons that work purely using CSS,and they are cross-browser compatible. That means that they do not use images at all,and they should format nicely in almost any browser.

Check them out and see if there are any you like:

Button 1

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Button 2

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Button 3

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Button 4

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Button 5

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Button 6

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Button 7

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Button 8

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Button 9

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Button 10

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Button 11

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Button 12

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How to Use Pretty Links with Google App Engine (Python)

Graeme — Sat, 16 Jun 2012 11:33:12 +0000

Whether you are using Google App Engine to create a blogging platform, or some other web app, it’s likely that you will want to create human-readable URLs (pretty permalinks). I’ve seen this question asked many times, with many different answers. This is a tutorial that explains how I create the URL structure that you see on this website.

Many websites may overlook creating a pretty url structure, especially when the developer is not using a complex coding framework or CMS that does it for them. I know that when I started my first Google App Engine blog, I was using a structure like this: http://www.example.com/?post=12 for my posts. This works fine technically, but particularly when it comes to blogs, usually you want your URLs to be structured in a nice and human-readable format, so that people can pass them on without making errors. Also, the URL can then serve as an extra SEO indicator for search engines like Google that take URL information into account as descriptive text. For many bloggers, this is critical.

Configuring your app.yaml to direct the serve to your script.

My app.yaml configuration is very simple, even while I have pretty links.

In app.yaml:

application: graemeboy
version: 1
runtime: python
api_version: 1

handlers:
- url: /stylesheets
static_dir: stylesheets

- url: /images
static_dir: images

- url: .*
script: main.py

This will make all urls direct to your main.py script (or whichever you choose), and from there you can serve the appropriate data or file.

Serving the Appropriate File, According to the URL

For my personal site, I know that there are two groups of data that users want to access on my site: my homepage (the index), or an article that I’ve posted (the posts). So I know that I’m going to create two handlers for this: main, and post. I’m going to serve my main handler if they enter in my exact domain, without any further ‘slug’; I’m going to user the post handler whenever there is more to the URL that just the domain.

In main.py.

#!/usr/bin/env python
from google.appengine.ext import webapp
from google.appengine.ext.webapp import util
from google.appengine.ext.webapp import template
import os

class MainHandler(webapp.RequestHandler):
def get(self):
template_values = {}

path = os.path.join(os.path.dirname(__file__), ‘index.html’)
self.response.out.write(template.render(path, template_values))

class PostHandler(webapp.RequestHandler):
def get(self, slug):
template_values = {}
post_list = {
‘how-to-create-wordpress-plugins’ : ‘wordpress_plugins.html’,
‘app-engine-pretty-links’ : ‘python_pretty_url.html’
}

if slug in post_list:
path = os.path.join(os.path.dirname(__file__), ‘posts/’ + post_list[slug])
self.response.out.write(template.render(path, template_values))
else:
self.response.out.write(‘no post with this slug’)

def main():
application = webapp.WSGIApplication([('/', MainHandler),
('/(.*)', PostHandler)], debug=True)
util.run_wsgi_app(application)

if __name__ == ‘__main__’:
main()

As you can see from above, I’ve set up a python dictionary using the page’s slug as the key, and the name of the HTML file containing the post as the value. You could of course set up a database using the App Engine datastore, using the slug to find the post content, which would be stored as a blob or text value.

Conclusion

Using this very simple system, you can set up human-friendly URLs for your website, so that your site looks professional and is easy to share. Remember, there are also SEO benefits of setting your app up like this, especially if you are running a content-base website. There are many other ways to achieve this effect, the one outlined here is just the one that I use.

Virtue and Personhood from Neurobiological Foundations

Graeme — Sat, 16 Jun 2012 11:15:57 +0000

Determining and Developing Virtues

“Living is not a matter of executing an algorithm, or if it is, we are clueless as to what algorithm we are executing. A good life is a matter of living and being a certain way, or more likely, living and being in one of the multifarious ways that are worthy, which lead to flourishing and, if we are lucky, to happiness.” – Owen Flanagan

Josh Greene asks an important ethical question: are moral judgments perceptions of external truths, or projections of internal attitudes[1]? David Hume said that we cannot derive and “aught” from an “is”. The world is, and we have experiences of this world, but we cannot derive our morals analytically from such observances. But Hume also instructs us that a wise man proportions his beliefs according to the facts, suggesting that there are dispositions – Humean virtues, if you will – that are good to posses, and specifically that these are informed by facts. Patricia Churchland argues along similar lines when she says that science will not tell us what is right or wrong, but that in the domain of moral affairs, empirical observations can guide the understanding of human nature (Brain Based Values). This, says Churchland, will allow us to deal with such moral issues, which arise along a moral continuum, from greater depth, and with more clarity (“…a deeper understanding of what it is that makes us humans…may lead us to a greater understanding of how to cope with social problems” – Brain Based Values). These philosophers help us understand that the study of neuroscience will not relieve us of the burden of deciding what is good and virtuous. However, like the four noble truths in Buddhist philosophy, science may give us truths to use as foundations for morality[2].

Many moral philosophers (including those mentioned in this essay: Hume, Aristotle and Buddhist ethicists) acknowledge that human nature will often conflict with the moral principles we hold. Therefore, in order to live morally (however that is defined for the individual), one needs to cultivate appropriate dispositions (virtues), and this practice allows one to live a moral life. For Aristotle and the Buddhists (that is, virtue theorists), virtues are constructed with the end goal in mind, which, for Aristotle and the Buddhists, is eudaimonia (wellbeing or flourishing). Since this is the highest good (summum bonum), it follows that the function of the person is to practice the virtues that achieve this end: whatever supports flourishing. In sum, for these philosophers, virtues are defined as the best way to achieve eudaimonia. Therefore, virtues depend on two further things: a correct understanding of what eudaimonia is (meta ethics), and discovering the best ways to achieve it (normative ethics). Since this theory involves working with human nature to possess the habitual actions that bring about eudaimonia, if neuroscience has anything to say about human nature, then it may inform virtue theory ethics. We require such knowledge in order to develop practical wisdom (phronesis). For example, if evidence from neuroscience supports a “no self” theory, then some of our human nature (say, selfishness) may conflict with the reality of existence, and wisdom about this will inform our practice of developing virtue (depending on its relation to the summum bonum). For this reason, thinking about the nature of personhood is an excellent foundation for determining what is virtuous (indeed, Farah & Heberlein).

Personhood

“A human being is part of a whole, called by us the Universe, a part limited in time and space. He experiences himself, his thoughts and feelings, as something separated from the rest, a kind of optical delusion of his consciousness.” – Albert Einstein

Farah and Heberlein argue that there is a genetically pre-programmed network in our brains for distinguishing humans from other objects in the world. This system, comprising primarily of the fusiform gyrus and the medial prefrontal cortex, becomes activated by any stimuli similar to prototypical human display (physical or behavioral). The system activates in such a way as to create mental representations that form a basis for the distinction between “persons” and other material objects. Given that it is a separate system that represents persons, Farah and Heberlein argue furthermore for the mental distinction between these types of representations, which implicates a natural tendency towards dualism. The reason why it implicates a dualistic view of reality is that the attempted references of the representations of persons are inherently nonmaterial (“…reflects the child’s assumption that the important part of a person is the nonmaterial part and the resultant difficulty of thinking of people as physical objects”).

Attributes of an object that activate the person network invoke the human observer to assign intentionality to that object (Farah & Heberlein). To what part of the object does such intentionality become assigned? It is assigned specifically to the nonmaterial mental representation of the identity of that object! This is part of an uninformed attempt to find the sine qua non of the person. However, since the reference of this representation does not exist in the external world, it is an illusion to be convinced that it does. However, although the “person” identity might not exist in reality, it may still be sensible to think in terms of persons. Certainly it was evolutionarily adaptive to be able to assign intentions to the acts of others (Personhood). Here the dualistic view of self and other seems to be an implication of this attempt to assign intentions to an immaterial sine qua non. What reason could there be for the supposition that the person identity, as represented by some pattern of activation in the person network of the brain, exists outside of the mind? There is at least one considerable answer. Without the understanding of the functioning of the brain, how else could we predict the behaviors of others without assigning intentionality to some nonmaterial aspect of them? If it is adaptive to assign intentionality to other humans, the already existing identity of the body (based on statistical similarity for continuity) seems a likely place to assign such intentionality. It would make sense then that the intention-assigning function of the brain developed after the identity-assigning function, with the former being a social function for interpreting human behavior, and the latter for identifying objects in general. Would we have had a better understanding of cognitive neuroscience, we would have had a better foundation for understanding and predicting the behavior of others. But we did not, and so we assigned traits to a nonexistent aspect of the human. Farah and Heberlein argue that since the ascription of a person to a human is not a “matter of fact” (not an empirical question), there is “no point to the philosophical or bioethical program of seeking objective criteria for personhood more generally because there are none”. Of course, this is an objectionable claim. Since personhood is indeed a technical philosophical term, with many ethical consequences to its definition, it is precisely the preceding reasons that may make it important to seek criteria for personhood. There seems to be two proceeding options after we integrate this information: either there should be no definition of person and self at all (since persons is an unhelpful illusion), as Farah & Heberlein suggest, or we should define persons and the self as some emerging aspect of neurological and social processes (because, after all, persons is still a meaningful concept).

If persons are illusions created by a uniquely human network in the brain, what is our relation to animals? Of course, the substantive difference that was thought to make humans uniquely superior to other animals, as presumed by those such as Descartes, is precisely the illusion just explored. Humans are different to other animals in the same way that all animals are different to other animals, but not for the reason of personhood in the folk-psychological view. As a technical philosophical term, Person can substantiate this difference, however. One might say that that there is a unique structure in the human brain that allows for civility and “moral sensibility” (Kollek). There is mutual benefit (emerging from the division of labor) among humans to assign rights to one another, while no direct benefit exists for assigning these rights to animals, since they cannot contribute to our civilization. One problem with this sort of reasoning, and variations of this idea, is that it excludes many humans from the category of persons, whom we may like to think of as persons but who cannot contribute in this way. Another way to substantiate the category of persons is to ask if a being can reason, as humans are reasoning animals. However, it is highly problematic to make ethical decisions, such as those involving the treatment of animals, based on this claim. For instance, is it any more permissible to allow the suffering of an animal because it cannot reason in the way that humans can? Since pain processing is a lower level brain function, it differs little between humans and other animals (Farah). This leads us to examine a rather radical (even today) statement by Farah, “If a being is capable of suffering, then it deserves protection from suffering” (Animal Neuroethics). If this statement goes through on the basis of one’s moral reasoning then it implies the necessity for animal rights. The focus in this case moves away from the qualification of beings as persons as the means to protection, towards a radical utilitarian idea of maximizing wellbeing for all sentient beings: compassion dilates. If personhood is not an ontological category that implies a unique ability to experience suffering, then surely this is a defendable conclusion to reach regarding our relation to other animals.

Death of the Person

Thus far, this paper has argued strongly that personhood is not a natural kind, but that the idea of a self might be useful for social reasons. One of these reasons might be the meaning in life that we receive from ascribing such identities, symbolic representations though they might be, to those we love and to ourselves. One question that arises from this, then, is what defines the death of a person. When do we close the final chapter in our minds, so to speak, of our representation of a friend? One thing we know for certain is that the activation of that person’s pattern in our person network is no longer grounds for asserting that the person still exists (since, trivially, even the face will continue to activate the pattern until that face decays beyond recognition). The emphasis must shift from the symbolic to the natural; there is a potential for action of the person involved that is dependent on the empirical state of its body. An intuitive answer to the question might be this: since intentions are formed and executed in the brain, when the brain of the body that is represented by the activation pattern in the person network is no longer active, then the person is dead. Indeed, this is similar to the current criteria for brain death in the U.S. (the permanent cessation of integrated function of the entire brain, including brainstem). However, perhaps we can improve upon the “whole brain” theory of brain death. Since the brain stem is what makes human behavior stereotypical, while other parts of the brain serve to distinguish us (particularly: emotions, memories, etc.), it only follows that the death of the person is not at the inactivation of the brain stem, in exactly the same way that a person is not dead if they are paralyzed. It is precisely the higher functions of the brain that bring about the dispositions we refer to when reflecting on the personality traits of the individual. Nobody says, “When I think of John, I will always remember the profound regularity of his circadian cycles. When his hypothalamus gave out, we knew that we had lost our friend.” We remember our friends that have past for our shared memories, the knowledge that they had and their generosity to share it, their sense of humor, perhaps even the quirks they had due to some emotional conditioning. If the areas of the brain that produce these traits were still alive, with the potential to evoke the traits again (which requires consciousness), then to me, my friend would still be alive (psychological relations are sufficient for persistence of the person). Steven Laureys argues against this view of death, for two reasons. Currently, there is no accurate way to know whether such higher brain regions are still functioning, since, as in the case of consciousness, the neural correlates are not necessarily known (Death, Unconsciousness, and the Brain). Moreover, we are irreducibly closed to knowing whether another being is conscious (Chalmers, 1998). Furthermore, studies have shown it difficult to differentiate between “willful” movement and “automatic” movement, and therefore behavioral hints of consciousness do not reveal the integrity of higher functions. The vegetative state is often misdiagnosed due to this fact, since these behaviors, when performed by those in the minimally conscious state, are underestimated (Laureys). Therefore, such a definition of death, impossible as it is to access accurately, would imply the “burial of breathing ‘corpses’.” We would inevitably declare many living persons dead, simply because we cannot accurately judge the activity of such higher brain functions; this is especially true if islands of cortex were still active. This would necessitate further distinguishing which of the higher order functions are active in a living person. Indeed also, as Kollek argues, “it would be extremely difficult…to assess which mechanical, chemical or genetic intervention into the human brain…would interfere with or alter the self of the human person,” suggesting that defining the localized functions of the self might not be possible. Given the strength of both of these arguments, for neocortical death, and for whole brain death, the decision to be made is clearly one of practical concern. Since it is impractical at the current time to define the death of the person as the loss of those traits that we agree to be salient to the person, we require using the whole brain definition. This seems to involve casuistry in the argument for this definition of death, however practical or necessary it may be.

Revisiting Virtue Theory

“This delusion [of personhood] is a kind of prison for us, restricting us to our personal desires and to affection for a few persons nearest us. Our task must be to free ourselves from this prison by widening our circles of compassion to embrace all living creatures and the whole of nature in its beauty.” – Albert Einstein

“Goodie-goodies are the thieves of virtue” – Lao Tzu

Another definition of the self might include that which is responsible for the survival of one’s consciousness. Since there are specific functions of one’s body that involved in this process, one may identify with those features. This is also a radical departure from a traditional view of the self: it is to say that I beat my own heart; it is self as the body as opposed in in the body. However, this too breaks down under analysis. For instance, are there really any boundaries to this self? If I breathe in the air around me, or if “I am what I eat,” as the expression goes, then the separation of the body from the environment is merely a statistical, probabilistic calculation (“…the criteria by which we reidentify plants, animals, and persons involve similarity, not exact sameness” – Flanagan paraphrasing Aristotle). The “no self” philosophical view is more radical than this: if there is to be any identification at all, then I am either nothing, or I am everything[3]. What effect would this have on our moral judgments? The cognitive movement of identification to encompass more of existence necessitates one to feel more deeply and broadly compassionate. In this way, the virtues of compassion and equanimity follow from right view in Buddhism (which includes this no self conception as wisdom; Flanagan). Anatman, as a sort of axiom to that philosophy, provides the rational basis for these virtues. What other insights might provide a basis for virtue? The fact that there is suffering in the world is another candidate. After wisdom has been reached regarding identity, then the suffering of the world becomes one’s own. Accepting anatman, although the suffering of others does not reach my consciousness directly, it is because I am identified with more than my consciousness and no less that the entirety of existence that I am inspired and compelled to act compassionately, in lovingkindness, towards all sentient life (since all sentient life does not want to suffer – H.H. The Dalai Lama). This is in line with Farah’s philosophical views, as already discussed in this paper. The practice in this case thus involves two aspects: perfecting right view (which would mean fully understanding anatman so as to achieve phronesis), as well as developing compassion (through meditation, etc.)

This moral foundation, to decrease suffering in the world, implicates the development of other virtues, too (a synthesis of utilitarianism and virtue theory ethics, perhaps) While distinguishing definitions of equanimity, Flanagan uses the idea that “my being more calm and serene might make me more pleasant to be around” in contrasting a western conception of equanimity to the Buddhist meaning: equal love. However, both meanings denote virtue in the context of relieving suffering from the world. All dispositions that improve the state of the world, then, are virtues that should be cultivated – a rather heavy statement to make. If we accept the anatman doctrine, it follows that developing such virtues would become one’s natural inclination, due to the arising compassion for that with which one identifies (all existence). This inclination can be contrasted to Paul Churchland’s view of virtues as a set of social skills that are socially adaptive, similar to the prototypical social behaviors observed in the culture: social norms, essentially (as in Towards a Cognitive Neurobiology of Moral Values). In terms of what we have discussed in class about virtue theory ethics, this seems to be exactly what the development of virtue for the achievement of eudaimonia is not. It is difficult to see how following social norms will encourage any kind of unique flourishing. What would Eudaimonia^Churchland entail, through the conformity to prototypical, socially adaptive behavior?

There is another argument for identity that could be proposed. Since it would seem that consciousness floats, as it were, as seats of perspective in a material existence, there is something to grasp onto for personal identity. I might identify with consciousness, a passive function of the brain though it may be. However, since consciousness, using a meaning in this case more closely resembling awareness, has no inherent content, there might be little reason to support this hypothesis over self as any other function the body. If we identify with existence more broadly however, our understanding of consciousness might broaden, too. Our understanding of consciousness might go from the limited individual awareness of sensory stimuli and other internal perceptions, to a global embodied experience of knowledge and feeling: an intersubjective phenomenon among all sentient bodies (Rose).

[1] Which brings to mind that salient question from Euthyphro: is a pious action pious because the gods love it (internal attitude), or do the gods love it because it is pious (external truth)?

[2] Even a truth such as this: the mass industrial production of paperback books leads to the destruction of the environment provides a basis for some unification (large scale unconscious action is destructive) to support moral convictions (I bought a Kindle, because it is the right action, based on right view to do so).

[3] I believe this is the difference between saying, “I think therefore I am,” versus “I think, therefore there is thinking.” In the first case, if there is thinking at all (if existence exists), I must identify with something, but if there is no boundary delineating self then I must be everything. In the second case, if existence does not imply self, then I am nothing, and existence just is.

Dark Parts by Perfume Genius

Graeme — Sat, 16 Jun 2012 09:52:49 +0000

This is a very emotive song.

HEART by Oberhofer

Graeme — Sat, 16 Jun 2012 09:50:37 +0000

Nice song, great melody.

What is thinking?

Graeme — Sat, 16 Jun 2012 09:37:14 +0000

Thinking Computers

“You insist that there is something a machine cannot do. If you will tell me precisely what it is that a machine cannot do, then I can always make a machine which will do just that!” – J. von Neumann

The journey of philosophy and cognitive psychology towards an understanding of thinking closely follows, for many important reasons, the quest for artificial intelligence. For much of cognitive psychology’s infancy, thinking, in humans, was viewed as closely analogous to the way in which a computer comes to produce output for a given symbolic input. That is to say, the behavior of the organism is produced by a calculation of sorts by the brain, a calculation inevitably performed after a mathematically describable function. Related to this is Church’s nonformal thesis that every computable function is recursively computable. Turing expanded upon Church’s thesis, by proposing that a machine can compute any mathematical function, as long as there is an effective procedure to obtain the rules of that function. It seemed to follow that the output of the human mind must be computable by some machine that could perform a similar enough function to the one operating in the mind, and that such a machine was realizable. The system expected to achieve this was the Universal Turing Machine, a system that takes symbols as input, computes a function, and yields an output. Inevitably, it was thought, the UTM would receive not only character strings and integers as inputs, but visual and auditory signals as well. Thus, research began to create computers that closely mimicked the responses of humans to given inputs; if we could achieve this, it was thought, we would know the function used by the brain, and we would therefore know exactly how thinking is performed. A behavioral test known as the Turing Test was created as the benchmark for such a function, the passing of which entailed getting humans to believe that the computer was, too, a human. Soon the line between output that was clearly produced by man, and that which was produced by machine would become blurred, at which point it surely would follow that some basic function of the human mind had been computed, and that A.I. had been realized. Whether responding to conversational input, or solving mathematical puzzles with proofs that exceeded Bertrand Russell’s own, these ostensibly cognitive activities performed by machines seemed to prove that Artificial Intelligence was gaining ground very quickly in achieving its goal. It is no wonder, then, as the field of Cognitive Psychology was coming into its own, that psychologists drew bidirectional analogies between A.I. and the human brain. The primary of these was the information-processing model of the human mind, possibly derived from the method of computation by serial computers at the time. However, the limits of the linear model of input to computation and then to output were soon exposed, producing astonishing dilemmas for those involved in the related fields. It became apparent that the Universal Turing Machine was unfit for many complex tasks that the brain seemed to perform with relative ease. For instance, visual systems in biological nervous systems induced behavioral output in milliseconds, while advanced computational algorithms in digital circuits, a million times faster than the biological systems, failed even to compare in performance (Churchland, Could a Machine Think? ). There seemed to be something about the nature of the brain, then, that separated A.I. from its goal. Two prominent philosophers proposed this idea, both around the same time, each stressing two different, yet important, perspectives. The first was Hubert Dreyfus, who argued that Artificial Intelligence systems lacked a grasp of the background context with which information should be processed. In this sense, the information-processing model, a foundational concept in Cognitive Psychology, was indeed lacking in its explanation of how information is integrated in the brain while thinking; surely processing was not achieved in the serial manner envisioned and implemented by A.I. researchers and engineers. Accessing all of the relevant data in such a way, it became clear, would take too long, even with the most efficient serial processing algorithms; a new approach was needed. The second well-publicized attack on A.I. came from John Searle, who argued that there must be certain fundamental aspects of biological brains, deeply embedded in its inherent formation, that were not yet understood by Psychologists, Neuroscientists, and A.I. theorists. One such aspect of biological brains, he argued, was the phenomenon of consciousness, and he created an elaborate thought experiment to illustrate what he thought was the absurdity of the A.I. research program’s attempt to create intelligence from the digital computer paradigm. In this experiment, Searle asks the reader to imagine a symbol-manipulating system (the nature of a Turing Machine) that could translate Chinese to English. He then asks the reader whether this system in fact “knows” English. In Searle’s view, it seems preposterous to answer in the affirmative, and therefore argues that symbol-manipulation alone does not provide a platform for conscious intelligence. The two arguments from these philosophers are similar in one important respect: they both call for a non-behavioral evaluation of intelligence; merely passing the Turing Test will not suffice for either of these perspectives of what intelligence entails. It is interesting to note that this occurred at a time when the Behaviorist approach was being replaced more and more by the Cognitive Psychological approach in the general field Psychology, and thus Cognitive Psychology was forced more and more into the deep-end, so to speak, of explaining human cognition. Psychology had to go beyond mere behavior, and had to do so independently of analogies from Computer Science. Neurobiology must have seemed like the best bet as to where to look.

It seems that the primary mistake of the early A.I. research program, vindicating both Searle and Dreyfus, was the crude distinction between hardware and software. Given the UTM, it seemed only reasonable that one could compute the function of the mind on a software basis only; since it was the function that mattered, the engineering details were only relevant to a point. However, the human brain is not a UTM, and does not operate in a serial manner. Instead, the mechanism of the brain is inherently parallel; millions of neurons fire together to form a sum of input from many different areas, rather than a single stream from one point to another like in the UTM (Churchland, Could a Machine Think?). While the UTM works via binary signaling in an ordered sequence (if a and not b, then c), the brain contains networks of neurons, each network containing millions of inputs, with each input expressing a different weight on the system (depending for example, as one might imagine, on the input’s dendritic diameter or it’s degree of myelination), which altogether sum up to a probability for that node of the network, say a nerve, to send a signal. If the sum of the weights goes beyond a certain threshold, the system will fire and create an effect on the environment, and the new state will be fed back into the system through its sensory mechanisms. The network structure of this system became known as a neural network, and computational neuroscientists were able to model various elements of the nervous system based on this framework (Spivey, Continuity of Mind ). Furthermore, the system is also clearly dynamical, with bidirectional pathways to and from the target populations of processing units – for instance, populations of neurons in the human nervous system. This allows for a modulating ability between sensing and processing the environment. Thinking, therefore, cannot be a serial manipulation of symbols, just as Searle argued that it is not, but rather a far more complex and continuous, dynamical and parallel interaction of millions of efferent and afferent processing units. This does not mean that brains are not functional, that they aren’t “computers” in some sense; brains are computers, but in a radically different manner than was at first thought (Churchland, Could a Machine Think?).

With regards to thinking, an intriguing idea is the continuous manner, or “flow” of thinking. In natural language, we may say something such as, “think about your favorite food,” or we may tell someone to “think before you speak.” Although it may not always be useful to attempt to understand reality through the analysis of language, these phrases do give us insight into a general, “folk” understanding of what thinking is. If we use the understanding that inputs, fed into a system of neural networks such as a brain, cause a massively parallel and dynamical pattern of events, it is clear that the process will be continuous. This is due to the previously mentioned claim that as the nervous system processes inputs through the various sensory channels, the state of the system begins to change, and that this change is then fed back into the loop as new input. We might call this recursive process the foundation of the idea of cognition, as the brain continuously transitions to new states over time. As in the earlier examples from natural language, what happens when this process is applied with the conscious aim of moving the brain towards a state that “represents,” in some sense, an object in the world? It was an assumption of early folk psychology (a shared conceptual framework used to explain the behavior of ourselves and others), and even early Psychology, that beliefs (true or false statements about some subject) and desires were stored as symbolic representations in the brain. Paul Churchland argued that these ideas, having fermented for decades at the very basis of early Cognitive Psychology, were radically false and would soon be replaced by something more accurate. The answers were expected to come out of the growing field of Computational Neuroscience. The position that Churchland supports is known as eliminative materialism. It is materialist because it rejects dualism, thus requiring the perspective in question either to reduce to a theory coherent with the rest of neurobiology, or to be eliminated entirely by some new theory. It is an eliminative position precisely because it argues that such linguaformal representations, as described by folk psychology, do not exist in the brain at all (Churchland, Folk Psychology). Therefore, the eliminative materialist position requires a theory to explain basic mental processes, without using the idea that symbolic representations are accessed and processed by logical rules in the brain.

Meaning and Context

“We are all living in the same environment, but each of us lives in a different world.” – Schopenhauer

The question soon arises, if symbolic representations are eliminated by a theory of continuously transitioning brain states, in what way is there meaning in the brain? In the old theory from folk psychology, cognitive theorists could rely on the idea of propositional attitudes to understand how beliefs created meaning by reference to objects in the world (Churchland, Folk Psychology). In the new view, however, with no discrete representations or attitudes in the brain, it may in fact be easier to develop a theory of meaning. Armed with the new perspective of the brain that entails parallel processing, Computational Neuroscientists have envisioned a system that can take multiple forms of input at once, allowing for a sense of context that may not have been achievable by the representational theory of the brain. Moreover, the continuous and recurrent nature of the new theory further allows for integration, as these populations continuously communicate with different networks in the brain, which then feed into the system as new input. By discarding the hardware/software distinction, the root of early A.I., the new view opens Cognitive Psychology to a better understanding of learning; an understanding in which the very structure of the brain changes over time. In Computational Neuroscience and A.I. theory, this is known as “training up the system,” in which connections are made between relevant populations of processing units, and the individual weights of those connections are strengthened or weakened, based on the outcomes of the training sets (Churchland, Could a Machine Think? ). In this sense, the resulting image is not of the brain as a storage space for, or processer of, information. Rather, we have in mind a flexible and rather robust, not to mention sensitive and dynamical, incredibly intricate system; one that never produces an output without incurring some form of learning. However, how does all of this add up to meaning? If I encounter some complex idea, for instance, if I read in my textbook the metaphor “love is a collaborative work of art,” how might I begin to understand this? In this example, each part of the metaphor is connected to various other networks in the system; some of them entailing metaphors themselves, but all of them linked somehow to more and more networks, each by different strengths. It is this association among networks that creates context and meaning, and it is easy to see how such a system will also create meaning that is very specific to the individual system. For instance, if the population of processing units, in this case neurons, corresponding to the idea of art has been trained to connect with networks pertaining to ideas like illusion, something to display, inherently trivial, then the metaphor will produce a profoundly different meaning to someone for whom art is connected with the networks that map to inherently valuable, meaningful expression of the self, gift to the world, unique perspective of reality. Meaning is thus based on the structure of the brain itself, rather than on a function computed by logical systems. Some A.I. researchers believe that the way to create machines that have meaning is simply to imitate such neural networks, using algorithms that rely on Bayesian probability to calculate the strength at which nodes should signal to each other in the network; presumably this can be simulated on a Universal Turing Machine.

Vector Coding

“When people think about spring, surely they are not confused as to whether they are thinking about a season or something that goes boing – and if one word can correspond to two thoughts, thoughts can’t be words” – Steven Pinker

The previous illustration of the new view of meaning from Computational Neuroscience described the way in which a network as a whole can be structured so as to create a sense of context. How does do the populations of processing units themselves “stand for” the concepts associated in such a network, however, without being symbolic representations, as in the folk psychological view? Some Neurophilosophers, including Spivey and Churchland, have argued that the units in such a network become activated in specific patterns of distribution, and therefore create a vector particular to that activity: an activation pattern (Churchland, Neurosemantics). Although the vector is in no way itself a visual mental representation of the object in question, it provides, in a neurologically operational sense, a mathematical representation of this object. Spivey argues, however, that these representations are not completely accurate. Rather, there is again a Bayesian probability that a particular vector refers to an external object, a probability that is conditional upon other events in, and attributes of, the network (Spivey, The Continuity of Mind). Given that certain populations of neurons are firing, it becomes more or less probable that the vector refers to a particular object. Given this, one could imagine experiments where researchers observe the human brain in an fMRI machine, and predict which populations of activated neurons create the vector that “refers to”, for some person, some external object. In this sense, it would seem that objects are mapped in the brain in a meaningful way, and therefore it is difficult to discount representationism completely; it seems rather that the theory has been thoroughly revised, rather than eliminated (Churchland, Neurosemantics). This revision has allowed Computational Neuroscientists to overcome, perhaps a large part of, Dreyfus’ argument about such a system not integrating background information. Although the chess champion Deep Blue does not know whether or not he has won a game, equipped with such a system of parallel neural networks, perhaps he could simultaneously integrate enough concepts such as to create the context of “winning”.

Of course there are still far larger concepts to grapple with during this discussion. For instance, how do vectors, activation patterns in the brain, create qualia? One analogy that makes sense to me is that of sound waves to sound. Sound waves need some kind of interpretation by a nervous system in order to create the experience of sound, and perhaps, too, the vector codes correlating to green need an interpretive function to create the conscious experience of greenness. If such a function lies at a fundamental level of neurobiological systems, this would seem to be along Searle’s line of argument. Despite such an obvious wanting of explanation for these phenomena, I believe that the arguments illustrated in this essay move the conversation further towards a much more scientifically stable, so to speak, theory of cognition.

No, I Dont Remember by Anna Ternheim

Graeme — Sat, 16 Jun 2012 07:54:14 +0000

Cool live performance

Go To Me by Jordan Klassen

Graeme — Sat, 16 Jun 2012 07:50:15 +0000

Cute little song