The computational approach to the mind is based upon a single idea; namely, “the multiple realizability of mental properties.” (Kim, p. 73) Multiple realizability is based upon the more general condition that mental events and mental states causally depend or supervene upon physical systems – this is the ‘physical realization principle.’ (ibid, p. 74) The physical realization principle requires that there be some connection between a mental property M and a physical or physiological property P such that when P arises or is present, then so is M. The further implication of the computational approach, based as it is upon the physical realization principle, is that mental events can arise through a wide variety of different material implementations, for ultimately it is not the particular details of P which matter in providing M, but rather it is the connection between P and M that is important for the occurrence of consciousness. What this means from the standpoint of not only cognitive science, but also the field of artificial intelligence, is that it could be quite conceivable and not able to be ruled out on a priori grounds that a machine made of silicon and animated with electricity could have mental states just like the ones humans enjoy. In other words, the computational approach implies that consciousness can be realized in a variety of different physical systems, and even that one day we might be able to build a computer or robot that would have inner states of consciousness or awareness, just like we do.

The neurobiological approach to consciousness, however, eschews the possibility that consciousness could be embodied in other kinds of material, and argues instead that there is something both unique and essential about the physiological organization of the brain that allows it to manifest consciousness. The neurobiological approach proceeds according to two particular caveats that apply to thinking about consciousness as primarily an information processing phenomenon. The first caveat is that ‘simulation is not the same as instantiation.’ (Clark, p. 22) For instance, in the popular video game ‘The Sims,’ the ‘player’ of the game is able to construct a small world that simulated people inhabit. These people partake of a variety of different interactions with each other, appear to sleep, to eat, and to even have goals and go to work. Nevertheless, it would be perverse to argue that such a simulation could count as an actual instantiation of a world. In playing the game even a little bit, it becomes quickly apparent that the little ‘Sims’ are just ‘going through the motions,’ and all appearance of their intentionality and goal-directed behaviour is just that. Behind the surface of the simulation, there is nothing—no inner life, no thoughts, and no consciousness. The second caveat leveled by proponents of the neurobiological account of consciousness is the observation that many of our emotions and feelings (perhaps even more central to consciousness than the qualities of intentionality, rationality, and problem-solving) depend on a wide variety of different hormones and chemicals produced by the body that contains the brain responsible for consciousness. (ibid, p. 23) In essence, this speaks against the computational idea of consciousness because it claims that there is more to consciousness than the meager computational abstraction of it suggests.

A dedicated computationalist, however, could argue that fundamentally, the actions of all of the various hormones and biochemicals coursing through ones body is ultimately informational in nature, and therefore if these features of a biological organism are salient in producing or sustaining consciousness, then more accurate models of the informational backbone of such chemical reactions is all that is required. Concerning the first caveat, a computationalist could argue that, at some point, a simulation becomes so real and so indistinguishable from what it is trying to simulate, that questions about whether the simulation is ‘really’ conscious become to a very large degree irrelevant. In response to these sorts of arguments, John Searle has made famous the ‘Chinese Room,’ a kind of thought experiment that demonstrates how the tenets of computationalism simply cannot be correct. Noble views this theory as an act to disprove the fundamentals and overall concept of artificial intelligence. (Noble, 2004) At the core, not only of Searle’s thought experiment, but also his broader critiques of computationalism, are two core objections. First, the physical realization principle described above whereby the multiple realizablity of mental states is implied would also seem to imply universal realizability, i.e. the same things that make a brain like a computer (its ability to do computations) are precisely the same things that make a “stomach, liver, heart, solar system, and the state of Kansas” also like digital computers. (Searle, p. 208) In other words, there is nothing in the principle of multiple realizability to tell us which systems are and which are not computational. Indeed, in some sense, argues Searle, every phenomenon in the world can be seen at some level as a digital computer, and while this may be useful in certain contexts, it would be specious for us to conclude from this that everything (let alone the brain) really IS a digital computer. This objection Searle raises against computationalism is, he claims, the “consequence of a much deeper point, namely that ‘syntax’ is not the name of a physical feature… on the contrary, [proponents of computationalism] talk of ‘syntactical engines’… as if such talk were like that of gasoline engines or diesel engines, as if it could be just a plain matter of fact that the brain or anything else is a syntactical engine.” (ibid, p. 209) While Searle thinks that the first objection can be overcome through a “tightening up [of] our definition of computation…” (ibid), it is the second objection (i.e., that syntax under computationalism is thought to be a property akin to a physical property) that is fatal to any computationalist program. As Searle states, “The multiple realizability of computationally equivalent processes in different physical media is not just a sign that the processes are abstract, but that they are not intrinsic to the system at all. They depend on an interpretation from the outside.” (ibid) And if the syntactical properties of a system depend on an interpretation from the outside, then while it may be useful for some purposes or others to characterize systems as being computational (and therefore syntactical), it by no means follows that they are, in reality, computational systems whose syntactical features can be replicated, and in so doing can also replicate the inner mental features one ascribes to such observer-dependent features.

Patricia Churchland is also committed to a neurobiological approach to the mind and consciousness. In her article “Theories of Brain Function,” Churchland describes a particularly promising theoretical candidate grounded in a neurobiological framework: tensor network theory. According to this theory, the core of mental functioning of the brain is found in the cerebellum, a structure of the brain that is in humans as complex and as large as the cerebrum. The cells of the cerebellum convert vector based inputs to outputs, and these various actions are amenable to treatment using an array separated by different elements. Central to the theory is the idea that the “connectivity of arrays of neurons is crucial to explaining how a given input yields a given output…” (Churchland, p. 416) Tensors are generalized mathematical functions that transform one vector into another, “irrespective of the differences in metric and dimension of the coordinate systems.” (ibid, p. 418) The challenge for a theory of mind is not only to address the ‘top-level’ features of mentality and consciousness (such as intentionality, problem-solving, and reasoning), but also to account for how the embodied mind is able to physically interact with its external world. Tensor theory uses the model of vectors and tensors applied to the connections of the cerebellum to account for both the minds information processing abilities and its ‘embodiedness’ as it interacts with the world around it.

In between the theoretical extremes of computational and neurobiological approaches to understanding the mind, there are also intermediate positions. One such intermediate position is connectionism, which continues to have faith in the multiple realizability of consciousness, but assumes that consciousness is able to display its computational properties because of the huge number of interconnections between the various neurons of the brain and nerves of the body. Accurately simulate these connections, so argues the connectionist, and one will have a better chance at emulating consciousness in such a system. Another approach, also intermediate between the two extremes noted above, is the symbol systems approach. The most effective example of the symbol systems approach is with regards to linguistics. Linguistics is described as a field of study geared toward the natural and scientific approach to language. In addition, it encompasses the ability to differentiate between both the structure and the meaning of a specific language (Fromkin, 2000). This example illustrates that this approach has the ability to manipulate physical patterns and combine them into structures which can then be manipulated to produce new expressions. Fodor and Pylyshyn discuss the attributes of these approaches, especially vis a vis their ability to account for four features of mental phenomena that straightforward computationalism or neurobiology cannot—the productivity, systematicity, compositionality, and inferential coherence of cognition. Productivity is the ability of the mind to generate novel and unexpected linguistic structures given a finite set of rules and ‘atoms’ (words). This aspect of mentation is closely tied to another—systematicity, or the idea that “the ability to produce/understand some sentences is intrinsically connected to the ability to produce/understand certain others.” (p. 120) Compositionality is closely related to systematicity; in fact, Fodor and Pylyshyn argue that both of these aspects of cognition should be viewed as two sides of the same coin. Compositionality is the idea that sentences containing similar elements will be semantically related: “Jerry hit the puck,” for example, is made of the same elements as “the puck hit Jerry,” and understanding one sentence implies understanding of the other. (p. 124) Finally, inferential coherence is the aspect of mentation that ‘piggybacks’ on systematicity and compositionality to be able to construct logical inferences based on already given facts or true sentences. Fodor and Pylyshin argue that connectionism cannot be true because it is unable to account for these basic features of consciousness. Their argument, however, tends to leave them not on the side of neurobiology, but instead on the side of computationalism and its requirement of internally structured representations.

Clark also looks into the connectionist paradigm of cognition. According to Clark, the primary virtue of connectionism is that it is more biologically realistic when compared to the symbol systems approach. It provides the ability to achieve many high level processing goals executed by using unique storage/retrieval methods. One key aspect of PDP is its content addressable memory which is the process of dynamically storing information about the attributes of a given object. This ability allows for the sharing of information about other objects, and might go some way to addressing Fodor and Pylyshin’s criticism of connectionist models as failing to account for compositionality and informational coherence. A connectionist network, according to Clark, is able to make generalizations through a process called default assignment. This is a way of temporally assigning a variable to an object so that it shares needed attributes. Additionally, a connectionist network mimics data storage in the brain through the use of distributed memory, and this could address the criticism Fodor and Pylyshin level against connectionism that it fails to account for the systematicity of thought and cognitive phenomenon.

Based on the descriptions of the various theoretical positions above, it should be clear that we are really not much closer to a comprehensive theory of consciousness than we were 100 years ago, although both computational and neurobiological avenues have borne much fruit. The computational approach to consciousness views it primarily as a symbol representing and manipulating system. This approach has led to a number of interesting breakthroughs in the field of computer science, including the creation of expert systems that can diagnose patients more efficiently than doctors, and chess playing programs that can beat human grandmasters regularly. However, there are some fundamental objections to the computational approach that make it unappealing in the long-term as a final and comprehensive theory of cognition. Perhaps the most significant objection is that while abstract algorithms implemented on computer hardware are able to simulate the appearance of intelligence well, there is a fundamental category difference between a simulation of intelligence and actual, embodied intelligence itself, which seems to be associated with consciousness and the interaction of a conscious being with a world. Churchland’s neurobiological approach attempts to address the shortcomings of computationalism through focusing on the role of the cerebellum in translating intentions into motor actions. In Churchland’s theory, the brain is an irreducible component of any theory of consciousness. Intermediate positions, such as connectionism, attempt to synthesize the insights of computationalism (i.e. cognition is the execution of high-level programs) with those of neurobiology (cognition requires a great deal of interconnections between neural cells). While Fodor and Pylyshin level computationally motivated objections towards connectionism, Clark is able to provide a plausible story for how a connectionist approach can address these objections. Fundamentally, what seems clear in the field of cognitive science is that consciousness depends on the brain, and the brain’s operations involve to at least some extent the representation and manipulation of symbols according to rules. However, whether this unique ability of the brain to perform these actions is in fact ‘multiply realizable,’ as computationalists maintain, is something that has yet to be proven.

Churchland, P.S. (1986). Neurophilosophy: Toward a unified science of the mind-brain. Computational models of cognition and perception. Cambridge, Mass: MIT Press.

Clark, A. (1989). Microcognition: Philosophy, cognitive science, and parallel distributed processing. Explorations in cognitive science, 6. Cambridge, Mass: MIT Press.

Clark, A. (2001). Mindware: An Introduction to the Philosophy of Cognitive Science. New York, Oxford: Oxford University Press.

Fodor, JA, & Pylyshyn, ZW. (1988). Connectionism and cognitive architecture: a critical analysis. Cognition. 28 (1-2), 1-2.

Fromkin, V. A. (2000). Answer key for linguistics An introduction to linguistic theory. Malden (Mass.): Blackwell.

Kim, J. (2005). Mind as a computer: Machine Functionalism. pp. 76-7; 80-96. Westview Press.

Noble, H. M. (2004). Artificial intelligence The Chinese room argument. Appin: Tartan Hen. http://www.tartanhen.co.uk/essays/chinese.htm.

Searle, J.R. (1992). The rediscovery of the mind. Representation and mind. Cambridge, Mass: MIT Press.

Thimerosal

The first claim I will address is that vaccines contain poisonous mercury in the form of thimerosal, that can cause severe brain damage, particularly in infants. First, it must be noted that we are not really talking about pure mercury. Rather, there are two types of mercury – ethylmercury(referred to from now on as EM), and methylmercury(referred to as MM). EMs are “organic mercury compounds in which the mercury is attached to an ethyl group”, and MMs are the same, but attached to a methyl group.  EMs and MMs have the chemical formulas C2H5Hg+ and CH3Hg+, respectively.[¹] To show why this is important, look at the formulas for water, H20, and hydrogen peroxide, H2o2. Both have the same elements, but in different amounts. So, we can see that ethylmercury and methylmercury will have different effects on the body, just as water and hydrogen peroxide do.

Why is this important? It shows that one just cannot say “mercury in vaccines is bad”. Any harmful effects that MMs have cannot be applied to EMs. Of course it is still possible at this point for EMs to be harmful. But is it? No. Let’s look at some numbers.

The half life of EM in the human body is less than a week, compare this to the half-life of MM, 1.5 months.[2] This means that within a week, half the mercury will no longer be in your body.

The lethal dose of thimerosal for 50% of the population (this study was done in rats) is 98 mg per kilogram.[3](thanks to RoaringAtheist for finding this!)

Each 0.5 mL dose of the H1N1 vaccine contains 24.5mcg of ethylmercury. That’s 0.0245 mg.[4]

What does this mean? It means that a lethal dose for 50% of the adult population is ~4,000 H1N1 vaccinations per kg. I weigh ~90 kg. So, for me to die from mercury poisoning, I would have to get 360,000 doses of the vaccine in less than a week.

Of course, none of this matters at all, because there is also a thimerosal-free version of the vaccine.

The vaccine makes you sick/Live virus

Here is another ridiculous claim I have often seen about the vaccine – it will in fact give you the very illness it is supposed to protect against! Of course this is absurd.

There are two types of the flu vaccine: Inactivated vaccine, and Live attenuated vaccine. The inactivated vaccine is also known as the “killed” vaccine, with good reason. The viruses in the vaccine are dead![5] The live attenuated vaccine, on the other hand, contains a version of the virus that is alive, although weakened to the point that it is not pathogenic. Such viruses will cause an immune response while not causing illness.[6]

It’s My Choice

So, it is now apparent that the vaccine is not dangerous, and that there is no harm in getting one. But even so, why should you bother? The obvious answer is that so you don’t get the flu. But there is a second reason – herd immunity. This is the resistance of a group to attack by disease to which a large proportion of the members are immune.[7] To put it simply, the higher the percentage of people in a community who have gotten the vaccine, the less vulnerable the community is to suffering a pandemic. Every individual who gets the vaccine slightly lowers the chances of a pandemic. By getting the vaccine, you slightly lower the odds of other people getting sick or even dying.

These are the main reasons for not getting the vaccine that I have seen. If you have any further objections, please explain and I will attempt to answer.

[1] http://www.reference.md/files/D005/mD005035.html

[2] http://www.who.int/vaccine_safety/topics/thiomersal/statement_jul2006/en/index.html

[3] http://infao5501.ag5.mpi-sb.mpg.de:8080/topx/archive?link=Wikipedia-Lip6-2/221998.xml&style#1.4.

[4] www.fda.gov/downloads/BiologicsBloodVaccines/…/UCM182401.pdf

[5] www.cdc.gov/vaccines/pubs/vis/downloads/vis-flu.pdf

[6] http://virology-online.com/general/typesofvaccines.htm

[7] http://medical-dictionary.thefreedictionary.com/herd+immunity

Over the years, I have observed many things about the creationist movement that seem to be recurring; recently I joined several atheist communities, and found that there too, the arguments for Creation where by and large the same, and the people involved using the same questionable sources to support much of what they stand for. I’d like to touch upon a few of the major ones I run into regularly.

Firstly, it seems that Creationism, though usually strongly opposed to the modern theory of evolution, is going through a bit of evolution of its very own. Creationism at large seems to be adopting various new types of evidence into itself, even if there is nobody who actually agrees with their interpretation, purely to try and keep the layman convinced that their version of history is correct. I will touch on this later, but many creationist leaders seem to be ignorant or deceitful, as they support creationism by building an elaborate mockery of that which they are trying to go against. In recent years, creationism has adopted various scientific theories to call its own, as well as reinterpreting evidence to support creationism where it previously didn’t. A clear example of this is the adoption of many creationists of the Big Bang theory. Most creationists, Young Earth and other alike, now claim that the ‘beginning’ of the universe is a clear-cut proof for the existence of a creator, since everything needs to have a cause, including the universe. Similarly, transitional fossils such as Tiktaalik (Fish to Tetrapod) and the recent Ida (Split between Lemurs and other primates) are ignored, or interpreted as clear evidence that they were fully formed species, and therefore not transitional. Furthermore, many finds in quantum physics and various other fields are twisted into an unrecognizable mess, to try and support a predetermined world-view.

This touches upon a second comment I’d like to make : ignorance. Many Creationists have a very poor grasp of the topic they are attacking, often conflating many different fields of science (including the Big Bang, Abiogenesis, Evolution, the formation of the Earth) under one header, so if any of these fields shows even one shortcoming, they can wipe it all off the table. Most creationists, especially Young Earth ones, tend to lack a total understanding of even the most basic of evolutionary theory, preferring to base their judgement on a layman’s grasp of a very simplistic version of evolution. For an example of this : many creationist seem to think that the theory of evolution states anything between dogs turning into cats in one generation, crocodiles and ducks having a ‘crocoduck’ transitional species, where this creature looks something like a chimera of different bodyparts, and let’s not forget the idea that the human species is ‘more evolved’ than other animals on this world. (Or in some cases, being classified outside the animals!)

Kent Hovind

Much of this is deceit, manipulating the public with made-up versions of the opposing theories, fictional evidence for your own theory (for lack of real evidence) and excessive mischaracterization of everyone involved. Kent Hovind is a clear example: in his own words, he claims to have been a science professor for decades, and yet he demonstrates he knows absolutely nothing about any scientific theory, recent or otherwise. In lectures, he extensively misrepresents everything he’s against (which is pretty much all of modern science) by blatantly lying and making things up. To support his own claims, Mr. Hovind uses a great amount of fictional data, often straying deeply into pure fantasy. Most of his theories (including his famous ‘ Ice Meteor’, known generally as the Hovind Theory) don’t even work in the realm of natural laws, and need divine assistance constantly, making them entire speculation. And all of this is delivered with a straight face, to an audience of people that are largely clueless on scientific issues, and will take this man’s word for it. Dishonesty to the utmost degree. And that’s one. I can name Ted Haggard, Ken Ham, Ray Comfort among many others as similarly inclined.

As said, I despise the ‘evolution’ of creationism, as a subtle attempt to worm creationism back into acceptable territory; let them come with their own predictions and tests, and fight the battle with evolution on even ground. I loathe the dishonesty and ignorance of people dealing with this issue: they are fully aware of what they are doing and deceiving other people, or they are so ignorant on the topic that they should not be claiming knowledge.

There are many other reasons why I dislike creationism, but most of those are generally towards one or the other subgroup. Arrogance is one, as well as appeals to numbers, loyalty, false promises and their regular claims of the negative nature of anything that doesn’t agree with them.