Analysis of Computation, Cognition, and AI: A Detailed Essay

This essay delves into several key concepts in artificial intelligence and cognitive science. It begins by differentiating between a thing and its computational simulation, referencing the Church-Turing thesis. It then explores Searle's Periscope, discussing its functionality and limitations in the context of understanding minds in computers and robots. The essay further examines the similarities and differences between computation and language, highlighting the importance of input and output in both. It also addresses the distinction between grounding and meaning, particularly in relation to T2 and T3 robots. Furthermore, the essay investigates whether studying the brain can explain cognition, emphasizing the role of cognitive psychologists and neuroimaging techniques. Finally, it discusses the symbol grounding problem in computationalism versus computation, noting the dependencies and complexities involved. The essay concludes by citing various works that support its arguments.

Name
Professor
Course
Date
According to the Strong/Church Turing Thesis, just about anything in the world can be
simulated computationally: What is the difference between a thing and its computational
simulation?
The Church/Strong Turing thesis is based on the argument that everything can be
imitated to get a new and similar feature through the use of a Turing machine. Its argument is
based on what makes a computational simulation mentioning that the computational simulation
itself is a manipulation of the symbols that can mean something when interpreted. This means
that the result of what is being simulated gives the computational simulation. Therefore, what is
being simulated means it is the thing. This is because it has natural or its own existence that does
not depend on simulation to exist. However, the meaning to the shape of the symbol is not
relevant in understanding the simulation.
Moreover, to understand the differences between a computation simulation and a thing, it
is essential first to simplify the more complex word then understand each word independently.
Here, we can make it easier by understanding what computation independently means and also
the term simulation. After that, we can then combine the two to and try to differentiate with the
term thing. According to Turing (Magyar Pszichologiai Szemle 37) the term computation means
the use of technological devices such as the computers to perform a task. On the other hand,
simulation refers to the technique of representing or imitating the real world through the use of

computerized programs (Cook et al. 181). Being able to understand the two terms, now the word
computational simulation refers to the use of technological devices in representing the real-world
situation through simulation. On the other hand, a thing refers to the attribute, object, or any
quality preferred to have its own existence. According to Harnad (Journal of Consciousness
Studies 71) the existence of things does not depend on a computer algorithm as it is the case in
computational simulation.
What is Searle's Periscope? On what does it work and on what does it not work, and why?
A Searle's Periscope is more concerned with the minds in which both the people and the
computer understands. It is a computationalism soft underbelly. For an instant, failing of the
Turing Test (TT) is not a guarantor of lacking mind or the passing is not a guarantor of having a
mind (Turing 31). Its argument is however based on the rights and wrongs about the Searches
Chinese Room Argument. It argues on the fatal flow in computationalism such that the
computational states have no difference to the mental states. According to Harnad (philosophical
and methodological issues in the quest for the thinking computer 240) the Artificial intelligence
also argues on the mind thinking of all the programs with cognitive states. In this point, it is,
therefore, true to say that any Chinese understanding computer program does not mean that it
really understands Chinese. According to Harnad (Essays on Searle's Chinese room argument
47) this is because, for example, a person like the Searle who did not understand the language
could also execute a similar program without the ability to understand the Chinese. Hence the
execution of the program by the computer does not mean that it understands the Chinese.
However, the functioning of the Searle's Periscope does not work for a T3 robot but
works for the T2 robots and the computational part. A T3 refers to the sensorimotor interaction
where things interact through manipulation, touching and seeing. The computers are however

unable to do that. T2, on the other hand, is a symbol in symbol out with an ability of computation
(symbol manipulation) between them. For the T2, the activities of manipulation are therefore
supported by the computer.
What are the essential similarities and differences between computation and language?
To be able to understand the similarities between the two, it is essential first to
understand the meaning of each term and what is composed of. According to the Church-Turing
Thesis, the term computation refers to the manner in which something can be manipulated to
have a clear meaning especially based on the shape of the original object or thing that has been
manipulated. This manipulation involves something like the simulation where a new product is
achieved upon manipulating the original item. Harnad (arXiv preprint arXiv:1712.05881 601) it
can also be said computation is what the mathematicians do as they try to solve and get a final
and new result solution from the original problem. This solution resembles the original problem.
It is however impossible when it comes to the manipulation of the functions that are non-
recursive.
On the other hand, language refers to the remarkable and unique abilities that allow us to
make either a true or false statement. Acording to Harnad (Kaziemierz Naturalized Epistemology
Workshop (KNEW), Kaziemierz 327), this means that the reliability of the outcome whether it is
true or false depends on the input. Therefore, one of the similarities between the computation and
language is that they both involve some input to get an output. The quality of the computational
output depends on the input similar to the language where the reliability of the output whether
true or false depends on the input. The difference between the two is that in computation,
manipulation can be done through simulation where Turing machines can be used while for the
language, the Turing machines can be omitted to get the false or the true statement.

What is the difference between grounding and meaning?
Grounding is more concerned with the techniques that are used in giving certain words
meaning or matching the meaning of a word to its referent. The grounding involves more than
the meaning, and it is the source for meaning. The main problem associated with the grounding
is how to get the meaning of the words or the symbols hence the problem of what meaning itself
really is. However, Harnad (Scholarpedia2.7 1033) states that according to the Chinese Room
Argument, the grounding has been used to refer to an intrinsic meaning as a result of semantic
interpretation. On the other hand, meaning refers to a combination of both the feelings and the
symbol grounding. It moreover refers to our ability in pointing or finding the referent.
In grounding, the is one of the vital requirements as it is used in avoiding some of the
semantic misunderstandings between any two people as they have to get a close enough
meaning. When it comes to T2 and T3 in grounding, T3 can ground and reply questions
correctly. However, when it comes to meaning, the same T3 is unable actually to have feelings
or understand. Moreover, T3 allows doing of all things in grounding, but when it comes to the
meaning, it has some limitations to the things it can do.
Can studying the brain explain cognition?
It is true to say that cognition can be explained through studying the brain. Harnad
(Computation at 70, cognition at 20" 251), states that cognition refers to the way human beings
think in which they understand and acquire knowledge through experience and senses. The
understanding of the cognition among human beings is enhanced through the study of how the
human brain think, remember and learn. The behavior of the mind is quite complicated as
different people think and understand differently and, therefore, to understand how it occurs, it is

vital to do some study research (Searle 421). Looking directly at how people do their daily task is
not enough to explain the full cognition, and therefore it requires the brain scientist also known
as the cognitive physiologist to study and provide clear information concerning the human brain
thinking and understanding.
The cognitive psychologist study how people store information in their brains, how they
perceive and process any information. Harnad (Computation, cognition, and Pylyshyn 245) states
that to make it easy to understand the brain cognition, the scientist uses the new technology
resources such as the Magnetic Resonance Imaging (MRI) which have been designed such that it
can capture the picture the brain at work (Harnad 245). This enables the scientist to see the how
the brain works thus helping them to understand how the brain reacts to a particular stimulus.
They are also able to use the picture in understanding how brain structure can affect a person's
cognitive, personality or health functioning.
Why does computationalism have a symbol grounding problem but computation does not?
When a comparison between the computationalism and the computation is made, it is
found that the computationalism involves more activities as compared to the computation as an
independent. Computationalism is more recognized as a strong Artificial Intelligence compared
to the computation as it applies a lot of intelligence. In this computationalism, the understanding
of how human brains thinks understands and stores information in computational. According to
Harnad (422) the implementation of the computation does not depend on other computations
hence it is independent. Also, the intelligence of the computer through the use of replies to the
questions put on computers to be unable to distinguish a machine from another human being is
decisive (Harnad 525). This means that the intelligence of the machine has the ability to make a
decision quickly and effective hence the importance of symbol grounding.

On the other hand, the computation lacks the symbol grounding due to a lot of
dependencies and less complex requirement compared to the computationalism. The Turin
machine is used in computation only for less task. In computation, the machine is limited to what
it can read as it only reads what is on its reader or the head. It is also tasked with writing on the
tape, erasing what is on such tape and finally stopping the work. This less and independent
functionality to the computation does not, therefore, allow the symbol grounding.

Works Cited
Cook, R., et al. "Mirror neurons: from origin to function." Behavioral and Brain Sciences 37.2,
2014: 177-192.
Harnad S., Zahra, Jack Felag, and Josh Bongard. "Morphology dictates a robot's ability to ground
crowd-proposed language." arXiv preprint arXiv:1712.05881, 2013.
---. "10 Cohabitation: Computation at Seventy, Cognition at Twenty." Computation, cognition,
and Pylyshyn, 2009: 245.
---. "Cohabitation: Computation at 70, cognition at 20", 2009: 245-257.
---. "Darwin, Skinner, Turing and the Mind. (Inaugural Address. Hungarian Academy of
Science.)." Magyar Pszichologiai Szemle, 2002: 521-528.
---. "From knowing how to knowing that: Acquiring categories by word of mouth." Kaziemierz
Naturalized Epistemology Workshop (KNEW), Kaziemierz, Poland. Vol. 7, 2007.
---. "Symbol grounding problem."Scholarpedia2.7, 2007: 2373.
---. "Can a machine be conscious? How?" Journal of Consciousness Studies 10.4-5, 2003: 69-75.
---. "The annotation game: On Turing (1950) on computing, machinery, and intelligence." The
Turing test sourcebook: philosophical and methodological issues in the quest for the
thinking computer. Kluwer, 2006.
---. "What's Wrong and Right About Searle's Chinese Room Argument?" Essays on Searle's
Chinese room argument. Oxford University Press, 2001.
Searle, J. R. "Minds, brains, and programs." Behavioral and brain sciences 3.3, 1980: 417-424.
Turing, Alan M. "Computing machinery and intelligence." Parsing the Turing Test. Springer,
Dordrecht, 2009. 23-65.