Introduction to Philosophy of AI

INTRODUCTION TO THE PHILOSOPHY
OF ARTIFICIAL INTELLIGENCE (AI)

HI AI
What is refers to humans’ intellectual
capability that allows us to think,
learn from different experiences,
understand complex concepts,
apply logic and reason,
AI is a branch of Data Science that
focuses on building smart machines
capable of performing a wide range
of tasks that usually require human
intelligence and cognition
Nature Human Intelligence aims to adapt
to new environments by utilizing
a combination of different
cognitive processes,
The human brain is analogous,
aims to build machines that can
mimic human behavior and perform
human-like actions. machines are
digital.
Functioning Humans use the brain’s
computing power, memory, and
ability to think,
AI-powered machines rely on data
and specific instructions fed into the
system
Learning
power
Human Intelligence is all about
learning from various incidents
and past experiences. It is about
learning from mistakes made via
trial and error approach
throughout one’s life.
Artificial Intelligence falls behind in
this respect – machines cannot think.
They can learn from data and through
continuous training, but they can
never achieve the thought process
unique to humans.

1.ARTIFICIAL INTELLIGENCE
• 1.1 Definition of AI
• According to Haugeland: artificial
intelligence is “the exciting new effort to
make computers think machines with
minds”
• literal sense For Bellman, it is “the
automation of activities that we associate
with human thinking, activities such as
decision-making problem solving, learning.”

• For Kurzweil: AI is the art of creating machines
that perform functions that require intelligence
when performed by people
• Luger and Stubblefield hold it to be the branch of
computer science that is concerned with the
automation of intelligent behaviour.
• Charniak and McDermett define Al as the study
of mental faculties through the use of
computational model.

What does AI Definition Mean:
• Hauge land and Bellman point out that
artificial intelligence is concerned with
thought process and reasoning
• They have explained the mind as a machine
that is completely associated with human
thinking.
• That is to say, computers do think.
• Schalkoff Luger and Stubblefield are
concerned with the behavioral aspects of
systems. For them, computers behave as
intelligently as human beings.

• Kurz Weil, Rich and Knight are concerned with
measuring success in terms of human
performance.
• artificial intelligence can be attributed to
machines, but it belongs basically to the human
mind.
• Chamak, McDermett, are concerned with an ideal
intelligence. They explain the mental faculties
through the use of computational models,

• to sum up, all the definitions of Al can be
organized into four categories They are as
follows
• Systems that think like humans.
• Systems that act like humans.
• Systems that think rationally.
• Systems that act rationally

1. Systems that think like humans
• It is called cognitive modelling approach
• We can understand first in humans in two ways
• One through Introspection: Examination of one’s
own mental and emotional process
• Second through Psychological Experiement: it is a
scientific procedure undertaken to test a
hypothesis or demonstrate a known fact.
• If the program input/output and timing behavior
match with corresponding human behavior then
we can call it as cognitive modelling

• In short: it is to observe both how human
mind works for the Problem and how
computer works for the same problem
• Eg: a pigeon solving how to eat banana which
is tied above with the help of moving a sponge
near to banana. The focus in the example is
the cognitive play in the mind of pigeon. i.e
the reasoning steps

Acting like Human
• How machine can act like Human
• There are 5 important elements in AI which can
help to act like human.
• They are
• NLP: Natural Language Processing
• The Problem Solving
• Machine Learning
• Computer Vision
• Robotics

Acting like Human - NLP
• It is an AI language. It will help the AI to
communicate with outside World.
• The most common way that people communicate
is by speaking or writing in one of the natural
languages like, Hindi, English, French or Chinese.
• These artificial languages are designed so that
sentences have a rigid format, or syntax, making it
easier for compilers to phrase the programs and
convert them into the proper sequences of
computer instructions. Languages of AI Video

• Artificial intelligence researchers hope that
learning how to build computers that can
communicate as people do would extend our
understanding of human language and mind.
• Thus, if the question were Rome the capital of
the simple reply No' would be appropriate but, it
is Paris,' Rome is the capital of would be more
complex.
• Machine programs would also be able to explain
the meaning of the word in other terms and
also to translate from one language to another.

Problem Solving
• The first big successes in artificial intelligence
were programs that could solve puzzles and
play games like chess
• Techniques like looking ahead several moves
and dividing difficult problems into easier
sub-problems evolved in the fundamental
artificial intelligence techniques of search
and problem reduction

• According to Avron Barr and Edward A.
Feigenbaum, human beings often solve problem by
finding way of thinking about it that makes the
solution easy.
• but so far, artificial intelligence programs must be
told how to think about the problems they solve.
• Elaine Rich defines problem solving: as that which
"chooses the best technique(s) and applies it
(them) to the particular Another view is that goal
and set of means of achieving the goal are called
problem solving

• According to Stuart Russell and Peter Norvig
problem consists of four parts: They are
1. The Initial state,
2. Set of Operators,
3. Goal Test Function, and
4. Path Cost Function
• search can be judged on the basis of
completeness, optimality, time complexity,
and space complexity

• The agent has to search which the minimum
path to reach the goal.
• To solve problem is the main task of the agent
in artificial intelligence.
• one of the important searches in artificial
intelligence is the technique of Heuristic search
• The word derived from the Greek verb meaning
find or to discover
• According to Newell, Shaw and Simon, "process
that may solve given problem, but offers no
guarantees of doing so called heuristic for that
problem

• For example, game playing is also form of
problem-solving Games have engaged the
intellectual faculties of the humans.
• According to Carpenter and Just, an intelligent
machine can follow all these rules and play
more efficiently than human beings.
• For example, in speed chess, computers have
defeated the world champion, Gary Kosparov,
in both five minutes and twenty-five minutes
games.

• We are mainly concerned with how artificial
intelligence programs solve different problems
within a few seconds

Difference between AI, ML, DL
• AI: Enable the artificial agent think. Eg: AI
application, like self driving car.
• ML : it is the subset of AI. It provides statistical data
or tools to understand the data.
• Three things are involved, supervised: labeled data,
unsupervised: unlabeled data, semi supervised:
some will be labelled and some will not be labelled.
• DL: subset of ML. Multi-neural network
architecture, to mimic the brain – ML – Video
• ANN: Artiticial neural network – input numbers
• CNN: Convolutional neural network – input Images
• RNN: Recurrent neural network – time series form

MACHINE LEARNING
• It is the ability to adopt to new circumstances.
For example it is the ability to maintain the
temperature in the industry.
• It should predict the environment temperature
and accordingly maintain the temperature in
the industry.
• According to Bonnet: the ability to learn is one
of the fundamental constituents of intelligence,
• Learning is understood as indicating the way in
which the humans and animals can increase
their stock of knowledge and improve their skill
and reasoning powers.

• There are two fundamentals reasons for
studying learning.
• One is to understand the process itself:
Philosophers since Plato have also been
interested in the process of learning,
• Aim: it might help them understand and
know what knowledge is and how it grows.
• The second reason for research is to provide
computers with the ability to learn.

• the work in machine is important for expert
systems development, problem solving computer
vision, speech understating, conceptual analysis of
databases, and intelligent authoring in this way, a
computer can do more work than human beings.
• According to James R. Slagle, computers can do
arithmetic at an able speed, and no human can
compete with them. Besides, computers can do
many other odd jobs like detecting a certain
disease from the available data.

• Al as a study of machine intelligence,
especially of computers and robots, opens up
new vistas of understanding mind and
Intelligence.
• Intelligent behaviour can be studied in many
dimensions. The computers can do many
things that seem to require intelligence and
other mental abilities

Computer Vision
• Vision: It is the ability to perceive an object. It
is called image processing
• For example if you show an apple. It must be
able to recognize it as an apple and not as an
orange.
• machine vision means the vision of a machine
that can see or perceive the things in the
world.
• vision first and foremost, an information-
processing task.

• there is a distinction between human vision
and machine vision,
• human vision is defined as eye is just a sensor,
the visual cortex of the human brain is our
primary organ of vision.
• Eg: the table and the image of the table.
• Visual neuroscience develops the methods of
understanding how human visual systems
work.
• Visual neuroscience is beginning to on the
mechanisms that allow the cortex adapt its
circuitry and learn new task.

• Machine vision as part of the Al programme,
however, to develop systems that can
simulate human vision.

Tasks of Computer Vision
• OCR − In the domain of computers, Optical
Character Reader, a software to convert scanned
documents into editable text, which
accompanies a scanner.
• Face Detection − Many state-of-the-art cameras
come with this feature, which enables to read
the face and take the picture of that perfect
expression. It is used to let a user access the
software on correct match.

Tasks of Computer Vision
• Object Recognition − They are installed in
supermarkets, cameras, high-end cars such as
BMW, GM, and Volvo.
• Estimating Position − It is estimating position of
an object with respect to camera as in position
of tumor in human’s body.

ROBOTICS
• What is Robotics?
• Robotics is a branch of AI, which is composed of
Electrical Engineering, Mechanical Engineering,
and Computer Science for designing,
construction, and application of robots.
• Robots are aimed at manipulating the objects by
perceiving, picking, moving, modifying the
physical properties of object, destroying it,
• freeing manpower from doing repetitive
functions without getting bored, distracted, or
exhausted.

Aspects of Robotics
• The robots have mechanical construction, form,
or shape designed to accomplish a particular
task.
• They have electrical components which power
and control the machinery.
• They contain some level of computer
program that determines what, when and how a
robot does something.

Components of a Robot:
• Robots are constructed with the following −
• Power Supply − The robots are powered by
batteries, solar power, hydraulic, or pneumatic
power sources.
• Actuators − They convert energy into movement.
• Electric motors (AC/DC) − They are required for
rotational movement.
• Pneumatic Air Muscles − They contract almost
40% when air is sucked in them.

• Muscle Wires − They contract by 5% when
electric current is passed through them.
• Piezo Motors and Ultrasonic Motors − Best
for industrial robots.
• Sensors − They provide knowledge of real
time information on the task environment.
Robots are equipped with vision sensors to
compute the depth in the environment. A
tactile sensor imitates the mechanical
properties of touch receptors of human
fingertips.

Applications of Robotics
• The robotics has been instrumental in the various
domains such as −
• Industries − Robots are used for handling
material, cutting, welding, color coating, drilling,
polishing, etc.
• Military − Autonomous robots can reach
inaccessible and hazardous zones during war. A
robot named Daksh, developed by Defense
Research and Development Organization (DRDO),
is in function to destroy life-threatening objects
safely.

• Medicine − The robots are capable of carrying
out hundreds of clinical tests simultaneously,
rehabilitating permanently disabled people,
and performing complex surgeries such as
brain tumors.
• Exploration − The robot rock climbers used for
space exploration, underwater drones used
for ocean exploration are to name a few.
• Entertainment − Disney’s engineers have
created hundreds of robots for movie making.

3. Thinking Rationally
• For AI it is about thinking rightly
• We can say that it is right when the thinking falls
under the laws of thought approach.
• Aristotle is one of the first Greek Philosophers
who started to use the term right thinking
• The laws of thought traditionally recognized are.
• The Law of Identity, The law of Contradiction, the
Law of Excluded Middle

• The law of Identity asserts that if any statement is
true, then it is true. This law asserts that every
statement of the form P =P is true, and that every
such statement is a tautology
• The law of Contradiction asserts that no
statement can be both true and false.
• The law of Excluded Middle asses that any
statement is either true or false.

• In the Laws of Thought' approach to artificial
intelligence, the whole emphasis is on correct
syllogistic inferences.
• Eg: all men have brains,
• all humans have brains,
• all humans are men
• In this inference, the conclusion is based on
the premises according to the rules of
inference

• In an inference, a set of variables, a set of
constant terms, a set of functions, the set of
connectives if, and, or, and, not, the quantifiers
'exist' and 'for all' are the most important
symbols to build an Al program.
• All these constants and variables are the arbitrary
representations of the world.
• With the help of these symbols, the so-called
logistic tradition within, artificial intelligence
hopes to build on such programs to create
intelligent systems.

• Two obstacles in this process of Giving rational
ability to AI
• The first is the need of 100% knowledge
• The second is : it requires too many
computations.

4 Acting Rationally
• Let us clarify the term agent
• An agent is the one who speaks on behalf of the
two parties. A middle person who becomes a
channel for any transactions. Eg: a marriage
setter, one who helps in getting License.
• AI Agent: it is an agent which able to perceive its
environment through sensor and acts upon that
environment through effectors.
• Eg: we build AI to maintain the temperature of a
room. It should have temp sensor, if the room
temp is more, it should take action.

• The job of artificial intelligence is to design the agent
program, which is a function that implements the
agent mapping from percepts to action.
• The agent is an autonomous to the extent that its
behaviour is determined by its own experience.
• artificial intelligence is viewed as the study and
construction of a rational agent.
• There are also ways of acting rationally that cannot
reasonably be said to involve inference. For example,
pulling one's hand off hot stone is a reflex action that
is more successful than slower action taken after
careful deliberation

Agents and sensors
• Human Agent: human being has sensory
Organs like eyes, ears, skin, skin. Effectors like
hands, mouth, legs
• A Robotic agent: Cameras, infrared ranged
finders as sensors, motors, actuators for
effectors
• Software agent: Keystroke, file content,
received network as sensors. Displays on the
screen, sent network packets, as actuators.

Strong AI and Weak AI
• Strong AI argues that it is possible that one day a
computer will be invented which can function
like a mind in the fullest same of the word
• it can think, reason, imagine, etc., and do all the
things that we currently associate with the
human minds.
• On the other hand, weak Al argues that
computers can only stimulate human mind and
are not actually conscious in the same way as
human minds are.

• According to weak Al, computers having
artificial intelligence are very powerful
instruments in the hands of man.
• Whereas Strong Al holds that computer is not
merely an instrument in the study of the
mind, but that the appropriately programmed
computer is really a mind.
• computer can think and do reasoning like the
human beings
• In Strong AI, the programmed computer has
cognitive states,

• the program are not simple tools that allow us
to test psychological explanations; rather the
programs are themselves the explanations.
• The main aim of Al is to reproduce mentality
in computational machines,
• to try to prove that the functions of a
machine are similar to the functions of the
human mind.
• Could a machine have mental states for Al?

Super AI
• But if strong AI already mimics human
intelligence and ability, what’s left for the last of
the types of AI?
• Super AI is AI that surpasses human intelligence
and ability. It’s also known as artificial
superintelligence (ASI) or superintelligence. It’s
the best at everything — maths, science,
medicine, hobbies, you name it. Even the
brightest human minds cannot come close to
the abilities of super AI.

• in the words of Searle, "there is nothing
essentially biological about the human mind.
• The brain just happens to be one of an
indefinitely large number of different kinds of
hardware computers that could sustain the
programs, which make up human intelligence
• any physical system whatever that had the right
program with the right inputs and outputs
would have a mind in exactly the same sense
that you and I have minds. Searle here is critical
of the view

• the cognitive scientists believe that perhaps
they can design the appropriate hardware
and programs - artificial brains, and minds
that are comparable to human brains and
minds.
• Strong artificial intelligence is a reductionist
theory. Because strong Al reduces mind or
mentality to physical properties.

Chapter 2
Limits of AI
• The critics of AI show the limits of artificial
intelligence
• The computer scientists working for artificial
intelligence design the appropriate hardware and
programs, which simulate the human mind for
them, mind is the software and the brain is the
hardware in which the mind works.
• These machines do not purport to replace
human mind but simulate it by various methods
of cognitive modeling

• The artificially designed computing machines
constitute the bulk of the field as cognitive
science called artificial intelligence (AI).
• This chapter contains a critical evaluation of
the arguments against AI put forward by
Gödel, Searle, Putnam, Penrose, and Dreyfus

2.1 What are the Limits of AI?
• The above criticism of machines shows two
kinds of mistakes that the machines can
commit.
• We may call them errors of functioning' and
'errors of conclusion
• Errors of functioning are due to some
mechanical or electrical faults, which cause
the machine to behave otherwise than it is
designed to do.

• In philosophical discussions, one likes to ignore
the possibility of such errors, because we are
discussing abstract machines.
• These abstract machines are mathematical
fictions rather than physical objects by definition
they are incapable of errors of functioning.
• In this sense, we can say that, machines can
never make mistakes.
• However, the machines can commit errors of
conclusion because they can make mistaken
moves in this function
• These mistakes are the errors of argument.

Turing Test
• Definition:
• Turing test is a test performed to determine a
machine’s ability to exhibit intelligent behavior.
• The basic concept behind the test is that if a
human judge is engaged in a natural language
conversation with a computer where he cannot
reliably distinguish machine from human, the
machine passes the test.
• Responses from both participants in the
conversation are received in the form of a text-
only channel. This test was introduced by Alan
Turing in 1950.

Godel’s Argument
• Godel's theorem states that in any consistent
system, which is strong enough to produce simple
arithmetic there are formulas which cannot be
proved-in-the-system, but which we can see to be
true.
• The whole effort of Godel's theorem is to show that
all formal systems which are consistent, adequate
for simple arithmetic, contain the natural
numbers.

• The operations of addition and multiplication,
and that they are incomplete, contain
unprovable, though perfectly meaningful,
formulae, which we can see to be true,
standing outside the system.
• When we consider the mind on the model of
Cybernetic we have a similar model in view.
• If human mind is such model, mind is
determined by the way it is made.
• Then, there is no possibility of its acting on its
own, as it governed by certain rules of
constructions and certain input of
information.

• But this is not the characteristic of mind as mind
does not act under ready-made rules.
• In fact, it is easy to produce mechanical models
which will in many respects produce truth of
arithmetic far better than what the human beings
can do,
• but for every machine there is a truth which it
cannot prove, but which can be proved by the
mind.
• This is not to say that we cannot build a machine
to emulate any desired piece of mind like
behavior

• it’s only that we cannot build a machine to
simulate every piece of mind like behavior
• We can (or shall be able to one day) build
machines capable of reproducing bits of
mind-like behavior
• and indeed of outdoing the performances of
human minds but however good the machine
is, and however much better it can do in
nearly all respects than a human mind can it
always has this one weakness, this one thing
which it cannot do, where as a mind can."

• Therefore, Godel's argument shows that the
mechanical model of mind, because of its
inherent limitations cannot stimulate the
functions of the mind which are infinite and
indefinite
• Further, it shows that machines are finitely
closed and hence cannot be compared with
human minds.

• 2.3 Searle’s Argument
• Searle's main intention is to criticize and
overcome the dominant traditions in the study
of minds, both 'materialist' and 'dualist’
• For him, consciousness is central to the mental
phenomena We think of ourselves as conscious
mindful, rational agents in the world, but
science tells us that the world consists entirely
of mindless physical particles
• But, the question is: How can we match these
two conceptions

• According to Searle, can be the case that the
world contains nothing but unconscious physical
particles, and yet that it also contains
consciousness?
• Can an essentially meaningless world contain
meaning
• Searle writes, "I believe that the mind body
problem has a rather simple solution, one that is
consistent both with what we know always
neurophysiology and without commonsense
conception of the nature of mental states pains,
beliefs, desires and so on

• But before presenting that solution, I want to ask
why the mind body problem seems to tractable.
• Why do we still have in philosophy and
psychology, after all these centuries, a 'mind
body problem in a way that we do not have
• say, a digestion stomach problem? Why does the
mind seem more mysterious than other biological
phenomena?
• Moreover, for Searle, all the above problems spill
over into other contemporary materialistic
interpretations of the issues of mind.

• Materialism asks the question: How should we
interpret the recent work in computer science
and artificial intelligence aimed at making
intelligent machines?
• More particularly, does the digital computer
give us the right picture of the human mind?
• Thus, the central issue is What is the relation
between the ordinary, common sense
explanations of people's behavior and its
scientific modes of explanation

• Searle seeks to answer this question in his attack
on materialism in his philosophy of mind
• He offers a biological explanation of mind
according to which mind is a biological offshoot of
the brain.
• In order to distinguish this view from others in the
field, Searle calls it biological naturalism.
• He says that Mental events and processes are as
much part of our biological natural history as
digestion, mitosis, meiosis, or enzyme secretion,

• The biological naturalism raises many questions of
its own. But one of the fundamental questions is:
• What about the great variety of our mental life-
pains, desires, tickles, thoughts. visual
experiences, beliefs, tastes, smell, anxiety, fear,
love, hate, depression and elation?
• Again, some of the philosophical questions, which
were raised by Searle, are:
• What exactly is consciousness and how exactly do
conscious mental phenomena relate to the
unconscious?

• What are the special features of the 'mental',
phenomena such as consciousness, intentionality,
subjectivity, and mental causation?
• And how exactly do they function? What are the
causal relations between mental phenomena and
physical phenomena?
• And can we characterize those causal relations in a
way that avoids epiphenomenalism?

Epiphenomenalism
• is a position on the mind–body problem which
holds that physical and biochemical events
within the human body (sense organs, neural
impulses, and muscle contractions, for example)
are causal with respect to mental events
(thought, consciousness, and cognition).
• According to this view, subjective mental events
are completely dependent for their existence on
corresponding physical and biochemical events
within the human body yet themselves have no
causal efficacy on physical events.

• The appearance that subjective mental states
(such as intentions) influence physical events
is merely an illusion.
• For instance, fear seems to make the heart
beat faster, but according to
epiphenomenalism the biochemical secretions
of the brain and nervous system (such
as adrenaline)—not the experience of fear—is
what raises the heartbe

• Searle's biological naturalism provides an
effective counter argument to the currently
fashionable computational theory of mind
according to which, the mind is a computer
program.
• According to this theory, the mind is to the brain
what the program is to the hardware. In short,
minds are computer programs implemented in
brains.
• In Searle's words "The brain is just a digital
computer and the mind is just a computer
program

• One could summarize this.View-I call it strong
artificial intelligence or 'strong Al. by saying that
the mind is to the brain, the program is to the
computer hardware.
• The supporters of AI argue that we can feed the
understanding of Chinese into a robot
• If the robot operates the Chinese symbols
property, would that not be enough to guarantee
that it understands Chinese?
• Searle replies that the robot lacks understanding

• Even though it might behave exactly as if it
understands Chinese, it would still have no
way of getting from the syntax to the
semantics of Chinese.
• Thus, there is no way that the supporter of
strong A can argue that the mind consists of
purely formal or syntactic operation and the
mind is nothing but a computing machine.
• Searle argues that the mental quality of
understanding cannot be just a computational
matter.

• It is because the computer is unable to
duplicate human intelligence, though it has
the ability to simulate the latter.
• Here, the key distinction is between du
plication and simulation, and no simulation by
itself ever constitutes duplication.
• At the end of the argument, he says, "for any
artefact that we might build which had mental
states equivalent to human mental states.
• the implementation of a computer program
would not by itself be sufficient.

• Rather the artefact would have to have
powers equivalent to the power of the human
brain.
• Searle offers two different sets of criteria for
applying the expression 'intelligent behavior.'
• One of these sets consists of third person or
objective criteria that are not necessarily of
any subjective psychological interest whatever
so ever.
• But the other set of criteria are essentially
subjective and involve the first-person points
of view

• According to him, 'intelligent behaviour' on the
second set of criteria involves thinking, and
thinking is essentially a subjective mental
process.
• Now, if we adopt exclusively the third-person
criteria to intelligent-behavior, then computers,
such as not to mention pocket calculators, cars,
thermostats, and indeed just everything in the
world, engage in intelligent behavior.
• But this yields no specific result regarding
intelligent behavior of machines.

Definition of Syntax
• The Syntax of a programming language is used to
signify the structure of programs without
considering their meaning. It basically
emphasizes the structure, layout of a program
with their appearance.
• The tools evolved for the specification of the
syntax of the programming languages are regular,
context-free and attribute grammars.
• The Grammars generally are the rewriting rules
whose purpose is to recognize and generate the
programs.

• The grammar contains a finite set of grammatical
categories (such as noun phrase, verb phrase,
article, noun, etc), solitary words (elements of the
alphabets) and the well-formed rules to specify
the order within which components of the
grammatical categories should appear.
• Syntax analysis is a task performed by a compiler
which examines whether the program has a
proper associated derivation tree or not.

• The syntax of a programming language can be
interpreted using the following formal and
informal techniques:
• Lexical syntax for defining the rules for basic
symbols involving identifiers, literals,
punctuators and operators.
• Concrete syntax specifies the real
representation of the programs with the help
of lexical symbols like its alphabet.
• Abstract syntax conveys only the vital
program information.

• Types of grammars
• Context-free grammar is prevalently used to
figure out the whole language structure.
• Regular expressions describe the lexical units
(tokens) of a programming language.
• Attribute grammars specify the context-
sensitive part of the language.

Definition of Semantics
• Semantics term in a programming language is
used to figure out the relationship among the
syntax and the model of computation.
• It emphasizes the interpretation of a program
so that the programmer could understand it in
an easy way or predict the outcome of program
execution
• The programming language semantics can be
described by the various techniques – Algebraic
semantics, Axiomatic semantics, Operational
semantics, Denotational semantics, and
Translation semantics.

• Algebraic semantics interprets the program by
defining an algebra.
• Axiomatic semantics determine the meaning of a
program by building assertions about an association
that detain at each point in the execution of the
program (i.e. implicitly).
• Operational semantics compares the languages to
the abstract machine, and the program is then
evaluated as a sequence of the state transitions.
• Denotational semantics expresses the meaning of
the program in the form of a set of functions
operating on the program state.
• Translational semantics focuses on the methods
used for translating a program into another
language.

Differences Between Syntax and Semantics
• Syntax refers to the structure of a program written
in a programming language. On the other hand,
semantics describes the relationship between the
sense of the program and the computational
model.
• Syntactic errors are handled at the compile time.
As against, semantic errors are difficult to find and
encounters at the runtime.
• For example, in c++ a variable “s” is declared as
“int s;”, to initialize it we must use an integer
value. Instead of using integer we have initialized it
with “Seven”. This declaration and initialization is
syntactically correct but semantically incorrect
because “Seven” does not represent integer form.

Putnam’s Argument
• We can discuss Putnam's views as belonging to
early Putnam and later Putnam.
• Early Putnam argued for the possibility of
robotic consciousness.
• As a functionalist, early Putnam shows that a
human being is an automation that is, the
human mind is a computing machine.
• In short, may be defined as the theory that
explains mental phenomena in terms of the
external input and the observable output.

• It explains the mind as complicated machine.
Now the question arises:
• Does a computing machine have intelligence,
consciousness, and so on, in the way that human
beings do?
• According to Putnam, since mind is a Turing
machine, the whole human body is a physical
system obeying the laws of Newtonian physics.
• The universe as a whole is a machine too. The
Putnam's argument shows that the whole human
body to at least metaphorically a machine.

• Putnam has taken the robot to be a 'psychological
isomorphic to a human being."
• the epistemological, metaphysical, and moral
arguments show that there is no isomorphic
relationship between humans and robots.
• If machines were conscious, they would have
feelings, thoughts, attitudes, etc.
• The theory that proposes to provide a complete
description of our psychological states as a Turing
machine Is a utopian project

• Putnam realized this later because this sort of
utopianism is an illustration of what is called
scientism
• It is based on speculations regarding scientific
possibilities.

• The later Putnam, however, has found that his
earlier thesis was wrong as mind can never be
reduced to a machine.
• While arguing against Al, the later Putnam
points out that pessimism about the success
of Al in sımulating human intelligence
amounts to pessimism about the possibility of
describing the functions of the brain.

• Moreover, the later Putnam mentions that
functionalism is in compatible with our
semantic externalism because the mechanistic
view of the mind does not square with
meaning and representation developed within
a semantic theory.
• The semantic theory possesses an externalist
relation between meaning and the external
world
• Putnam takes meaning, not as a mental or
psychological content, but as a content
conditioned by the external world.

• Putnam has rejected the computational view
of mind on the ground that the literal Turing
machine would not give a representation of
the psychology of human beings and animals.
• For him, functionalism is wrong in holding the
thesis that propositional attitude is just a
computational state of the brain
• For example, to believe that there is a cat on
the mat, is not the same thing as that there is
one physical state or a computational state
believing that there is a cat on the mat

• Therefore, it is not right to hold that
propositional attitudes are semantically or
conceptually reducible to computational
predicates.

Dreyfus’s Argument
• In What Computers Canons Do, Dreyfus
argues that research in artificial intelligence is
based upon mistaken assumptions,
• which included psychological, epistemological,
biological, and ontological assumptions about
the nature of human knowledge and
understanding
• We will see now what these assumptions are

• The psychological assumption is that the mind
can be viewed as a device operating on bits of
the mind according to formal rules.
• Thus in psychology, the computer as a model
of the mind is conceived by the cognitive
scientists.
• The epistemological assumption is that all
knowledge can be formalized in terms of
logical relations, and more exactly in terms of
Boolean functions
• , i.e., the logical calculus which governs the
way the bits are related according to rules

• A biological assumption is that the brain has
neurons, which operates so as to process
information in the brain according to a neural
network.
• The ontological assumption is that the
computer model of mind presupposes that all
relevant information about the world,
• everything essential to the production of
intelligent behavior, must in principle be
analyzable as a set of situation-free
determinate elements.

• The psychological, epistemological, biological,
and ontological assumptions have this in
common
• they assume that man must be a device which
calculates according to rules on data that take
the form of atomic facts.
• Dreyfus argues that all these assumptions can be
criticized on philosophical ground
• Each of the assumptions leads to conceptual
difficulties

• The assumption that machines can do everything
that human beings can do is definitely false as the
human capacity exceeds that of the machine.
• All the above-mentioned assumptions are
definite because they assume more than they can
prove.
• The idea that the human mind functions like a
digital computer is, according to Dreyfus,
inadequate and misleading.
• any complete description of behavior you should
be adequate to serve as a set of instructions,

• , it should have the characteristics of a plan that
could guide the action described.
• But, as Dreyfus argues, what instructions could
one give a person about to undertake the action
• Perhaps some very general rules such as listen to
the instructions', 'look toward an object', make
your selection', etc
• It is not clear why or how a complete de
deception in psychology should take the form of a
set of instructions.

• Again, Al scientists say that human bodies are part
of the physical world and objects in the physical
world have been shown to obey law which can be
expressed in formalism manipulate on a digital
computer.
• To be more particular, if the nervous system obeys
the laws of physics and chemistry, and then it is
bound to be a part of the physical world.
• Accepting the fundamental assumption that the
nervous system is a part of the physical world

• all physical processes can be described in a
mathematical formalism which can in turn be
manipulated by a digital computer,
• one can arrive at the Strong claim that the
behavior which results from human
'information processing, whether directly
formalize or not, can always be indirectly
reproduced on a digital machine.
• Against the above view, Dreyfus argues that
every form of information processing cannot
in principle be simulated by a digital computer

• Therefore, the strong claim that every form of
information processing can be imitated by a
digital computer is misleading.
• Arguing against the epistemological hypothesis
• Dreyfus says, "is there reason to suppose that
there can be a formal theory of what linguists call
pragmatics?
• There are two reasons to believe that such a
generalization of syntactic theory is impossible

• (1) An argument of principle, for there to be a
formal theory of pragmatics, one would have to
have a theory of all human knowledge, but this
may well be impossible.
• (2) A descriptive objection not all-linguistic
behavior is rule-like. We recognize some linguistic
expression as odd-as breaking the rules and yet
we are able to understand them."
• Eg:, the idea is in the pen' is clear in a situation in
which we are discussing promising authors. But in
fact, an idea cannot be in the pen, because
obviously an idea is not a physical object.

Penrose Argument:
• His suggestion is that un conscious actions of the
brain are ones that proceed according to
algorithmic rules
• whereas the conscious acts of the minds are non-
algorithmic
• Penrose discusses this nature of consciousness
and computation, and provides an answer to the
question
• whether our conscious awareness of happiness,
pain, love, aesthetic sensibility, will,
understanding, etc. can fit into a computational
model of mind His argument consists in the
following proposition

• (a) All thinking is computation, that is all
cognitive acts can be mathematically computed.
• (b) Physical actions of the brain can be simulated
computation ally, but this computational
simulation itself cannot evoke awareness.
• (c) Awareness cannot be explained by physical,
computational or any other scientific terms.
• Awareness, understanding, consciousness,
intelligence, perceptions, etc are all our
intuitively given mental activities.

• These cannot be computationally explained.
• Thus, according to him, 'intelligence' requires
understanding and understanding te quires
awareness‘
• Awareness is a basic feature of consciousness
• These mental activities are basic to the human
mind
• a person's awareness is to be taken, in effect, as a
piece of software,
• his particular manifestation as a material human
being is to be taken as the operation of this
software by the hardware of his brain and body.

• However, human awareness and understanding
are not the result of computations undertaken by
the brain
• Understanding is the inborn activity of the
human mind which cannot be simulated by a
computer
• Human understanding cannot be replaced by
computer simulations.
• The strong AI, much against our ordinary
understanding of the mental activities, tries to
reduce them to computational functions.

• In the words of Penrose: "Thus, according to
strong AI, the difference between the
essential functioning of a human brain
including all its conscious manifestations)
• that of a thermostat lies only in this much
greater complication (or perhaps higher-order
structure' or 'self-referential properties, or
some other attribute that one might assign to
an algorithm) in the case of a brain.
• Most importantly all mental merely as
aspects of this complicated functioning, that is
to say, they are features merely of the
algorithm being carried out by the brain.

• Thus, mathematical activity is a very tiny area of
conscious that is indulged in by a small minority of
conscious beings for a limited fraction of their
conscious lives.
• . There is a vast area of human consciousness
which does not follow the mathematical rules of
computation
• This non-computational consciousness allows us
to become directly aware of something.
• This direct awareness plays a very important role
in our mental life as we have already mentioned.

• human understanding and conscious awareness
cannot be reduced to computational processes
following algorithms.
• There is something essential in human
understanding that is not possible to simulate by
any computational means.
• According to this view, conscious being either
must be alive must what alive, where the
similarity between the behavior things.
• In other words, only what be haves living thing
that conscious. Our concept conscious state
concept state with certain of behavioral
expression.

• We cannot really make sense conscious stone,
because stone does not behave like conscious
being.
• The point that being biologically alive not the
same being conscious, necessary that
conscious being should behave like living
thing.
• Thus, instead identifying consciousness with
the material composition brain, should
identify with certain higher-order properties
brain,

• which manifest conscious behavior example,
pain higher-order property physical states,
which consists certain pattern causes and
effects, and certain outward behavior

THE NON-COMPUTATIONAL VIEW of
The MIND
Chapter 3

• Descartes is one of the classical founders of
the non-computational theories of mind.
• Without proper understanding of Descartes'
view on mind, impossible discuss the
contemporary philosophy of mind
• This section deals with two important issues,
namely, the existence mind and its nature,
and how Descartes' idea of mind is non-
computational
• These two issues are related to Descartes' non
computational view of mind

The Existence of Mind and Its Nature
• According Descartes, the existence of knowing
subject means that their mind
• again, he tries find out through his cogito
argument that there is at least one knowing
subject, i.e., his own self
• He arrives at this truth through his method of
doubt. For Descartes, cogito ergo sum is an
indubitable proposition
• Doubting one's own existence presupposes
one's existence

• Is it a syllogistic inference like, whatever one
thinks exists; I think; therefore, I exist?
• For Descartes, it is not a syllogistic inference; it
is rather a self-evident truth known by a
simple intuition of the mind.
• The function of the word cogito' in Descartes'
dictum is to refer to the thought-act through
which the existential self-verifiability of l
exists' manifests itself for him.
• the relation of tom' w similar to the recession
of a process to its product.

• The truth of I exist' is revealed to one only
when one actively thinks there is illumination
only when the source of light exists
• The truth of 'l exist' cannot be revealed by any
arbitrary human activity such as treating, etc.
but only by thinking
• According to Descartes, the thought act is due
to the thinking thing, which is the self.
• For him, again, the thinking thing or the self is
that which, "But what then am I A thing that
thinks.

• What is that A thing that doubts, understands
• An attempt to think one's own non-existence
amounts to persuading oneself to the belief that
one does not exist., affirms, denies, is willing is
owl ling, and also imagines and has sensory
perceptions.
• The existence of the thinking thing is the same as
the existence of the knowing thing from this
statement it follows that there is a mind, which
has the power of knowing something.

• And if there exist at least one mind, it is logically
and even empirically possible that their other
minds
• Now the question is: If there is/are mind, what is
its nature or science?
• Thought, according to Descartes, is the essence of
mind the sentence of a thing is defined as that
which is necessary for its existence.
• Descartes claims that he has clear and distinct
perception of awareness that he is a thinking
thing and nothing other than thought belongs to
his nature.

• Malcolm argues that in identifying thought as
mind's essence Descartes employs the following
principle
• X is my essence if it is the case that
• (a) if I am aware of X, then (necessarily) I am
aware of myself and (b) if I am aware of myself
then (necessarily) I am aware to X.
• thinking satisfies these conditions.
• Ergo, thinking is my essence. for Descartes one
of the most important aspects of cognitive states
and processes in their phenomenality.

• Our perception, understanding, judgment etc.
can be defined and explained only in relation
to consciousness
• Ac- cording to Descartes, the mind is a
thinking substance endowed with various
faculties, such as sensory perception,
understanding, willing. ness, etc
• For him, it is one and the same mind, which
wills, under stands, and has sensory
perceptions.

Descartes' Idea of Mind is
Non-Computational
• In the Cartesian scheme of mind, there is no
place for computationalist because the thought
act is due to the subjective thinking thing, which
is the self.
• Again, this subjective thinking thing or the self is
that which "doubts, understands, affirms, denies,
is willing is unwilling, and also imagines and has
sensory perceptions.
• The existence of the thinking thing is same as the
existence of the subjective thinking thing because
it is the subject, who thinks.

• All these subjective activities are non-
computational because subjective activity is not
mechanical.
• The mental processes, for Descartes, are
intentional and are the free acts of the thinking
subject.
• Hence, they cannot be mapped mechanically in
an algorithmic system
• Descartes concept of I think presupposes
subjective experience, because it is ‘i' who
experience the world.

• Descartes' notion of T negates the notion of
computationality in the mind.
• The essence of mind is thought, and the acts
of thoughts are identified with acts of
consciousness.
• Therefore, it follows that cognitive acts are
conscious acts, but not computational acts.
• Thus, for Descartes, one of the most
important aspects of cognitive states and
processes is their phenomenality.

• because our judgments, understanding, etc. can
be defined and explained only in relation to
consciousness, not in relation to computationality.
• We can only find computationality in machines
and not in the mind, which will understand, and
judges.
• Descartes' dictum, "I think, therefore, I am not
only establishing the existence of the self which
thinks and acts but also its freedom from
mechanistic laws, to which the human body is
subject.

• Descartes is a dualist, rather than a mentalist.
• Descartes' argument for the mind, which is
distinct from body, needs to be understood as an
argument for the logical possibility of their
separate existence and not for the fact that they
exist independent of each other.
• Descartes admits the distinction between mind
and body and this shows that the mind is non-
computational.
• It is mind, which has the capacity of intelligence,
and understanding.

The Consequences of
Non-Computationalism
• A non-computational theory of mind brings into
focus the view that consciousness is a
combination of many features such as
qualitativeness, subjectivity, and unity.
• The three are related to each other because the
first implies the second and the second implies
the third.
• We human beings are conscious beings having
conscious experience
• The conscious experience is non-computational

• because human beings have uniqueness of
experiencing things, and it is very important to
understand the very nature of the subjective
experience.
• As Searle puts it, "I think the existence of
consciousness ought to seem amazing to us
• It is easy to imagine a universe without it, but if
you do, you will see that you have imagined a
universe that is truly meaningless.

• Consciousness is the central fact of specifically
human existence because without it all of the
other specifically human aspects of our
existence-language, love, humor, and so on-
would be impossible.
• I believe it is, by the way, something of a
scandal that contemporary discussions in
philosophy and psychology have so little of
interest to tell us about consciousness.
• According to Searle, consciousness is
essentially a subjective, qualitative
phenomenon

• It is not a mechanical state or a certain kind of set
of dispositions to behavior or a computer
program, as many philosophers believe.
• According to him, it is a common mistake to think
that consciousness can be analyzed
behavioristically/psycho logically or
computationally
• The Turing test rests on the mistaken assumption
that the conscious mental states are mechanical
or computational states.

• It gives us the view that for a system to be
conscious, it is both necessary and sufficient
that it has the right computer program or set
of programs with the right inputs and outputs.
• But this leaves no room for the inner,
subjective and qualitative features of the
mental states.
• Our mental states cannot be fully represented
in a machine or in a computer because we
have subjective mental phenomena
• , which require a first-person perspective for
understanding properly

• As Searle puts it, "the qualitative experience can
exist only as experienced by some subject or
subjects.
• And even if the different to ken experiences are
qualitatively identical, that is they all exemplify
the same type,
• each token experience can exist only if the
subject of that experience has it.
• Because conscious states are subjective in this
sense, they have what I call a first-person
ontology,

• as opposed to the third-person ontology of
mountains and molecules, which can exist even
if no living creatures exist.
• Subjective conscious states have a first-person
ontology ('ontology" here means mode of
existence) because they exist only when they are
experienced by some human or animal agent.
• They are experienced by some T that has the
experience, and it is in that sense that they have
find person ontology

• The qualitative features of conscious experience
are uniquely in stated in the characteristic 'feels'
of our conscious experience.
• Nagel made this point, when he pointed out that
if bats are conscious, then there is something that
it is like to be a bat
• This idea of being something like an organism is
not itself a computational notion,
• a computing machine cannot have this idea
because conscious states enter only when human
beings experience them.

• it can only be known from a first-person
perspective, but not from a third-person
perspective.
• This first-person perspective establishes the
notion of subjectivity, which cannot be
computationally explained.
• Nagel puts it, the fact that an organism has
conscious experience at all means, basically, that
that there is something it is like that organism.

• There may be further implications about the
form of the experience, there may even
though I doubt it) be implications about the
behavior of the organism.
• But fundamentally an organism has conscious
mental states if and only if there is something
that it is like to be that organism-something it
like for the organism.

What is Creativity?
• what conditions can we say that a human act is
creative We can identify two aspects in any act.
• One is the product of the act and the other is the
process.
• By product, we mean the thing which is produced
by the act
• the process stands for the way the product is
produced.
• The process, being psychological, is something
subjective.

• Therefore, in order to judge whether an act is
creative, it is not possible to depend only
upon the features of the psychological
processes involved.
• An act can be judged to be creative on the
basis of some of the objective features that
the product possesses, such as artistic
creations, poetic compositions, etc.
• As Vernon defined it Creativity denotes a
person's capacity to produce new or original
ideas, insights, invention or artistic products,

• which are accepted by experts as being of
scientific, aesthetic, social, or technical value.
• Why should we be creative? We are creative
because we have to solve our day-to-day
problems.
• That is to say, we are creative in most of our day-
to-day activities of problem solving.
• Hence, creativity is manifested in problem solving.

AI's Failure in Explaining Consciousness
• Artificial intelligence fails in explaining the
concept of consciousness and creativity
• As we have already seen, the way Al explained the
concept of creativity and consciousness is very
mechanical and artificial.
• It explains consciousness in terms of the
computational functions of the brain and so it fails
to account for the creative features of
consciousness
• As we have already argued, creativity is as one of
the essential features of the consciousness.

The Hard Problem of Consciousness
• In recent times, all sorts of mental phenomena have
yielded to scientific explanation, but consciousness
has stubbornly resisted this explanation.
• Many philosophers and scientists have tried to
explain it, but the explanations always seem to fall
short of the target.
• why is it so difficult to explain?
• According to Chalmers, cognitive science has not
explained, why there is conscious experience at all.

• When we think and perceive, there is a whir of
information processing, but there are also
subjective individual aspects of consciousness,
which go beyond the information processing.
• According to him, even if all the functions of a
system are well articulated, there is further
question as to why there is any experience at
all accompanying their function.
• Cognitive science fails to explain why there is
any experience at all, even though it explains
all the brain functions

• Why is the hard problem so hard?
• And why are the easy problems so easy?
• According to Chalmers, the easy problems are
easy because they concern the explanation of
cognitive abilities and functions.
• To explain a cognitive function, we need a
mechanism that can perform the function.
• The cognitive sciences offer this type of
explanation and so are well suited to the easy
problem of consciousness

• On the other hand, the 'hard' problem is
hard', be- because it is not a problem about
the performance of functions
• . The problem persists even when the
performance of all the relevant functions are
explained.“
• Chalmers says, "I suggest that a theory of
consciousness should take experience as
fundamental.
• We know that a theory of consciousness
requires the addition of something
fundamental to our ontology

• as everything in physical theory is compatible
with the absence of consciousness.
• We might add some entirely new non-
physical feature, from which experience can
be derived,
• but it is hard to see what such a feature
would be like More likely,
• we will take experience itself as a fundamental
feature of the world, alongside mass, charge,
and space-time

• Artificial Intelligence has not solved the hard
problem of consciousness because as we have
seen, it has explained consciousness only in
term of the easy problem of consciousness
• Easy problems are all concerned with how a
cognitive or behavioral function is performed.
• These are questions about how the brain
carries out the cognitive task that is, how it
discriminates stimuli, integrates information
and so on.

• Whereas the hard problem of consciousness
goes beyond the problem about how
functions are performed.
• If artificial intelligence tries to give a definite
definition of consciousness then it leaves out
the explanatory gap
• that is to say, it discusses the distinction
between mind and body
• If this is so, then it leaves out subjective
experience, and opts for there will be only a
third person perspective of consciousness.

The Explanatory Gap and Subjectivity
• The reductionists deny that there is a mind-
body problem at all.
• For them the mind is reductively explainable
in term of body.
• On the other hand, many philosophers hold
that mental states are not reducible to any
physical states.
• Chalmers argues that no reductive explanation
of consciousness can succeed because there is
subjective quality of experience

• Therefore he argues that this quality of
consciousness makes it different from all other
properties, including emergent biological
properties such as life.
• The essence of body is spatial extension, the
essence of mind is thought.
• By the term thought, chalmers understand
everything which we are aware of as
happening within us, in so far as we have
awareness of it.

• Consciousness is essentially a first-person,
subjective phenomena and conscious states
cannot be reduced or eliminated into third-
person.
• It is consciousness, which makes the
explanatory gap between the first person and
third-person perspective.
• Pardhan argues that the mental life is
independent of the physical body, though they
co-exist:

• "(A). The quail of the mental states cannot be
reproduced in an artificial machine like a
robot or a machines table; they are unique to
the person condemned.
• (B). The qualia are the essence of
consciousness and so must be intrinsic to the
conscious subjects
• Thus Pradhan concludes that the intelligibility
gap between the qualia and the physical world
remains, as the qualia are understood widely
as belonging to the conscious subjects.

• the qualitative experience can exist only as
experienced by some subjects.
• Because conscious states are subjective in this
sense, it is legitimate to hold that there is a
first-person ontology, as opposed to the third
person ontology
• Therefore, subjective conscious states have a
first-person ontology because they exit only
when they are experienced by a subject as
well Iris T

• Therefore, subjective conscious states have a
first-person ontology because they exit only
when they are experienced by a subject as
well Iris T who has experience and in this
sense,
• it has the subjective existence
• This gap between the self and the body not
only establishes explanatory gap, but also
gives the ontology of first-person.
• Therefore, the subjectivity or T is the central
problem of the explanatory gap.

• Cognitive science tries to explain how
conscious experience arises from the electrical
process of the brain.
• But it cannot show low and why conscious
states belong to the subject or I
• This qualitative feature of mental states brings
is the existence of qualia, which are the
qualitative experiences of the human mind.

Qualia
• Qualia are the intrinsic quality of conscious
experience
• For example, the experience of tasting a sweet
is very different from that of watching a movie
because both of these have a different
qualitative character of experience.
• This shows that there are different qualitative
features of conscious experience.
• That is why, we cannot derive the pleasure of
eating sweets by watching movies and vice
versa.

• As Chalmers writes, a mental state is
conscious if there is something it is like to be
in the mental state.
• To put it in another way, we can say that a
mental state is conscious if it has a qualitative
feel-an associated quality of experience
• These qualitative feels are also known as
phenomenal qualities, or qualia for short.
• But, functionalists like Dennett have argued
for eliminating qualia from the discourse of
mind.

• The basic reason for them is that mind is a
machine; it cannot entertain the so-called
qualitative subjective experiences called the
qualia.
• We have to show that the mentality of human
mind cannot be represented in a mechanistic
model and that there are subjective mental
states which need a first-person explanation.
• According to Dennett, "qualia are supposed to
be properties of a subjects that are

• are (1) ineffable, (2) intrinsic, (3) private, (4)
directly or immediately appraisable in
consciousness.
• Qualia are ineffable because one cannot say
exactly what way one is currently seeing,
tasting, smelling, and so forth.
• Why qualia are ineffable is that they are
intrinsic properties, which seems to imply
inter alia that they are somehow atomic and
unanalyzable.

• Since they are simple, there is nothing to get
hold of when trying to describe such property.
• Since qualia are ineffable and intrinsic, qualia
are private because all inter personal
comparisons of these of appearing are
systematically impossible.
• . Lastly, since they are properties of
experiences, qualia are directly accessible to
the consciousness because qualia are
properties of one's experiences with which
one is immediately apprehensible in
consciousness.

• Thus, qualia constitute the phenomenal
structure of the mind in that they enrich our
understanding of the mind and also provide
clues to the ontology of the mental.
• What the mental ultimately is, as
distinguished from the physical, is to be
known from what the qualia reveal about
mind
• Therefore, the qualia play a very important
role in the understanding of mind.
• The important question is: Is Dennett right in
calling qualia the private and ineffable
experiences of a queer sort?

• Obviously, not. As Pradhan has argued,
• "the notion of privacy as we know from
Wittgenstein’s private language argument
does not apply to the qualia in the sense that
the qualia are inter subjectively intelligible
and that they are available for inter-personal
communication.
• The qualia of colour perception are such that
any two persons belonging to the same
linguistic community can easily communicate
their colour-experiences and can understand
each other well.

• This shows that the qualia, in spite of being
subjective, are not private at all.
• As to their affability or otherwise, it goes
without saying that they are expressible in an
inter personal language;
• that is the reason why they are accessible to
all speakers if they are suitably placed.
• Thus, Dennett's main argument that the
qualia are inaccessible to all except to the
subject of the qualia does not hold good.

• Again, Dennett's argument that qualia are
atomistic and non-relational is equally weak
for the reason that the subjective experiences
need not be atomistic at all
• they can be taken as constituting the stream
of consciousness in that they constitute a
single unbroken series of the conscious
experiences.
• In this sense the qualities are holistic rather
than atomistic.
• The fact of the matter is that the qualia never
exist in isolation and that they are always in a
constellation.

• For example, the colour experience of a red
rose is not only that of the colour red but also
of the rose plant of certain shape and size.
• Here, the two experiences do not stand apart
but constitute one whole.

Conclusion
• Human beings have many mental qualities
such as intelligence, consciousness, originality,
free will, etc.
• which are said to be necessarily lacking in
machine.
• That is why, a machine is normally treated as
an artefact and a mere mechanical
contrivance manufactured for a definite
purpose.
• Human mind is, on the contrary, essentially
non-computational

• And I have argued that the non-computational
view of mind is already shown by Descartes.
• Descartes' concept of 'I think presupposes
subjective experience, and the first-person
view of mind
• This view of mind negates the notion of
computationalism in the mind.
• The essence of mind is thought, and the acts
of thoughts are identified with acts of
consciousness, so it follows that cognitive acts
are conscious acts, but not computational
acts:

• Thus, for Descartes, one of the most
important aspects of cognitive states and
processes is their phenomenality because our
judgments, understanding, etc. can be defined
and explained only in relations to
consciousness, not in relation to
computationally.

• The mechanistic theory of mind does not have
any positive answer to the question how
qualia are a necessary feature of
consciousness
• Machine functionalism fails to account for the
subjective nature of conscious ness and the
creativity involved in the conscious acts.
• There are two aspects of this thesis, the
epistemological and the metaphysical.
Epistemologically, the subject of
consciousness intimately knows the raw
feelings or the qualia.

• Metaphysically speaking, however, the raw
feelings are real in the sense that they are part
of the furniture of the mental world.
• Therefore, we can hardly deny that the mental
world is real.

Introduction to Philosophy of AI

Introduction to Philosophy of AI

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