Learning and Teaching Philosophy
Based on some notes for a second year course on philosophy for AI
Last updated: 27 May 2007
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There are many ways of teaching philosophy. A standard way is to ensure
that students know what various philosophers have thought and written.
This course is too short for that. So I shall aim mainly to try to
ensure that students learn two main kinds of things.
(a) A family of new concepts that are useful for formulating and
discussing philosophical questions.
(b) How to do
philosophy. That is very hard to teach. I don't
really know how communicate it except by doing philosophy and helping
students to do it, hoping that they will somehow pick up the techniques
by imitation and practice. I tried to outline some of the techniques in
my 1978 book The Computer Revolution in Philosophy
, which is now
out of print. However describing
the process of philosophising
does not seem to be good a way of communicating what it is about to
those who have not yet learnt to do it.
To that extent, learning to do philosophy is something like learning to
play the violin, or ride a bicycle. It's very easy to play out of tune,
or lose your balance.
As this is a single module course you are expected to do on average
about 6.5 hours a week of work on the course, including all the time
spent in lectures or classes, reading, writing notes, thinking, etc. A
significant amount of that time should be spent in the main library
finding things out for yourself, e.g. initially by looking for
encyclopaedias and dictionaries of philosophy, so that you learn where
to find things out quickly, reading books that give overviews, and later
on reading recent articles which analyse some of the problems we'll
You may find it useful to start with an introduction to some fairly
`traditional' ways of doing philosophy. E.g. try to find one of the
introductory books listed below, e.g. by Campbell, Hospers, Magee (on
Popper), Mitchell, or one of the collections of readings in philosophy
by Edwards & Pap, Goldman or Lycan. There are very many
books that give introductory overviews, and you will find others by
looking in the library for introductions to philosophy, to metaphysics,
to epistemology, to philosophy of mind, or philosophy of science. For
the first two weeks of the course, simply try to do as much general
reading as you can, and bring to the classes any questions you have
about the arguments, or concepts, or theories you find.
The course is assessed by an essay to be submitted in the Summer term.
In order to be able to write a good essay you will need practice. So
each student will be expected to introduce a discussion of one or two
topics this term, and to write a sample essay on which you can get
critical feedback. Details will be arranged later.
ASPECTS OF PHILOSOPHY
There are many different ways of dividing up philosophy. You may recall
the question we set you at the beginning of your course here:
"Can a goldfish long for its mother?"
This raises many different aspects of philosophy:
What kinds of things exist? (E.g. fish, material
things, mental states, relationships.)
Epistemology (or theory of knowledge):
What can we know and how do
we know it? In particular how could we tell whether a goldfish does or
does not long for its mother? Can we ever know about the contents of
"other" minds? For that matter can we know about anything other than
our own mind and its contents?
The question "How can we know X?" has at least two very
different interpretations. On one interpretation it asks about the
causal history of our knowing: did we see the evidence, or hear it, read
about it, or infer it from some experiment, use our own tests or belief
what someone else said, etc. On the other interpretation it is a
question regarding justification: is the means by which you came to know
X sufficient justification
for claiming that it is true, or that
you know it is true?
Philosophy of mind:
What are mental states and processes? What's
the relationship between mind and body? Are certain material states
to produce mental states? Can mind and matter interact
causally? Could longing cause swimming? Can sadness cause weeping?
Ethics or moral philosophy:
How should we think about the rights
of a goldfish? Do we have the right to kill them? To cause them pain?
To take them from their mothers?
Philosophy of science:
If someone thinks it is a scientific
question whether the goldfish feels pain, then we can ask what the
difference is between science and other types of knowledge, or
knowledge-seeking? What are: scientific theories? Explanations?
Evidence? Can theories ever be proved, or refuted, and if so how?
What's the relationship between the development of new concepts and the
development of new theories?
It soon becomes clear that we are not sure
what question we are asking? What does it mean
to say that a
goldfish longs for something? What does it mean
to say that it can
think about its mother? Or that it has a mother? (Could a tree or a rock
have a mother? What about a battle?) There are many concepts we use
outside of doing philosophy, which are extremely difficult to analyse.
Examples of such concepts are: mind, matter, meaning, truth,
causation, experience, freedom, goodness, concept. knowledge,
explanation, science, intelligence, emotion,
and many more. A great
deal of modern philosophy attacks old problems by showing that the
questions were confused because the concepts used were full of muddles,
like "Where is the universe and which way is it moving?"
I believe that learning to do conceptual analysis is one of the most
important aspects of learning to do philosophy: everything else hangs on
it. E.g. people who are unclear about the concepts they use can argue at
cross purposes, or flounder in interminable debates (for examples see
most of the discussion in comp.ai.philosophy).
But it is also relevant to being a good scientist. One of the most
spectacular examples was how Einstein's attempts to analyse the
our concept of simultaneity led to the special theory of relativity.
Last year you had a brief introduction to conceptual analysis when we
talked about similarities and differences between: embarrassment,
shame, guilt, regret
and related concepts. To help you get back into
doing philosophy have a go at trying to write down what these states
have in common and how they differ.
There is a fairly terse introduction to conceptual analysis in Chapter 4
of The Computer Revolution in Philosophy (1978) now available online
There are many variants on the question about a goldfish. For instance
you could ask about other mental states, or about about other animals.
Here are some examples (in each case add the the question: "What does
this question mean?" "What techniques of enquiry or analysis are
relevant to deciding whether one answer is better than another?"
1. Could a mouse desperately hope that her children will do well in
2. Could a tadpole hope that it will survive to be a frog and make more
3. Is a fly aware of my fly-swatter coming down to flatten it?
(If not, why does it always escape?)
4. Is the fly afraid of being hit by the fly-swatter?
(If not, why does if fly away?)
THE RELEVANCE OF AI TO PHILOSOPHY
It is fairly evident that philosophy is relevant to AI, e.g. helping to
set its goals and clarify many of the concepts it uses, such as
intelligence, perception, learning, memory, understanding,
Equally, AI and Computer Science are relevant to philosophy because they
provide a host of new concepts and forms of explanation, as well as
raising new questions relevant to old philosophical problems, about
metaphysics, about what we can know, about the relationship between mind
For example: what is a virtual machine? What's the relationship between
virtual machines and physical machines? Can virtual machines enter into
causal relationships? Can a "software event" like the creation of a
new data-structure (e.g. a new list), cause
physical events to
occur, or is it only physical things that can enter into causal
relationships? Do computing systems have "emergent" properties? How do
computational machines differ from previous sorts of machines? What are
machines? Are connectionist machines significantly different from
symbol manipulating machines? What are symbol manipulations? Isn't
changing the weight on a neural link a sort of symbol manipulation?
A PROVISIONAL PLAN FOR THE COURSE
It is impossible to plan a philosophy course without knowing the
philosophical capabilities of the students well. So here is a
provisional list of topics, which we may pursue in rough chronological
order, though if appropriate we can change the order. In fact there is
order for learning philosophical concepts and theories:
like learning a new town you have to go round and round getting to know
things better by learning their mutual relationships. So here's a
possible sequence for the course.
(1) Philosophical concepts and jargon.
the acquaintance of some terminology, e.g. notions like
epistemology, metaphysics, ontology, monism, dualism, reductionism,
physicalism (materialism), behaviourism, phenomenalism, idealism,
epiphenomenalism, interactionism, intentionality, "derivative"
intentionality, concept, proposition, rationality, concept empiricism,
knowledge empiricism, supervenience, the analytic/synthetic and
empirical/apriori distinctions, deductive nomological explanations, the
design stance, the intentional stance (Dennett),
, and various theories
about the relation between mind and body.
(2) Computer science, AI and Philosophy.
Try to get a feel for some of the philosophical problems raised by
computing and AI. (E.g. What is a machine? What is computation? What's
the relationship between computational processes and physical processes?
Can a software event cause
a physical event? What is intelligence?
Can there be a behavioural criterion for intelligence? What's the status
of the Turing test? Can computational processes support semantics? Are
neural processes in some fundamental way different from processes on a
(3) Machines and intentionality.
What does it mean to say that a
machine refers to something, or understands something? Searle's chinese
room argument, and replies to it. Causal theories of meaning.
Alternatives to causal theories of meaning. Harnad's "Symbol Grounding
What are they? What is their role in
intelligence? How many different kinds are there? Does logic have a
special role? What, if anything, is special about pictorial or
(5) What sorts of machines could have machines?
Are there some
aspects of mind that are particularly difficult to accommodate in
machines in general, or in computers in particular? Qualia? Pains and
pleasures? Emotional states? Consciousness? Experience? How could this
be settled? Can machines have what Haugeland calls "original
intentionality" as opposed to "derivative intentionality"? The
relevance of new architectures to new analyses of old concepts. What's
the difference between simulation and replication? When is a simulation
of a Y a Y?
(6) Freedom of the will and related concepts.
What Minsky calls
"Dumbell theories" (everything is either an A or a not-A and there's
nothing in between) and what is wrong with them. What could it mean for
a machine to have its own goals? What does it mean for us to have our
own goals? Do we have a kind of freedom machines could never have?
(7) The importance of architecture.
When you have an architecture,
it defines a collection of possible states and processes. (Think of how
current theories of the architecture of matter define different kinds of
stuff - different elements, different chemical compounds, etc. Compare
how people previously thought of water, iron, air, etc.) How many of our
ordinary mental concepts presuppose specific architectures? What sorts
of architectures can support mental states and processes?
Other possible topics to be decided later. Maybe we should talk about
consciousness. There are many other concepts of ordinary language that
we could try to analyse and relate to the possibility of instantiation
in machines, e.g. em sensory experience, learning, desire, pain,
pleasure, emotion, personality.
Philosophy is a very old subject and has spawned a vast and diverse
array of books and journals from many cultures. Here is a tiny subset of
pointers into that literature, including some traditional introductions
to philosophical ideas and also some more recent inspired particularly
by developments in AI. I have not yet read all of this myself. Some of
it is included on the basis of recommendations from others.
Boden, M. (1990)
The Creative Mind
Abacus edition, 1992.
Margaret Boden (Ed)
The Philosophy of Artificial Intelligence
(Oxford University Press,) 1990.
Churchland, P.M. (1984).
Matter and Consciousness: A Contemporary Introduction to the Philosophy
Cambridge MA: MIT Press.
Body and Mind
A useful little introduction
to traditional philosophical theories of mind.
Dennett D.C. (1978).
Brainstorms: Philosophical Essays on Mind and Psychology
Cambridge, MA: MIT Press.
D.C. Dennett, (1984)
Elbow Room: the varieties of free will worth wanting,
Oxford: The Clarendon Press,
Compare my notes on how to dispose of the free will issue
D.C. Dennett, (1996)
Kinds of minds: towards an understanding of consciousness
Weidenfeld and Nicholson,
Paul Edwards & Arthur Pap (eds) (1957) (and various new editions)
A Modern Introduction to Philosophy
Collier Macmillan, New York
Fetzer, J.H. (ed)
Epistemology and Cognition
Kluwer Academic, 1990,
Haugeland, John, (ed)
Mind Design: Philosophy, Psychology, Artificial Intelligence,
Bradford Books, MIT Press, 1981.
Hofstadter D.W. and Dennett D.C. (Eds.) (1981).
The Mind's I: Fantasies and Reflections on Self and Soul
Brighton: Harvester Press.
John Hospers (1973)
An Introduction to Philosophical Analysis
Routledge and Kegan Paul
(Many students have found this a very useful (if somewhat wordy) general
introduction to philosophy.
Lycan, William G. (ed)
Mind And Cognition: A Reader
Oxford: Basil Blackwell, 1990.
Fontana Modern Masters Series.
(A very good short introduction to Karl Popper's views of knowledge and
An introduction to logic
(This is mainly an introduction to philosophical analysis of logical
concepts rather than an introduction to formal logic.)
The Problems of Philosophy
(An ancient paperback book)
The Concept of Mind
(A seminal, yet still underrated book).
Searle J. (1984).
Minds, Brains and Science: The 1984 Reith Lectures
London: BBC Publications.
(An attack on AI)
Sloman, Aaron (1978)
The Computer Revolution in Philosophy: Philosophy science and
models of mind
, Harvester press.
(Out of print but now available online with some afterthoughts added:
There are many journals that include discussion of philosophical issues
relevant to Computing, AI and Cognitive Science. Over the last ten years
or so, standard philosophical journals have increasingly included such
articles, including the following:
The British Journal for the Philosophy of Science
There are also now journals that are explicitly concerned with issues to
do with mind, brain and AI, and include philosophical and
Artificial Intelligence Review
Behavioral and Brain Sciences
Minds and Machines
New Ideas in Psychology
and many more.
3. CONFERENCE PROCEEDINGS
Several AI conferences include philosophical papers, including, for
example, proceedings in the following series of regular conferences:
International Joint Conference on Artificial Intelligence (IJCAI)
American Association for Artificial Intelligence (AAAI)
European Conference on AI (ECAI)
And conferences on Artificial Life.
4. THE INTERNET
There are increasing numbers of World Wide Web sites, some of
which include philosophical references or articles.
David Chalmers has an extensive online bibliography and pointers to many
useful web sites:
A site with general philosophical information is
Many more internet sites giving information about philosophy can be
found by giving google some combination of these words and phrases:
philosophy, epistemology, philosophy of mind, philosophy of language,
philosophy of law, introduction tutorial, etc.
There are various philosophical articles included in the Birmingham
CogAff Web directory, accessible as:
Some of my slide presentations including philosophical presentations are
5. USENET NEWS GROUPS - THE INTERNET
There are several usenet groups that include philosophical discussion
from time to time. Often the "signal to noise" ratio is not very high.
The easiest way to read news groups is to use Google's groups facility:
You can try these news groups:
There is an "electronic" journal of AI that is accessed via Usenet,
the "Journal of AI Research".
See the two groups:
Includes announcements of new papers available on JAIR.
Includes the actual papers, circulated in compressed, uuencoded
(Ask for help if you don't know what that means.)
School of Computer Science
The University of Birmingham