This document is available in PDF and HTML here.
The PDF version is generated from the HTML version and may be out of date.
A shorter version originally appeared in Computing in Schools, 1981,
then extended and published in 1984 as
'Experiencing Computation: A Tribute to Max Clowes,'
in New horizons in educational computing,
Ellis Horwood Series In Artificial Intelligence, Ed. Masoud Yazdani,
pp. 207--219, Ellis Horwood, Chichester,

This tribute was much enlarged in March and April 2014, including
-- recollections by Wendy Manktellow (nee Taylor) [WM], and
-- a draft annotated biography of Max Clowes with publications [BIO].
Please send corrections and additions to a.sloman[ at ]


A Tribute to Max Clowes
Aaron Sloman[AS]

Previously: Reader in Philosophy and Artificial Intelligence
Cognitive Studies Programme[COGS]
School of Social Sciences,
The University of Sussex

Since this was posted online at Birmingham University, there have been a number of
modifications. If you have information about Max's biography that you would be
willing to contribute, please let me (AS) know.

Added March 2014
Wendy Manktellow worked with Max at Sussex University, helping with project
administration. She was then Wendy Taylor, and will be remembered by several of
Max's students and collaborators. In February 2014 she stumbled across this
web page, and wrote to me with an anecdote which I've appended below[WM], with
her permission.
Added April 2014 [BIO].
Draft annotated biography/bibliography of Max Clowes, with help from colleagues






Max Clowes died of a heart attack on Tuesday 28th April 1981. He was one of the
best known British researchers in Artificial Intelligence, having done
pioneering work on the interpretation of pictures by computers. His most
approachable publication is cited below. He was an inspiring teacher and
colleague, and will be remembered for many years by all who worked with him. He
helped to found AISB, the British society for the study of Artificial
Intelligence and the Simulation of Behaviour, now expanded to a European
society. This tribute is concerned mainly with his contribution to education.

He was one of the founder members of the Cognitive Studies Programme begun in
1974 at the University of Sussex, a novel attempt to bring together a variety of
approaches to the study of Mind, namely Psychology, Linguistics, Philosophy and
Artificial Intelligence. During the last few years his interests centred mainly
on the process of teaching computing to absolute beginners, including those
without a mathematical or scientific background. He was one of the main
architects of the Sussex University POP11 teaching system (along with Steve
Hardy and myself), which has gradually evolved since 1975. In this brief
tribute, I shall sketch some main features of the system, and hint at the unique
flavour contributed by Max.

POP11 embodies a philosophy of computer education which is relatively unusual.
It includes a language, a program-development environment, and a collection of
teaching materials including help facilities, much on-line documentation, and a
large collection of exercises and mini-projects. Unfortunately, it is at present
available only on a PDP11 computer running the Unix operating system, though a
version now being written in C should be available for use on a VAX by the end
of this year.[CPOP]

When we started planning the system, in 1974, we were much influenced by the
writings of John Holt (see references at end), the work on LOGO at MIT by
Seymour Papert and colleagues, and at Edinburgh University by Sylvia Weir, Tim
O'Shea, and Jim Howe.

These influenced our conviction that learners of all ages should be treated not
like pigeons being trained by a schedule of punishment and reward, but like
creative scientists driven by deep curiosity and using very powerful cognitive
resources. This entailed that learners should not be forced down predetermined
channels, but rather provided with a rich and highly structured environment,
with plenty of opportunities to choose their own goals, assess their
achievements, and learn how to do better next time through analysis of failures.

Although these needs can to some extent be met by many older learning environ-
ments (e.g. meccano sets, learning a musical instrument, projects), the computer
seemed to be potentially far more powerful, on account of its speed, flexibility,
reactiveness and ability to model mental processes. Instead of making toy cranes
or toy aeroplanes, or dolls, students could make toy minds.

Unlike educational philosophies which stress 'free expression', this approach
stresses disciplined, goal oriented, technically sophisticated, activities with
high standards of rigour: programs will not work if they are badly designed. Yet
the computer allows free expression to the extent that students can choose their
own goals, and their own solutions to the problems, and the computer will
patiently, more patiently than any teacher, pay detailed attention to what the
student does, and comment accordingly, by producing error messages, or running the
program and producing whatever output is required. Of course, error messages need
to be far more helpful than in most programming environments, and the system
should make it easy for the student to make changes, to explore 'where the program
has got to', and to try out modifications and extensions without a very lengthy
and tedious edit compile and run cycle.

These ideas are embodied in a course, Computers and Thought, offered as an
unassessed optional first year course for students majoring in Humanities and Social
Science subjects. By making the computer do some of the things people can do, like
play games, make plans, analyse sentences, interpret pictures, the students learn to
think in a new way about their own mental processes. Max put this by saying that he
aimed to get students to 'experience computation' and thereby to 'experience
themselves as computation'.[CT] In other words, our answer to the student's
question 'Does that mean I'm a computer?' is 'Yes'. Of course people are far more
intricate, varied, flexible, and powerful than any man-made computer. Yet no other
currently available framework of concepts is powerful enough to enable us to
understand memory, perception, learning, creativity and emotions.

Choosing a language

Part of the LOGO philosophy was that beginners playing with computers needed a
very powerful language, making it easy to perform interesting tasks quickly. (See
Papert). Interesting tasks include building 'toy minds'. Thus we needed a
language which is interactive and provides procedures with recursion and local
variables, and facilities for non-numerical problem solving, such as list
manipulation. This rules out BASIC. LOGO is much more powerful, but, we felt,
did not go far enough: after all, it was designed for children, so it could not
be powerful enough for children! PASCAL was ruled out as too unfriendly and even
less powerful than LOGO. (E.g. the type structure makes it impossible to program
a general-purpose list-processing package: the package has to be re-implemented
for numbers, words, lists etc.) We did not know about APL. It might have been a
candidate, though its excessively compressed syntax which delights mathematicians
is hardly conducive to easy learning by the mathematically immature. Moreover it
appears to have been designed primarily for mathematical applications, and does
not seem to have suitable constructs and facilities for our purposes. PROLOG
would have been considered had an implementation been available, though it too is
geared too much towards a particular class of problems, and is hard to use for

We therefore reduced the choice to LISP and POP2, and settled for the latter
because of its cleaner, more general semantics (e.g. functions are ordinary
values of variables), more natural syntax, and convenient higher-level
facilities such as partial-application and powerful list-constructors (Burstall
et. al). A subset of POP2 was implemented on a PDP11/40 by Steve Hardy, and then
extended to provide a pattern-matcher, database, and other useful features. We
now feel that the power of PROLOG (see Kowalski 1979) should be available as a
subsystem within POP, and are planning extensions for the VAX version.[CM]

More than just a language

From the start we intended to provide a wide range of facilities in the library, so
that students could easily write programs to do things which interested them: draw
pictures, analyse pictures, play games, have conversations relating to a database of
knowledge, etc. We soon also found the need for help-facilities, on-line
documentation of many kinds, and a simple, non authoritarian teaching program
(written in POP11, and calling the compiler as a subroutine to execute the student's
instructions), which could, for some learners, feel less daunting than a twenty page
printed handout.

One of the ideas that played an important role in our teaching strategy was an
analogy between learning a programming language, and learning a natural
language, like English. The latter does not require formal instruction in the
syntax and semantics of the language. The human mind seems to possess very
powerful capacities for absorbing even a very complex formalism through frequent
and fruitful use. So, instead of starting with lectures on the language,
we decided to give the students experience of using the language to get the
computer to do things we hoped would make sense to them. So they were encouraged
to spend a lot of time at the terminal, trying out commands to draw pictures,
generate sentences, create and manipulate lists, etc, and as they developed
confidence, to start working towards mini-projects. Extending or modifying
inadequate programs produced by the teacher (or other students) provides a means
of gaining fluency without having to build up everything from the most primitive
level. Naturally, this did not work for everyone. Some preferred to switch at an
early stage to learning from more formal documentation. Some found the pain of
even minor errors and failures too traumatic and needed almost to be dragged
back to try again - often with some eventual success. Some, apparently, had
insuperable intellectual limitations, at least within the time-scales available
for them to try learning to program. But many students found it a very valuable
mind-stretching experience.

One of the ways in which Max contributed to this was his insistence that we try to
select approaches and tasks which were going to be more than just a trivial game
for the student. He was able to devise programming exercises which could be
presented as powerful metaphors for important human mental processes - such as
the pursuit of goals, the construction of plans, the perception and recognition
of objects around us and the interpretation of language. He would start the
'Computers and Thought' course by introducing students to a simple
puzzle-solving program and erect thereon a highly motivating interpretation:
treating it as a microcosm of real life, including the student's own
goal-directed activities in trying to create a working program. (Perhaps this is
not unconnected with a slogan he defended during his earlier work on human and
machine vision: "Perception is controlled hallucination'' - hallucinating
complex interpretations onto relatively simple programs helps to motivate the
students and give them a feel for the long term potential of computing).

Moreover, he always treated teaching and learning as more than just an
intellectual process: deep emotions are involved, and need to be acknowledged.
So he tried to help students confront their emotions of anxiety, shame, feeling
inadequate, etc., and devised ways of presenting material, and running seminars,
which were intended to help the students build up confidence as well as
understanding and skills.

There is no doubt that for many students the result was an unforgettable
learning experience. Whether they became expert programmers or not, they were
changed persons, with a new view of themselves, and of computing. Some of this
was due to his inimitable personality. In addition he advocated strategies not
used by many university teachers at any rate: such as helping all the students
in a class to get to know one another, prefacing criticisms with very
encouraging comments, and helping students cope with their own feelings of
inadequacy by seeing that others had similar inadequacies and similar feelings
about them, whilst accepting that such 'bugs' were not necessarily any more
permanent than bugs in a computer program.

As a teacher I found myself nervously treading several footsteps behind him - too
literal-minded to be willing to offer students his metaphors without qualification,
yet benefitting in many ways from his suggestions and teaching practice.

Just before he left Sussex we had a farewell party, at which he expressed the hope
that we would never turn our courses into mere computer science. There is little risk
of that, for we have learnt from him how a different approach can inspire and
motivate students. The computer science can come at a later stage - for those who
need it. For many, who may be teachers, managers, administrators, etc. rather than
programmers or systems analysts, the formalities of computer science are not
necessary. What is necessary is a good qualitative understanding of the range of
types of things that can be done on computers, and sufficient confidence to face a
future in which computation in many forms will play an increasingly important role.

None of this should be taken as a claim that the teaching system based on POP11,
used by Max and the rest of us, is anywhere near perfect. We are aware of many
flaws, some of which we feel we can remedy. But there is still a great deal of
exploring to be done, in the search for a good learning environment, and good
learning experiences. Moreover, we don't know how far what is good for novice
Arts university students would also be good for school children, though several
have played with our system and enjoyed it. We are still in the process of
improving the POP virtual machine to make it a more natural tool for thinking
about processes. This is a never-ending task. Probably a language is needed
which can be 'disguised' to present a simpler interface for the youngest
learners, without sacrificing the power to do interesting things very quickly.
To some extent the 'macro' facility in POP (see Burstall et. al.) makes this

Computing in Schools?

In December 1980 Max left Sussex, to join a project on computing in schools.
Although I don't know exactly what his plans were, I feel that he would probably
have fed many important new ideas into the educational system. New ideas are
surely needed, for teaching children to program in BASIC is like teaching them
to climb mountains with their feet tied together: the permitted steps are so
very small. Moving towards COMAL will merely loosen the ropes a little. Teaching
them PASCAL will loosen the ropes a lot more, but add heavy weights to their
feet: taking some big steps is possible in PASCAL, but unnecessarily difficult.
And some things are not possible, as mentioned previously.

The problems of providing better teaching languages and teaching environments are
enormous, since available computers are much too small, and there is too little
expertise on tap in schools. I think Max might have tried to press for funds to be
diverted from stand-alone microcomputers to larger, shared, machines, or networks,
making available better languages, shared libraries, larger address spaces and
increased opportunities for learners to help one another, including teachers. This
may be more expensive: but what could be a more important use of computers?

Such a system, based on a DEC 11/23, running the UNIX operating system,
has just been introduced at Marlborough College, partly as a result of Max's

It will be interesting to watch what happens there. Maybe we'll learn from that
how to use the newer, cheaper, bigger, faster systems that will shortly be on
the market. Let us hope the existing puny machines with their inadequate
languages will not have turned too many people off computing for life.


Acknowledgements (for the original obituary notice)

I am grateful to Reg Baukham and Masoud Yazdani, who reminded me of some
features of Max's teaching omitted from a first draft, and who pointed me at things
he had written in CSGAS, an informal magazine edited by Masoud Yazdani.


Original References

R M Burstall, et. al. Programming in POP2, Edinburgh University Press, 1972

Max Clowes, 'Man the creative machine: A perspective from Artificial Intelligence
research', in J. Benthall (ed) The Limits of Human Nature,
Allen Lane, London, 1973.

John Holt, How Children Learn, Penguin Books

John Holt, How Children Fail, Penguin Books.

Robert Kowalski Logic for Problem Solving, North Holland, 1979.

Seymour Papert, Mindstorms, Harvester Press, 1981.
Entry for Max Clowes at HOPL (History of Programming Languages) web site.
Alas, now appears to be defunct. (12 Apr 2014)



Now at the University of Birmingham

I discovered a version of this article among some old files in 2001, and
thought it would be useful to make it available online, at least for people
who remember Max, and perhaps others.

I added a few footnotes, putting the text in the context of subsequent

Note added 28 Mar 2014
I have been working on a paper on unsolved problems in vision, making use
of some of Max's ideas, here:

The Cognitive Studies Programme, was founded by Max Clowes and others at
the University of Sussex as a cross-disciplinary undergraduate programme
within the School of Social Studies. Later, a few years after he died it
became a separate School of Cognitive Sciences. Within a few years it
had enlarged further and become what is now known as COGS, The School of
Cognitive and Computing Sciences, with an international reputation. But
for the early inspiration influence of Max Clowes it would never have
existed. My own role in its development was a direct consequence of the
influence Max had in changing my research direction, from about 1969.

Note added 2001:
In fact the version in C proved to be a temporary bridge towards a Pop11
in Pop11 compiler subsequently developed by John Gibson, which became
the core of the multi-language Poplog system, which was later sold world
wide. It is now available free of charge with full system sources at
where much of the still useful AI teaching material has its roots in his
approach to teaching. E.g.

Some years later, ideas that had developed out of the course appeared in a book:
Sharples, M. Hogg, D. Hutchison,C. Torrance,S, Young,D.
Computers and Thought: a practical introduction to Artificial Intelligence
MIT Press 1989.
Many students without backgrounds in programming and mathematics find
that this book provides a useful route into AI and computational cognitive
science. The text (without images) and Pop-11 code can be downloaded here:

Chris Mellish implemented a Prolog in Pop-11 in 1981, and after that the system
combining both languages came to be known as Poplog.
Later, other languages were added, including Common Lisp, and Standard ML.
There are Wikipedia entries with more information:

APPENDIX 1: Max's first pupil (added 9 Mar 2014)

In February 2014, out of the blue, I received a message from Wendy Manktellow,
who, as Wendy Taylor, had worked with Max as an administrative assistant while
he was at Sussex University. She described an episode that sheds light on Max as
teacher and colleague, which I have added here, with her permission.
I have just found your tribute to Max on line and realised, as I read about
his thinking on teaching and learning, that I was his first pupil!!!

I recall his growing consternation having been awarded his chair, that he
was to teach Arts students who would have little or no maths. So he
decided to use me as his guinea pig.

There was one session when he was trying to teach me how to display a loop
on screen from digitised cursive-script handwriting (presumably received
from Essex who were working on that area of AI at the time). We were both
getting very stressed as I displayed it every way but upright. Eventually,
in tears, I said: "Max I am just too stupid to learn."

He stared at me for a moment and said: "No Wendy, I am too stupid to

Years later, after my English degree and a PGCE (both Sussex) when I was
teaching at Comprehensive level, that incident kept coming into my mind. It
was a eureka moment about the nature of teaching and learning.

That day, when I'd dried my tears, Max and I had a long talk about it,
about the feelings of inadequacy, shame and stupidity in the teaching and
learning process. I think we were both stunned that we were both feeling
the same emotions.

Then we got back to finding loops and we both got it right!!!

I never forgot what I learned that day and it made such a huge difference
throughout my teaching career.

Yours is a fine tribute. Max was such a very special person. You all
were. Those pioneering days of the Cognitive Studies Programme in the
prefabs next to the refectory were so full of energy and excitement. I
have wonderful memories of those years.

Thank you for finding the time to read this.

Wendy Manktellow (nee Taylor)


APPENDIX 2: Draft Incomplete Annotated Biography/Bibliography
(Added 11 Apr 2014; Updated: 16 Apr 2014; 5 May 2014)

With thanks to Margaret Boden, Steve Draper, Mark Jenkin, Alan Mackworth,
Keith Oatley, Frank O'Gorman, Vaughan Pratt, Mark Steedman, Tom Vickers, and google.

Max B Clowes

Biography Contents: Biography/Bibliography
  • Date of Birth 1933
    (according to Margaret Boden Mind as Machine, p.787)

  • PhD in the department of Physics, University of Reading,
    supervised by R.W. Ditchburn (1958 or 1959?)

  • The following publication is likely to have been based on the PhD thesis:

    M.B. Clowes & R.W. Ditchburn (1959)
    An Improved Apparatus for Producing a Stabilized Retinal Image,
    Optica Acta: International Journal of Optics, 6:3, pp 252-265,
    Taylor & Francis, DOI: 10.1080/713826291

    Criteria for defining the efficiency of an apparatus for stabilizing the
    retinal image are formulated. A distinction is made between geometrical
    stabilization and stabilization of illumination. A new technique is
    described which employs a telescopic normal incidence system. This makes
    it possible to obtain geometrical compensation both for rotations and for
    translations of the eye. It also gives good illumination stabilization.
    The degree of compensation achieved may be evaluated by precise physical
    measurements. About 99.7 per cent of natural eye rotations in horizontal
    and vertical planes is compensated and the effect of translations is
    negligible. The apparatus is designed to permit easy interchange of
    normal and stabilized viewing conditions.

    (a) The Acknowledgements section states:

    We would like to thank Dr. D. H. Fender and Dr. Stella Mayne for much
    helpful discussion. Mr. W. S. Martin has provided technical assistance in
    the construction of the apparatus. This work was supported by a research
    grant No. B-1233 from the Department of Health, Education and Welfare,
    Public Health Service, U.S.A.
    (b) The document states for Max:
    "Now at the National Physical Laboratory, Teddington."

  • NPL Teddington 1959 - 1963
    (Dates and NPL information provided by Tom Vickers.)
    He seems to have gone from Reading to the National Physical Laboratory,
    Teddington (NPL), where he worked with John Parks, and David Yates.

    I don't have access to the next two papers, apparently written at NPL
    and referenced in his 1967 paper, below.

    • Clowes, M. B., & Parks, J. R.(1961)
      A new technique in character recognition.
      Comput. J. , 4, 121-126.

    • Clowes, M.B.(1962).
      The use of multiple auto-correlation in character recognition.
      Optical Character Recognition.
      Fischer, Pollack, Radack & Stevens, Eds. Pp. 305-318.
      Baltimore: Spartan Books, Inc.

  • Oxford Psycho-linguistics Research Unit 1963-196?
    From NPL he moved to the MRC Psycho-linguistics Research Unit at Oxford.
    The 1967 book chapter was written there.

  • Founding AISB (1964)
    According to Margaret Boden in Mind as Machine Vol 1, p.364, in 1964 Max
    Clowes, presumably still in Oxford, started a "Study Group on Artificial
    Intelligence and the Simulation of Behaviour (AISB)" as a subgroup of the
    British Computer Society, and writes "within a decade this had become the AISB
    Society, under the interdisciplinary leadership of researchers at the universities
    of Edinburgh, Sussex, and Essex. The name was a psychological pun
    on Clowes' part: 'A is B'".

    AISB is still flourishing and celebrated its 50th year
    in 2014: .

    Note: AI did not start at Sussex until Max arrived around 1969, and it did not
    start at Essex until Pat Hayes and Mike Brady, and later Yorick Wilks,
    established it around 1972 and after. So initially the "leadership" must have
    involved Edinburgh plus Max Clowes, then at Oxford?
    PDF versions of the conference proceedings (from 1974) are available at

  • M. B. Clowes, Perception, picture processing and computers
    Machine Intelligence Vol 1 pp 181--197
    Eds. N L Collins and Donald Michie, Oliver & Boyd, 1967.
    Later re-published by Edinburgh University Press.

    For information about the Machine Intelligence series see

    Max's address is given as
    M.R.C. Psycho-Linguistics Research Unit University of Oxford
    The ACKNOWLEDGEMENTS section states:

    "I would like to acknowledge with gratitude the use of the computing
    facilities at the Culham Fusion Research Laboratory, U.K.A.E.A., the
    assistance of Douglas Brand and Barry Astbury, and valuable discussions
    with John Marshall, Professor N. S. Sutherland and Professor
    R. C. Oldfield."
    A footnote says:
    Present address: Computing Research Section, C.S.I.R.O., Canberra, Australia.
    So presumably he went from Oxford to Australia. When?)

    Biology and Engineering
    It is clear that although the paper was written in an engineering context Max's
    concerns were partly biological, as illustrated by these extracts:

    "The ability to interpret and respond to the significant content of pictures is
    shared by a large proportion of the animal kingdom and a small but growing
    number of machines."
    "No machine can as yet approach this sort of performance. We may well
    ask, therefore, what if anything we can learn from a study of 'machine
    perception' which could conceivably help us to understand human perception.
    The answer lies in the fact that any realistic account of the mechanism
    underlying perceptual or any other human skills will be complex. The virtue
    of a computer lies in its ability to capture in a definite form processes of
    indefinite complexity and subtlety, and moreover, to permit an evaluation
    of the efficacy of the proposed description by trying it out on the actual

    He discusses the work done in linguistics on formally characterising linguistic
    structures (e.g. spoken or written sentences) at different levels of
    abstraction, and remarks:

    "Comparable mechanisms for processing pictures have not appeared to any
    significant extent either in Artificial Intelligence or in Psychology. Instead
    the emphasis has been on classifying pictures, i.e., upon the equivalent of
    deciding the type (S1 or S2) of a sentence. The possibility that a structural
    description of a pictorial object is necessary has only recently emerged in
    Artificial Intelligence (Kirsch 1964). It appears to be crucial to the
    automation of many picture processing tasks (e.g., interpreting bubble-chamber
    photographs, recognising fingerprints). That perceptual behaviour involves
    description as well as classification could be supported by innumerable examples
    beyond the two already quoted in the introduction to this paper. However, it
    seems to have received scant attention in recent psychological literature. This
    may well be because overtly descriptive (rather than classificatory) behaviour
    has a large verbal element. There is a strong temptation to avoid this
    'complication' by designing experiments which merely require simple YES/NO
    responses ...." (... or selecting labels from a fixed set, he might have added).

    A variant of this comment could be applied even to a great deal of current AI
    research in machine vision (i.e. up to 2014), focusing on training machines to
    attach labels as opposed to understanding structures. One of the points he could
    have made but nowhere seems to have made, is that natural vision systems are
    mostly concerned with motion and change, including change of shape, and
    change of viewpoint. The emphasis on static scenes and images may therefore
    conceal major problems e.g. those pointed out by J.J.Gibson. AI vision
    researchers later started to address this (partly influenced by Gibson), though
    as far as I can tell, it never interested Max.

    So he specifies the objective of

    "... development of a formal (i.e., rigorous) theory of picture processing which
    aims to provide a structural description of pictorial objects as well as a
    classification of them (wherever appropriate)."

  • Computing Research Section, C.S.I.R.O., Canberra, Australia. 19??-1969?
    (Commonwealth Scientific and Industrial Research Organisation
    The next publication I've found gives Max's address as
    Division of Computing Research,
    C.S.I.R.O., Canberra

    M.B. Clowes, Pictorial relationships - a syntactic approach.
    Machine Intelligence Vol 4, pp 361-384, 1969
    B. Meltzer & D. Michie (eds.). Edinburgh University Press

    Influence of Chomsky
    This important paper was deeply influenced by Chomsky, especially
    Chomsky,N.(1965) Aspects of the theory ofsyntax. Cambridge,
    Mass: MIT Press.

    In particular Max (like several AI vision researchers in that decade) argued
    that images had a type of syntax and what they depicted could be regarded as
    semantic content. Max attempted to develop a research methodology inspired
    partly by Chomsky's work, emphasising the importance of concepts of
    - 'ambiguity' (two possible semantic interpretations for one syntactic form)
    - 'paraphrase' (two syntactic forms with the same semantic content),
    - 'anomaly' (syntactically well formed images depicting impossible semantic
    contents -- impossible objects, e.g. "The devil's pitchfork" often misdescribed
    as an "illusion"!)

    He also emphasised important differences between pictures and human languages, e.g.

    "The variety of relationships which we can readily identify and name is
    much greater in pictorial expressions than in string expressions."
    And goes on
    "Published accounts of 'picture syntax' have not provided any systematic
    accounts of the variety of pictorial relationships with which they deal,
    much less a discovery procedure for those relationships. This omission
    may of course be intentional in the sense that no attempt is being made
    to capture our intuitive knowledge of picture structure in these picture
    syntaxes. In this account, however, we adopt as goal the formal
    description of our pictorial intuitions and accordingly we shall adopt a
    more or less systematic methodology for ascertaining what
    these intuitions are."
    In section 4.5 he writes "we are characterising our intuitions about picture
    structure, not erecting some arbitrary picture calculus." This leads to the notion
    that the same picture, or portion of a picture may instantiate different qualitative,
    relational, structures at the same time, i.e. different 'views'.
    "Significantly, however, we cannot hold these multiple views simultaneously
    -- we switch between them. Formally, that is, we can only assign a single
    relational structure at a time, although this structure may relate a number
    of items ... in quite a complex manner."

    Unlike the majority(?) of current computer vision researchers he did not simply
    accept the properties and relationships that are derivable via standard
    mathematical techniques from image sensor values and their 2-D array
    co-ordinates (e.g. defining "straightness" in terms of relationships between
    coordinates in a digitised image) but instead attempted to identify the
    properties and relationships that are perceived by human viewers and used
    in interpreting visual contents.

    This approach has important consequences:

    "When faced, however, with a wholly novel picture, for example that
    produced in some esoteric experiment in physics, we may find that it
    takes some considerable time to adjust our view so as to recover the
    significant elements of Form and reject the insignificant."
    "The conclusion we would draw from this is that the structure we assign
    to a picture is determined not solely by the 'raw data' of that picture
    but also by a priori decisions as to the varieties of relationship we
    expect to find there. The question therefore becomes 'can we formalise
    these a priori decisions?'"

  • Seeing as hallucinating
    The 1969 paper includes a precursor of the slogan "Perception is controlled
    hallucination" attributed to him by later authors, discussed below:
    "We may summarise the foregoing argument as 'People see what they
    expect to see'. The essential rider is that what they want to see is
    things not pictorial relationships, that is, the a priori decisions
    reflect assumptions about the things and events which we expect to
    see exhibited in the picture. We shall argue that it is necessary and
    indeed possible to give a structural characterisation of things and
    events which is a mapping of the relational structure of the picture.
    This characterisation we call the semantics of the picture."
    There is some ambiguity here as to what sort of contrast is implied by "things
    not pictorial relationships", compounded by the phrase "exhibited in the
    picture". In view of his more explicit discussions in later papers, I take him to
    be saying here that we expect to see things that are not in the picture but are
    represented by the contents of the picture. That would include, for example,
    seeing 3-D structures or object-fragments since the plane surface in which
    the picture lies can include only 2-D entities and their 2-D relationships.
    The 1971 paper (listed below) is unambiguous: the entities represented
    in the picture (the picture's "semantic" content) have 3-D structure, namely
    polyhedra, whose surfaces lie in different planes, most of which are not
    parallel to the picture plane.

    What sorts of entities a collection of lines is intended to denote can affect how it
    should be parsed. E.g. he points out that in a circuit diagram, straightness of
    lines, and the existence of corners are less important than they might be in other
    pictures (e.g. a drawing of a building).

    "A machine (or program) capable of mediating translations between these
    various languages would utilise the underlying semantic structure as the
    'pivot' of the translational process. We could describe such a machine as
    'informed' -- 'informed', that is, about the varieties of relationship
    applicable in these various representations of an event. It would not,
    however, be intelligent. Such an appellation should be reserved for a
    machine (like us) capable of formulating and testing hypotheses about new
    relationships and ultimately about new systems of attainable concepts
    manifesting these relationships."

    Images vs things depicted
    These ideas about interpreting image structures as depicting non-pictorial
    structures (e.g. 3-D objects, electrical circuits, and other things that
    constitute the semantic content of the pictures) are ignored by many current
    vision researchers (in 2014), who, instead, use powerful mathematical machinery
    and elaborate machine statistical learning regimes, whose result is a collection
    of narrowly focused (shallow?) systems that perform well in some (often
    arbitrary) benchmark tests for recognising or labelling image fragments, but are
    far behind the visual capabilities of a human toddler, a squirrel, a
    nest-building bird, an elephant, and many other animals, whose evolution and
    epigenesis are subject to pressures and constraints that are quite different
    from typical AI vision benchmarks.

    I am not sure whether Max drew the conclusion that instead of totally general
    purpose learning mechanisms applied to the raw data of visual and other sensors,
    human-like intelligent machines would need to have learning mechanisms
    tailored to the kinds of environments in which we evolved and preferences for
    types of "syntactic" and "semantic" ontologies that have been found useful in
    our evolutionary history. Research on learning using artificial neural nets
    may be thought to meet that requirement, but that could be based on
    misunderstandings of functions and mechanisms of biological brains. Compare
    John McCarthy on "The well designed child".

    At that time, I don't think Max knew how much he was echoing the viewpoint of
    Immanuel Kant in The Critique of Pure Reason (1781). However, he was aware
    of the work of von Helmholtz (perception is "unconscious inference") and he
    may have been aware of the M.L.J Abercrombie's influential little book
    The Anatomy of Judgement (1960), summarised here, which made several similar
    points from the viewpoint of someone teaching trainee zoologists and doctors
    to see unfamiliar structures, e.g. physiological fragments viewed in a

    The connection between Max's work and Kant's philosophy was later
    acknowledged in Footnote 2 of the 1971 paper 'On Seeing Things' (listed below).

  • Influences and connections while at CSIRO, Australia

    The Acknowledgements section of the Machine Intelligence 4 paper states:

    "The approach to picture interpretation outlined here has emerged from the
    Verbigraphics Project. It is a pleasure to acknowledge my indebtedness to
    my colleagues D. J. Langridge and R. B. Stanton. I am grateful to Dr G. N.
    Lance for encouraging us and supporting us in this work."

    The MSc Thesis of Vaughan Pratt, Dated August 1969, University of Sydney,
    Title: "Translation of English into logical expressions"
    acknowledges "Dr Max Clowes, formerly of CSIRO ...., Canberra, for arousing
    my interest in transformational approaches to English, and also acknowledges
    "Associates of Max, including Robin Stanton, Richard Zatorski, Don Langridge
    and Chris Barter."

  • Move to Sussex University, Experimental Psychology, 1969
    In Oxford, Max had worked with Stuart Sutherland, who later came to
    Sussex University as head of the Experimental Psychology (EP) laboratory in the
    School of Biological Sciences (BIOLS). This functioned more or less
    independently of the social, developmental, and clinical psychology groups in
    schools within the Arts and Social Sciences "half" of the University.

    A result of this move was that Max was invited to return to the UK
    to a readership in EP, where he arrived in 1969. Somehow I came to know
    him and he, Keith Oatley and I had a series of meetings in which we
    attempted to draft a manifesto for a new research paradigm. (I think
    none of us knew at that stage that Margaret Boden also had a strong
    interest in AI, and had been reviewing and commenting on AI publications,
    as reported in Boden(2013).)

    Partly as a result of Max's dislike of the proximity (and smell) of rats, along
    with his interest in linguistics, and psychology of humans, he was offered a
    chair in AI, in the Arts and Social studies area, of the university, in 1973, to
    help start the new interdisciplinary Cognitive Studies Programme, mentioned in
    the obituary notice. This was located in the School of Social Sciences (SOCS).

  • First PhD student, Robin Stanton
    Robin Stanton, mentioned in the acknowledgements section of the MI4 paper,
    was supervised by Max for a PhD at ANU. He came to Sussex University after
    Max moved there in 1969, where I believe he completed the PhD in 1970,
    and remained for a while doing post-doctoral research with Max before
    returning to Australia. Some of that information was obtained from:

    Robin's work shifted from AI to more "central" computing science thereafter.

  • IJCAI 1971
    The second International Joint Conference on AI (IJCAI) was held at Imperial
    College in London in 1971. As a leading AI researcher in the host country Max
    had an important organising role for that conference, though I can't recall
    exactly what it was. One consequence was that he bullied me to fight a bout of
    'flu before the submission deadline and submit a paper, which I did, and it
    changed my life.

  • On Seeing Things (1971)
    The following is Max's best known paper, closely related to the talk he gave at
    the Institute of Contemporary Arts (ICA) around 1971, published later.
    M.B. Clowes,
    On seeing things,
    Artificial Intelligence, 2, 1, 1971, pp. 79--116,
    This develops the themes summarised above and introduced the line-labelling
    scheme used in interpretation of pictures of polyhedra, independently discovered
    by David Huffman, and referred to by Clowes:
    Huffman, D. A.
    Impossible objects as nonsense sentences. Machine Intelligence 6,
    Meltzer, B., and Michie, D. (Eds.), Edinburgh University Press, (1971), 295-323.
    Footnote 1 states: "Omitted from this discussion is any treatment of Huffman's
    [24] excellent study. The two papers employ what is essentially the same idea
    -- the interpretation of junctions as edge complexes -- in a rather different
    manner. Huffman's treatment is applied to single bodies, not to scenes as in
    the present paper, but contains a more extensive formulation of the concept of a
    well-formed polyhedron. The algorithm reported here is not paralleled by any
    procedural mechanism in Huffman's account."

    This shared idea is often referred to as "Huffman-Clowes" labelling, and was
    generalised by many later researchers, including David Waltz who enriched the
    ontology and showed that constraint propagation could often eliminate the need
    for expensive search, and Geoffrey Hinton who showed that use of probabilities
    and relaxation instead of true/false assignments and rigid constraints, allowed
    plausible interpretations to be found in the presence of noise (e.g. missing or
    spurious line fragments or junctions) that would not be found by the alternative
    more 'rigid' mechanisms.

    One of the themes of the paper reiterates the syntax/semantics distinction made
    in his earlier papers, emphasising the need for different domains to be related
    by the visual system, e.g. the picture domain and the scene domain, also
    referred to as the 'expressive' and 'abstract' domains. Consistency requirements
    in the scene (abstract) domain constrain the interpretation of the previously
    found structures in the picture (expressive) domain. An example in the paper is
    that in a polyhedral scene an edge is either concave or convex but cannot be
    convex along part of its length and concave elsewhere when there is no
    intervening edge junction.

    The paper echoes his earlier paper in claiming that the interpretation of
    complex pictures requires "a parsing operation on the results of context-free
    interpretation of picture fragments" i.e. picture elements and their
    relationships need to be described, as a basis for interpreting the picture.

    [This not a comprehensive summary of the contents of the 1971 paper.]

    [ ... summary to be expanded ... ]

    The Acknowledgements section thanks R. Stanton, A. Sloman and especially
    Jack Lang, "for exposing deficiencies in the formulation by attempting to
    program earlier versions of the algorithm".

  • Controlled hallucination?
    Several AI vision publications refer to the 1971 paper as the source of the
    slogan "Perception is controlled hallucination", usually attributed to him.
    However, That wording does not occur in this paper. The closest thing I have
    found is the wording in his 1969 paper quoted above:
    "We may summarise the foregoing argument as 'People see what they
    expect to see'. The essential rider is that what they want to see
    is things not pictorial relationships, ....
    That earlier slogan has more content insofar as it indicates explicitly that the
    hallucinated contents concern things depicted, not contents of the depiction.


    Keith Oatley informs me that a French author expressed a similar
    view of perception much earlier: Hippolyte Taine, a French discursive
    writer of the nineteenth century wrote:
    "So our ordinary perception is an inward dream, which happens
    to correspond to things outside; and, instead of saying that a
    hallucination is a perception that is false, we must say that
    perception is a hallucination that is of the truth"

    Taine, H. (1882). De l'intelligence, Tome 2. Paris: Hachette.
    (p. 13, emphasis in original).
    Full text, in English, available free here:

    Taine's formulation does not include the constructive role of perceptual
    mechanisms implicitly using prior knowledge of constraints on what is
    possible in the environment.

  • M.B. Clowes, "Scene analysis and picture grammars", (1972)
    in: F. Nake and A. Rosenfeld, eds., Graphic Languages
    (Proc. IFIP Working Conf on Graphic Languages, Vancouver, 1972),
    Amsterdam 1972, pp. 70-82;
    also in: Machine Perception of Patterns and Pictures,
    Institute of Physics, London and Bristol, 1972, pp. 243-256
    (I have not found an online version of this.)

  • ICA Lecture 'Man the creative machine...'(1972/3)
    Max Clowes,
    'Man the creative machine: A perspective from Artificial Intelligence research',
    in: J. Benthall (ed) The Limits of Human Nature, Allen Lane, London, 1973.

    I used to believe Max had used the "controlled hallucination" slogan in 1971 in a
    public talk at the Institute of Contemporary Arts, later published in (1973). That
    talk included a still from the film "Sunday bloody Sunday" in which two
    intertwined bodies were shown, presenting the viewer with the task of using
    world knowledge to decide which parts belonged to the same body: an example
    of "controlled hallucination" of hidden connections. The same picture is in the
    published paper. However I have now (April 2014) acquired the book and
    searched through the paper. There is no mention of hallucination, though he
    may have used "controlled hallucination" when presenting the talk at ICA.
    Readers may be able to work out which hands belong to which person, using
    knowledge of human anatomy in this sketch derived from the picture used in the
    ICA presentation and included in the book (apologies for my poor drawing).


  • O'Gorman and Clowes Collinearity (1973, 1976)
    Frank O'Gorman, M. B. Clowes:
    Finding Picture Edges through Collinearity of Feature Points.
    IJCAI 1973: 543-555

    Frank O'Gorman, M. B. Clowes:
    Finding Picture Edges Through Collinearity of Feature Points.
    IEEE Trans. Computers 25(4): 449-456 (1976)

  • Other publications to be added:
    Inaugural Lecture (197??) (unpublished)

    Frank O'Gorman:
    Edge Detection Using Walsh Functions.
    Artif. Intell. 10(2): 215-223 (1978)

  • Students and colleagues at Sussex
    Max had several other research students at Sussex working on various
    aspects of vision, and he also supervised some AI MSc projects. One of
    his students is Alan Mackworth who went on to become a leading AI
    researcher in Canada with a prominent international role, e.g. in IJCAI and
    AAAI, among others.

    Steve Draper followed up a BSc in Physics and a DPhil in AI at Sussex
    supervised by Max, with a career in psychology.
    Larry Paul was supervised both by Max and Aaron Sloman.

    Frank O'Gorman, after an MSc in Computer Science at Birmingham, worked
    with Max as a research assistant for several years (and also taught me a great
    deal about programming and computer science, partly by teaching me Algol 68,
    which was used for their research in the mid 1970s). After the grant ended
    he worked for a while on my POPEYE project described here, which attempted
    to extend some of Max's ideas. The grant was awarded by the Cognitive
    Science panel of the Science Research Council on condition that Max had an
    advisory role. Others on the team were David Owen, and, for a short time,
    Geoffrey Hinton. We were all deeply influenced by Max.
    [Other students, collaborators, etc. ... ?]

  • Obituary notices
    • The Sussex University Bulletin obituary notice in 1981:
      mentions that Max was at Reading, Oxford, and NPL, before he
      went to Australia.
    • There was a short notice in the proceedings of IJCAI 1981, for which I do
      not have the text.
    • Experiencing Computation: A Tribute to Max Clowes, by Aaron Sloman,
      was published in Computing in Schools in 1981,
      the same year as the BBC Micro was announced.
    • The longer version included above was published in 1984, in
      New horizons in educational computing, Ed. Masoud Yazdani,
      Ellis Horwood Series In Artificial Intelligence, pp. 207--219, Chichester,

Margaret A. Boden, "Remarks on Receiving the Covey Award",
in Philosophy & Technology, 26, 3, 2013,
Springer, Netherlands, pp333-339,

About this document ...

This document was originally generated, using LaTeX2HTML,
by Aaron Sloman on 2001-02-17 followed by some hand editing.
Considerable further editing is indicated by notes at the top and in-line comments.

Aaron Sloman
17 Feb 2001
Revised: 1 May 2014; 5 May 2014; 11 May 2014