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Chapter 0. Enclosure - Enclosing the Field from ‘Mechanisation of Thought Processes’ to ‘Autonomics’

Chapter 0. Enclosure


Some of the history of a subject may be revealed in its bibliography. The frequent reference to certain authors or publications, whether by way of relevance or reverence, has something to say about what is significant in that particular field. The bibliography of Artificial Intelligence does not lack references to the published proceedings of the Symposium on Mechanisation of Thought Processes that was held at the National Physical Laboratory in Teddington, SW of London, in the autumn of 1958. The particular papers referenced will vary according to preferred flavour: McCarthy’s ‘Programs with Common Sense’, Selfridge’s ‘Pandemonium’ are but two of the most frequently cited; there were also papers from Marvin Minsky, John Backus and others—some less familiar to the student of computing’s history. Yet, while histories of computing never fail to mention the meeting at Dartmouth in the summer of 1956 at which ‘Artificial Intelligence’ is said to have been founded, nor do they neglect the volume Automata Studies, edited by McCarthy and Shannon and published shortly before, the 1958 Symposium is rarely mentioned. The same contributors appear—and more besides. Such gatherings were as rare in 1958 as in the years before, yet history and the bibliographical record seem to differ. A curiosity—this research began as an attempt to discover why.

But this inquiry led to a broader question: what is computing science? Or rather why, when the evidence of that 1958 symposium attests to a very broad interest in the intellectual challenge of computing, should computing have developed to be for the most part an amalgam of mathematics and engineering? To point to the origin of computing machinery in the mid-twentieth century, as a tool for applied mathematicians and as an engineered artefact, will not suffice. The new machinery, both its potential uses and the philosophical questions raised, attracted wide interest; and not all from an ill-informed public dazzled by ‘giant electronic brains’.

A new phenomenon is perceived, explained, and assimilated by analogy with what is already known. A restricted range of analogues, a poverty of models, may constrain the understanding that is eventually achieved. When, through familiarity, the computer ceases to be ‘a sort of...’ and is just an everyday object, the place of that object in our world may depend on the route by which we have come to understand it.

In the 1940s and 50s there were other models of computing and automated machinery, analogies that took their inspiration not from engineering, physics, or mathematics, but from biology; from empirical observation rather than a priori reasoning; from a study of creatures in the world, doing and being done by, rather than commanded by instructions in code. This approach retains a following, indeed it shows signs of renewed interest, but it is peripheral to what presently constitutes computing science; cognitive science is, perhaps, more a sub-field of psychology than computing. And new fields such as bio-informatics are certainly not in the tradition of biology: rather, they show the adoption (some might say usurpation) of the reductive and discrete traditions of physics by the life sciences.

If we talk of an enclosure of computing science, of its assimilation into a predominant scientism—reductive, mechanical, the purity of its science assayed by the density of its mathematical content—then the traditions of natural history are not the only exclusion. There was, for example, from the beginning, a significant interest in computing applied to natural language. This has had less lasting influence; unlike genetics and molecular biology the enthusiasm for machine translation did not lead to a notable success for a mathematico-logical approach. But what of a counter influence? At the time of the Teddington symposium, there were significant developments in programming languages, Fortran, Cobol, Algol, and Lisp, all represent significant strands in the move toward high-level languages and conceptions of a virtual machine. That is, a machine instantiated by an effort of imagination. Yet though we talk of programming languages, the analogy of software-as-fiction appears to have attracted little attention. By and large, we study the language of programs in a manner which the experience of machine translation might have led us to distrust. Though programs are written, and the text enacted, the analogy of a literature of programs seems to have attracted only passing attention.

In 1958 then, there was an open field: computing as an intellectual challenge knew no disciplinary boundaries. Within ten years, there was a distinct discipline of computing science, yet one that seems to lack a ‘cognitive content’ of its own. A study of computing machinery is engineering, a study of algorithms, mathematics: what is unique to computer science? The answer I suggest is software, but not as the coding of an algorithm, nor the specification of a virtual machine; outside the field enclosed by engineering and mathematics, there is not only a natural history but also a humanist perspective: a study of the virtual worlds conjured up by programming.

In chapter one we will consider the problem of what we see when we encounter a thing for the first time. In chapter two, the origin of the deep cultural bias that favours the abstract, the ‘useless’ and mathematical knowledge. The third chapter looks at the computing and automation in the biological tradition. Chapter four is an account of Autonomics at NPL, a research programme that owes much to that biological influence. Examining the context of one project in that programme, machine translation, the dominance of a mathematico-logical model is evident. Finally, in a contrasting view of the nature of language, chapter six attempts to trace the gradual coming into consciousness of programming as a literary activity.

This work thus falls into three parts. The first two chapters are concerned with theory, a history of ways of seeing. The second and major part, which extends from chapter three into chapter five, is a history of a particular perception of computing and computers. The final part, taking chapter five forward into six, retraces that history of computing to detect the emergence of yet another perception, one whose status—mainstream or meander—is as yet undecided.

2014-07-19 18:44
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