Experience and Computation

Steve Russ
sbr@dcs.warwick.ac.uk
Department of Computer Science, University of Warwick, UK

Since the emergence of the electronic technology sixty years ago that gave rise to the kinds of computers we use today there have been many attempts to define the notion of computation. These range from precise concepts, such as the evaluation of a function or the execution of an algorithm, that have good mathematical models, to more nebulous notions such as information processing.

Most of these attempts omit any specifically human element in their account of computation. The human contribution has been relegated to the construction of algorithms and the writing of programs which specify computation. While understandable in the context of an automation agenda this is nevertheless a remarkable omission. Prior to the mid-twentieth century the word ‘computer’ meant a person who was good at, or occupied with, computation. There is, of course, a vast history of ‘computing before computers’ and this computing practice was largely managed, controlled, and performed by humans, albeit with the help of various auxiliary devices and means.

Over the last twenty years the Empirical Modelling (EM) group at Warwick has been exploring an alternative approach to computing that restores the human element to computation in an essential way. We are developing a collection of principles that are much broader than the traditional ‘theory of computation’ while still being practical enough to support tools that have given rise to a substantial repository of models on a huge variety of topics. (Basketball, ancient Greek battles and ant navigation by landmarks are some recent examples.) The development of our principles and tools has, implicitly, resulted in a radical revision of the notion of computation. It is a notion in which experience, and therefore the human, plays a central and explicit role.

The key idea in our research is that of building computer-based artefacts that embody the patterns of agency and dependency amongst observables that we identify in the real-world situations for which they are a counterpart. The correspondence between a situation and its computer model is established and elaborated through interaction with the situation, and with the model, in such a way that the interpretation of the model is ‘given in experience’ rather than governed by a formal semantics. The principles by which such a model (or ‘construal’ in the sense used by David Gooding) is built to represent a situation are similar to – though more general than – those by which a spreadsheet is constructed and interpreted. Like spreadsheets, our models can be viewed as capturing states as we experience them ‘in the stream of thought’, and their semantics is rooted in a fundamental tenet of William James’s radical empiricism – that primitive knowledge rests on the way in which ‘one experience knows another’. The approach of EM is fundamentally concerned with sense-making activities.

The principles of EM have far-reaching implications for the nature and scope of computer science. There is clear affinity with the suggestion of Brian Cantwell Smith that computer science may turn out to be a ‘science of intentionality’. With the priority given to direct or ‘felt’ experience in our modelling the principles are inevitably linked to philosophical issues and particularly to phenomenology although our understanding of these connections is still at an early stage.

For more details of the Empirical Modelling group as a whole see www.dcs.warwick.ac.uk/modelling

This paper will describe the principles of EM, demonstrate the tools and some models, and draw attention to some of the philosophical issues that are associated with this form of ‘human computing’. All kinds of criticism, contribution, engagement and participation in the talk and our overall research will be welcomed.