Seminar series: Philosophy of computer science

University of Essex

When & where: 3pm, Friday 18-Sep-2009, Room 1N1.4.1 (Network Building seminar room)

Speaker: Rick Kazman is a professor in the Department of Information Technology Management in the Shidler College of Business at the University of Hawaii, Honolulu, HI, USA and a visiting scientist at the Software Engineering Institute of Carnegie Mellon University, Pittsburgh, PA, USA

The Metropolis Model: Crowdsourcing for Software and Content Development

Abstract: We are in the midst of a radical transformation in how we create our information environment. This change—the rise of large-scale cooperative efforts, peer production of information—is at the heart of the open-source movement but open source is only one example of how society is restructuring around new models of production and consumption. This change is affecting not only our core software platforms, but every domain of information and cultural production. The networked information environment has dramatically transformed the marketplace, creating new modes and opportunities for how we make and exchange information. “Crowdsourcing” is now used for creation in the arts, in basic research, and in retail business. These changes have been society-transforming. So how can we prepare for, analyze, and manage projects in a crowdsourcing world? Existing software development models are of little help here. These older models all contain a “closed world” assumption: projects have dedicated finite resources, management can “manage” these resources, requirements can be known, software is developed, tested, and released in planned increments. However, these assumptions break in a crowdsourced world. In this talk we will present principles on which a new system development model must be based. We call these principles the Metropolis Model.

Reference: Rick Kazman, Hong-Mei Chen. “The metropolis model a new logic for development of crowdsourced systems.” Communications of the ACM 52(7): 76-84.

Audience: Open to the general public

Where & when: Friday 10-Oct-2008, 3:00 pm (place to be confirmed)

Speaker: Prof. Selmer Bringsjord, Chair, Department of Cognitive Science, and Director, Rensselaer AI & Reasoning Lab, Rensselaer Polytechnic Institute (RPI) Troy NY 12180

Doing AI That's Tough Enough: Human Genius, Hypercomputation, and Automatic Programming

Abstract: Human persons are astonishingly smart.  Members of this group have managed to produce such things as *Hamlet*, G\"{o}delian incompleteness results, and the Ninth Symphony; we could continue the list indefinitely.  On the other hand, many of the things human persons do don't require lots of smarts.  (Ants can walk from point A to B, and when humans do such things, in general, they do nothing ingenious.)  Unfortunately, AI has, by my lights, devolved away from striving to engineer computing machines that are human-level smart.  I explain this situation, make it precise by explicating 'human-level smart' as doing something that requires hypercomputation, and present the latest example (within the context of prior ones) of AI work I'm pursuing because it's truly tough enough: automatic programming. 

Audience: Open to the general public

Where & when: Friday 14-Dec-2007, 3:00 pm, seminar room, Department of Computing & Electronic Systems

Speaker: Amnon Eden, Department of Computing & Electronic Systems, University of Essex, and Center For Inquiry, Amherst, NY, USA

Host: Wayne Martin, Department of Philosophy, University of Essex

Three Paradigms of Computer Science

Abstract: Is computer science a branch of mathematics, as Tony Hoare suggested, concerned primarily with mathematical objects such as algorithms? Is it an engineering discipline, concerned primarily with the construction of complex software artefacts on a par with bridges and power plants? Or is it an experimental ('natural') science on a par with astronomy and economics, as Newell and Simon claimed? Should knowledge about the behaviour of programs proceed deductively (using proofs) or empirically (by experimentation)? We discuss some of the methodological and philosophical disputes among computer scientists and suggest that distinct positions taken in regard to these questions emanate from distinct sets of received beliefs or paradigms within the discipline:

• The rationalist paradigm, which was common among theoretical computer scientists, defines computer science as a branch of mathematics, treats programs on a par with mathematical objects, and seeks certain, a priori knowledge about their ‘correctness’ by means of deductive reasoning.
• The technocratic paradigm, promulgated mainly by software engineers, defines computer science as an engineering discipline, treats programs as mere data, and seeks probable, a posteriori knowledge about their reliability empirically using testing suites.
• The scientific paradigm, prevalent in the branches of artificial intelligence, defines computer science as a natural (empirical) science, takes programs to be entities on a par with mental processes, and seeks a priori and a posteriori knowledge about them by combining formal deduction and scientific experimentation.

Are computer scientists at Essex experimental scientists, technocrats, or rationalists? Are the traditional distinctions any longer relevant?

Keywords: philosophy of computer science; ontology and epistemology of computer programs; scientific paradigms

Reference: Amnon H Eden. “Three Paradigms of Computer Science.” Minds & Machines, Special issue on the Philosophy of Computer Science, Vol. 17, No. 2 (Jul. 2007) pp. 135–167.

Audience: Open to the general public

Where & when: Friday 8-Dec-2006, 3:00 pm, seminar room, Department of Computer Science

Speaker: Dr. Susan Stuart, University of Glasgow

Bodily Consciousness and Kinaesthetic Imagination

Abstract: Imagination is commonly thought to amount to nothing more than a creative faculty. But imagination as bodily expectation can be revealed through examination of the imagination’s productive, bodily, character, that aspect of the mind that extrapolates through bodily consciousness or experience an anticipation or, let us say, an expectation of how our world will continue to be from moment to moment, from sensation to sensation. It is a notion of imagination that is fundamental to any conscious experiencing system, for it is through the smooth functioning of this imagination that we are able: (i) to have unconscious expectations about how our world will be with regard to each of our senses and (ii) to recognise change when our sensory expectations are not realised. Perhaps most importantly it is from this power of the imagination, to build up unconscious sensory expectations and recognise when they are not realised, that we are able to develop our sense of the passage of time. Thus, our sense of the passage of time is, at base, physiological and unconscious, and derived from our plenisentient and dynamic coupling with our environment.

Audience: Open to the general public

Where & when: Friday, 21-Apr-2006, 3:00 pm, seminar room, Department of Computer Science

Speaker: Prof. Luciano Floridi, Dipartimento di Scienze Filosofiche, Università degli Studi di Bari, and Faculty of Philosophy and IEG, Computing Laboratory, Oxford University.

The Informational Nature of Reality

Abstract: In recent years, there has been a renewed and growing interest in ontological issues. One of the classic questions that has resurfaced is whether the ultimate nature of reality might be digital (discrete) or analogue (continuous). Digital Ontology (and its corollary thesis of Pancomputationalism) and Informational Structuralism seek to provide an answer to this fundamental and very old question, by relying on original and innovative analyses in terms of computational systems. They are fellow travellers, which share a similar outlook but differ in the conclusions reached. In this talk, I shall first provide a brief introduction to a digital approach to ontology. I shall then argue that Digital Ontology is mistaken insofar as it favours a one-sided interpretation of the ultimate nature of reality. I shall present a thought experiment against the dichotomy “digital vs. analogue” in order to argue that either (a) the dichotomy is misapplied because of a confusion regarding the nature of the object under analysis or (b) if properly applied, it runs into counterintuitive consequences. This leaves Informational Structuralism—according to which it is a matter of levels of abstraction whether reality is to be described as digital or analogue—as a more convincing option. Informational Structuralism may not be the only game in town, but it is the only one that is metaphysically safe to play.

Audience: Open to the general public

Where & when: Wednesday, 16-Nov-2005, 4:30 pm, seminar room, Department of Computer Science

Speaker: Prof. Barry Smith, Department of Philosophy, State University of New York at Buffalo, USA, and Institute for Formal Ontology and Medical Information Science, Saarland University, Germany.

Why Computer Science Needs Philosophy

Abstract: Human beings are becoming ever increasingly dependent on computers, not only in their everyday traffic with the world but also in their special activities as scientists, doctors, managers, administrators, soldiers. This means that software engineers are increasingly confronted with challenges of a new kind. How can they build software that can do justice in a useful and sophisticated way to the reality of chemistry, or biology, or medicine, or of a large enterprise, or battlefield? How, even more problematically, can they do justice simultaneously to a plurality of such domains — for example of genes/proteins/cells/toxins/diseases — in ways which would allow inferences to be drawn automatically from the corresponding data? One currently popular response to these challenges from the computational side consists in the building of what are called 'ontologies'. We shall examine some of the results of this work, and show in what ways it is confused. We shall then describe how philosophy is being used to resolve such confusions, and indicate more generally the practical value that can be derived from the confrontation between computer science and philosophy.

Audience: Open to the general public

Where & when: Wednesday, 6-Apr-2005, 11 am, seminar room, Department of Computer Science

Speaker: Prof. B. Jack Copeland, Professor of Philosophy, University of Canterbury, New Zealand

Alan Turing: The Mechanisation of Thought Processes, Intelligent Machines, and the Imitation Game

Abstract: The field of Artificial Intelligence is commonly believed to have originated in the United States in 1956. In fact, the field's origins can be traced back 15 years earlier, to the wartime work of Alan Turing on the Enigma code at Bletchley Park, the British codebreaking headquarters.

In 1936 Turing, perhaps the greatest pioneer of the Information Age, had conceived the basic principle of the modern computer, the idea of controlling the machine's operations by means of a program of coded instructions stored in the computer's memory. At the war's end in 1945 Turing drew up the first complete design for an electronic stored-program universal digital computer—a Turing machine in hardware. A computer based on his design (the 'DEUCE') went on to become a cornerstone of the fledgling British computer industry.

This lecture examines the evolution of Turing's thinking about machine intelligence, from his early investigations at Bletchley Park through to his famous 1950 publication 'Computing Machinery and Intelligence', where he set out his 'imitation game'. Now known simply as the Turing Test, this has been the target of a hail of objections from both computer science and philosophy. I show that the leading objections in the literature miss their mark, being for the most part based on misunderstandings of Turing's subtle test.

Audience: Open to the general public