The Bit (and Three Other Abstractions) Define the Borderline Between Hardware and Software
Modern computing is generally taken to consist primarily of symbol manipulation. But symbols are abstract, and computers are physical. How can a physical device manipulate abstract symbols? Neither Church nor Turing considered this question. My answer is that the bit, as a hardware-implemented abstract data type, serves as a bridge between materiality and abstraction. Computing also relies on three other primitive—but more straightforward—abstractions: Sequentiality, State, and Transition. These physically-implemented abstractions define the borderline between hardware and software and between physicality and abstraction. At a deeper level, asking how a physical device can interact with abstract symbols is the wrong question. The relationship between symbols and physical devices begins with the realization that human beings already know what it means to manipulate symbols. We build and program computers to do what we understand to be symbol manipulation. To understand what that means, consider a light switch. A light switch doesn’t turn a light on or off. Those are abstractions. Light switches don’t operate with abstractions. We build light switches (and their associated circuitry), so that when flipped, the world is changed in such a way that we understand the light to be on or off. Similarly, we build computers to perform operations that we understand as manipulating symbols.
KeywordsSymbol Abstraction Hardware Software Physical symbol system Hardware–software bridge Type Abstract data type Bit Affordances Concept externalization Symbol grounding
- Abbott, R. (2008). If a tree casts a shadow is it telling the time? International Journal of Unconventional Computing, 4(3), 195–222.Google Scholar
- Abbott, R. (2019). A software inspired constructive view of nature. Presented at the 2016 conference of the international association for computing and philosophy. To appear in selected papers from that conference. Springer.Google Scholar
- Chua, H.-C. (2018). Teaching notes, National Taiwan University. https://www3.ntu.edu.sg/home/ehchua/programming/java/datarepresentation.html.
- Cubek, R., Ertel, W., & Palm, G. (2015). A critical review on the symbol grounding problem as an issue of autonomous agents. In Joint German/Austrian conference on artificial intelligence (Künstliche Intelligenz) (pp. 256–263). Cham: Springer.Google Scholar
- Dennett, D. C. (2017). From bacteria to Bach and back: The evolution of minds. New York City: WW Norton & Company.Google Scholar
- Gibson, J. J. (1977). The theory of affordances. In R. E. Shaw & J. Bransford (Eds.), Perceiving, acting, and knowing. Abingdon-on-Thames: Lawrence Erlbaum Associates.Google Scholar
- Gibson, J. J. (1979). The ecological approach to visual perception. Boston: Houghton Mifflin.Google Scholar
- Janssen, T. M. V. (2017). Montague semantics. In Zalta, E. N. (Ed.), The Stanford encyclopedia of philosophy (Spring 2017 Edition).Google Scholar
- McCullogh, W. (1960). What is a number that a man may know it, and a man, that he may know a number? Alfred Korzybski Memorial Lecture, Institute of General Semantics, Princeton Club, NY, NY. First published in General Semantics Bulletin, No. 26/27, 7-18. Reprinted in www.vordenker.de (Winter Edition 2008/2009) J. Paul (Ed.) http://www.vordenker.de/ggphilosophy/mcculloch_what-is-a-number.pdf.
- McCullough, W. (1964). What’s in the brain that ink may character? International congress for logic, methodology and philosophy of science, Jerusalem, Israel, August 28, 1964, first published in Embodiments of Mind (pp. 387–397). MIT Press. Reprinted in www.vordenker.de (Winter Edition 2008/2009) J. Paul (Ed.). http://www.vordenker.de/ggphilosophy/mcculloch_whats-in-the-brain.pdf.
- Miyazaki, H. (2013). The wind rises. Koganei: Studio Ghibli.Google Scholar
- Newell, A. (1980). Physical symbol systems. Cognitive Science, 4, 135–183. (Newell includes the following footnote to the paper title. “Herb Simon would be a co-author of this paper, except that he is giving his own paper at this conference. The key ideas are entirely joint”.).CrossRefGoogle Scholar
- Norman, D. A. (1988). The psychology of everyday things. New York: Basic Books.Google Scholar
- Norman, D. A. (2013). The design of everyday things: Revised and (expanded ed.). New York City: Doubleday.Google Scholar
- Rosen, G. (2017). Abstract objects. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Winter 2017 Edition).Google Scholar
- Sony Corporation. (1974). Ad for a Sony sound system. Radio-Electronics, p 13. https://www.americanradiohistory.com/Archive-Radio-Electronics/70s/1974/Radio-Electronics-1974-02.pdf.
- Turing, A. M. (1936) On computable numbers, with an application to the Entscheidungsproblem. Proceedings of the London Mathematical Society, 2 (published 1937), 42(1), 230–265. https://doi.org/10.1112/plms/s2-42.1.230. Turing, A. M. (1938). On computable numbers, with an application to the Entscheidungsproblem: A correction. Proceedings of the London Mathematical Society, 2, 43(6), 544–6. https://doi.org/10.1112/plms/s2-43.6.544.
- Turner, R., & Angius, N. (2017). The philosophy of computer science. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Spring 2017 Edition).Google Scholar
- The Unicode Consortium. (2017). The Unicode ® Standard Version 10.0—Core specification. The Unicode Consortium. http://www.unicode.org/versions/Unicode10.0.0/UnicodeStandard-10.0.pdf.
- US Copyright Office. Website, FAQ page. https://www.copyright.gov/help/faq/faq-general.html. Accessed September 2, 2017.
- van Eijck, J. (2010) A program for computational semantics. Slides for informal presentation. Centre for Mathematics and Computer Science (CWI), Amsterdam, Universities of Utrecht, Amsterdam. https://homepages.cwi.nl/~jve/courses/10/pdfs/APFCS.pdf and http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.297.9166&rep=rep1&type=pdf.
- Wetzel, L. (2018). Types and tokens. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (Fall 2018 Edition).Google Scholar
- Woodward, J. (2003). Making things happen, volume 114 of Oxford studies in the philosophy of science. Oxford: Oxford University Press.Google Scholar