Advertisement

Heideggerian AI and the Being of Robots

  • Carlos HerreraEmail author
  • Ricardo Sanz
Chapter
Part of the Synthese Library book series (SYLI, volume 376)

Abstract

Current Heideggerian AI (HAI) is the attempt to revise the fundamentals of Artificial Intelligence based on Heidegger’s philosophy. While the debate is much monopolized with questions regarding the role of representations, there is overall agreement that HAI should be conceived to foster development of AI techniques, on the assumption that Heidegger’s ontological analysis of humans (Dasein) should apply to artificial systems. We argue this is inconsistent with Heidegger’s philosophy, as it denies ontological meaning to categories such as robot and human, considered the same type of beings. The aim of this paper is to steer HAI towards the question of our pre-ontological notions of artificial systems, and robots in particular. We present a provisional ontological analysis that considers robots specific, non-human and non-animal beings, which we derive from the relationship between robots and work. Robots are those machines that perform human labour – because in practice they can only transform it, their being is one that cannot be fulfilled.

Keywords

Martin Heidegger Heideggerian AI Hubert Dreyfus Ontology Robotics 

References

  1. Agre, P. E. (1997). Computation and human experience. Cambridge/New York: Cambridge University Press.CrossRefGoogle Scholar
  2. Aristotle (1968) Complete works. Harvard University Press.Google Scholar
  3. Brooks, R. A. (1991). Intelligence without representation. Artificial Intelligence, 47(1–3), 139–159.CrossRefGoogle Scholar
  4. Brooks, R. A., & Steels, L. (Eds.). (1995). The artificial life route to artificial intelligence: Building embodied, situated agents. Hillsdale: L. Erlbaum Associates.Google Scholar
  5. Buchanan, B. G. (1972). Review of Hubert Dreyfus’ what computers can’t do: A critique of artificial reason. Stanford: Department of Computer Science, Stanford University.Google Scholar
  6. Čapek, K., & Selver, P. (1928). RUR (Rossum’s universal robots): A play in three acts and an epilogue. London: H. Milford, Oxford University Press.Google Scholar
  7. Clark, A. (1998). Being there: Putting brain, body, and world together again. Cambridge, MA: The MIT Press.Google Scholar
  8. De Beistegui, M. (2005). The new Heidegger. London: Continuum.Google Scholar
  9. Dennett, D. (1978). Why not the whole iguana? Behavioral and Brain Sciences, 1, 103–104.CrossRefGoogle Scholar
  10. Dieguez Lucena, A. J. (2009). Thinking about technology, but in Ortega’s or in Heidegger’s style? Argumentos de razón técnica: Revista española de ciencia, tecnología y sociedad, y filosofía de la tecnología, 12, 99–123.Google Scholar
  11. Dreyfus, H. L. (1965). Alchemy and AI. The Rand Corporation.Google Scholar
  12. Dreyfus, H. L. (1972). What computers can’t do: A critique of artificial reason. New York: Harper & Row.Google Scholar
  13. Dreyfus, H. L. (2007). Why Heideggerian AI failed and how fixing it would require making it more Heideggerian. Philosophical Psychology, 20(2), 247–268.CrossRefGoogle Scholar
  14. Heidegger, M. (1962). Being and time (trans: Macquarrie, J. & Robinson E.). New York: Harper & Row.Google Scholar
  15. Heidegger, M. (1982). The question concerning technology, and other essays. New York: Harper Perennial.Google Scholar
  16. Heidegger, M. (1993). The end of philosophy. Basic writings (pp. 427–449). New York: Harper Collins.Google Scholar
  17. Heidegger, M. (2001) Introducción a la filosofía, Editorial Cátedra/Ediciones de la Universidad de Valencia, Madrid. Translation by Manuel Jiménez Redondo. Original text Heidegger, M. (2001). Einleitung in die Philosophie (Vol. 27). Vittorio Klostermann.Google Scholar
  18. Kenaw, S. (2008). Hubert L. Dreyfus’s critique of classical AI and its rationalist assumptions. Minds and Machines, 18(2), 227–238.CrossRefGoogle Scholar
  19. Kiverstein, J., & Wheeler, M. (Eds.). (2012). Heidegger and cognitive science. New York: Palgrave Macmillan.Google Scholar
  20. Klir, G. J. (1991). Facets of systems science, volume 15 of IFSR international series on systems science and engineering (2nd ed.). New York: Kluwer Academic/Plenum Publishers.Google Scholar
  21. Kuhn, T. S. (2012). The structure of scientific revolutions. Chicago: University of Chicago press.CrossRefGoogle Scholar
  22. Langton, C. G. (1986). Studying artificial life with cellular automata. Physica D, 22, 120–149.Google Scholar
  23. Masís, J. (2009). Fenomenología Hermenéutica e Inteligenca Artificial: Otra Urbanización de la ‘Provincia Heideggeriana. Proceedings of Primeras Jornadas Internacionales de Hermenéutica. Buenos Aires, Argentina.Google Scholar
  24. McCorduck, P. (1979). Machines who think: A personal inquiry into the history and prospects of artificial intelligence. San Francisco: Wh freeman.Google Scholar
  25. Papert, S. (1968). The artificial intelligence of Hubert L. Dreyfus: A budget of fallacies. Google Scholar
  26. Pattison, G. (2000). Routledge philosophy guidebook to the later Heidegger. London: Psychology Press.Google Scholar
  27. Rouse, J. (2008). Heidegger on science and naturalism. In G. Gutting (Ed.), Continental philosophies of science (pp. 121–141). Oxford: Blackwell.Google Scholar
  28. Sharkey, N. E., & Sharkey, A. J. C. (2007). Artificial intelligence and natural magic. Artificial Intelligence Review, 25, 9–20.CrossRefGoogle Scholar
  29. Taylor, C. (1993). Engaged agency and background. In C. Guignon (Ed.), The Cambridge companion to Heidegger. Cambridge: Cambridge University Press.Google Scholar
  30. Taylor, C. (1995). Philosophical arguments. Cambridge, MA.: Harvard University Press.Google Scholar
  31. Toda, M. (1962). The design of a fungus-eater: A model of human behavior in an unsophisticated environment. Behavioral Science, 7(2), 164–183.CrossRefGoogle Scholar
  32. Wilson, S. W. (1991). The animat path to AI. In J.-A. Meyer & S. W. Wilson (Eds.), From animals to animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior (pp. 15–21). Cambridge, MA: MIT Press.Google Scholar
  33. Winograd, T. A., & Flores, C. F. (1986). Understanding computers and cognition: A new foundation for design. Norwood: Ablex Pub.Google Scholar
  34. Ziemke, T. (2008). On the role of emotion in biological and robotic autonomy. BioSystems, 91(2), 401–408.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Universidad Politécnica de MadridMadridSpain

Personalised recommendations