Abstract
Will robots ever be able to learn like humans? To answer that question, one first needs to ask: what is learning? Hubert and Stuart Dreyfus had a point when they claimed that computers and robots would never be able to learn like humans because human learning, after an initial phase of rule-based learning, is uncertain, context sensitive and intuitive (Dreyfus and Dreyfus in A five stage model of the mental activities involved in directed skill acquisition. (Supported by the U.S. Air Force, Office of Scientific Research (AFSC) under contract F49620-C-0063 with the University of California) Berkeley, February 1980. (Unpublished study). Washington, DC: Storming Media. https://www.stormingmedia.us/15/1554/A155480.html. Accessed 10 Oct 2017, 1980). I would add that learning also builds on prior learning, and that from the outset (birth), human learning is a socio-cultural materially grounded collective epistemology. This posthuman acknowledgement shifts the focus from the individual learner to learning within collective phenomena. Dreyfus and Dreyfus (1980) do not seem to emphasise the essentially social and cultural nature of the human condition. Learning theory (especially the Vygotskyan perspective), new materialism (especially as presented by the physicist Karen Barad) and postphenomenology (especially as presented by Don Ihde) have emphasised in different ways the materially based socio-cultural nature of human learning. They thereby point towards a ‘posthuman’ learning that is far from the machine-like or enhanced creature envisioned by singularists. Until robots are essentially social and ground their epistemologies in socio-cultural materiality, I suggest that human-like AI is not possible.
Similar content being viewed by others
Notes
Note, I have reversed the gender presented by the Dreyfus brothers, who themselves lamented that they were ‘painfully aware’ of their use of ‘he’ (Dreyfus and Dreyfus 1986, 20).
The Dreyfus–McDowell debate (see McDowell 2007) is more complex than I can deal with here, even if relevant for the topic of learning. It is about if and how rationality is already embodied in perception. The cultural aspect of materiality is often overlooked in these debates and that the ‘affordances’ McDowell and Dreyfus argue about could be seen as culturally diverse intra-active meetings halfway between concept formation and unpredictable materials.
From a posthuman perspective, it is not at all certain that this is an ability of humans alone. We increasingly acknowledge that animals also live in meaningful worlds.
References
Barad K (2007) Meeting the universe halfway: Quantum physics and the entanglement of matter andmeaning. Duke University Press, Durham
Boden MA (2006) Mind as machine: a history of cognitive science, vol 1. Oxford University Press, Oxford
Braidotti R (2013) The Posthuman. Polity Press, Cambridge
Dreyfus HL (1965) Alchemy and artificial intelligence. The RAND Corporation. Paper P-3244
Dreyfus HL (1979) What computers can’t do. MIT Press, New York
Dreyfus SE (2004) The five-stage model of adult skill acquisition. Bull Sci Technol Soc 24(3):177–181. https://doi.org/10.1177/0270467604264992
Dreyfus S, Dreyfus H (1980) A five stage model of the mental activities involved in directed skill acquisition. (Supported by the U.S. Air Force, Office of Scientific Research (AFSC) under contract F49620-C-0063 with the University of California) Berkeley, February 1980. (Unpublished study). Washington, DC: Storming Media. https://www.stormingmedia.us/15/1554/A155480.html. Accessed 10 Oct 2017
Dreyfus HL, Dreyfus SE (1986) Mind over machine: the power of human intuition and expertise in the era of the computer. Free Press, New York
Ferrando F (2013) Posthumanism, transhumanism, antihumanism, metahumanism, and new materialisms. Differ Relat Existenz 8(2):26–32
Gill KS (1991) Summary of human-centred systems research in Europe, part 1. Systemist. J UK Syst Soc 13(1):7–27
Hasse C (2008) Postphenomenology—learning cultural perception in science. Human studies. Springer, Hamburg, pp 43–61
Hayles K (1999) How we became posthuman; Virtual bodies in cybernetics, literature, and informatics. The University of Chicago Press, Chicago
Ihde D (2002) Bodies in technology. University of Minnesota Press, Minneapolis
Ihde D (2003) Postphenomenology again. Working Papers from the Centre for STS Studies, nr 3, 2003, http://sts.au.dk/fileadmin/sts/publications/working_papers/Ihde_-_Postphenomenology_Again.pdf. Aarhus
Ihde D (2011) Of which human are we post? In: Gregory R, Hansell, Grassie W (eds) Transhumanism and its critics, Chapter 8. Metanexus Institute, Philadelphia, pp 123–135
Kurzweil R (2005) The singularity is near: when humans transcend biology. Viking, New York
Lyyra A (2015) Towards interaction machines. iSChannel 9(2):6–13
McDowell J (2007) What myth? Inquiry 50(4):338–351. https://doi.org/10.1080/00201740701489211
Minsky M (1986) The Society of Mind. Simon and Schuster, New York
Merleau-Ponty M (1962/1945) Phenomenology of perception. (C. Smith, Trans.). Routledge, New York, London
Mercer C, Trothen T (2014) The religion of technology: transhumanism and the myth of progress. In: Mercer C, Trothen T (eds) Religion and transhumanism: the unknown future of human enhancement. Praeger, Westport
More M, Vita-More N (2013) The transhumanist reader: classical and contemporary essays. Wiley-Blackwell, New York
Nagel T (1974) What is it like to be a bat? Philos Rev 83(4):435–450
Nath R, Sahu V (2017) The problem of machine ethics in artificial intelligence. AI Soc. https://doi.org/10.1007/s00146-017-0768-6
Sheets-Johnstone M (2000) Kinetic tactile-kinesthetic bodies: ontogenetical foundations of apprenticeship learning. Hum Stud 23(1):343–370 (Kluwer Academic Publishers, Amsterdam)
Vygotsky LS (1978) Mind in society: the development of higher psychological processes. In: John-Steiner V, Scribner S, Souberman E (eds) Cole M. Harvard University Press, Cambridge
Vygotsky LS (1987) Thinking and speech. In: Rieber RW, Carton AS (eds) The collected works ofL.S. Vygotsky, vol. 1 Problems of general psychology, Plenum, New York, pp 39–289.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hasse, C. Posthuman learning: AI from novice to expert?. AI & Soc 34, 355–364 (2019). https://doi.org/10.1007/s00146-018-0854-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00146-018-0854-4