Abstract
More intellectual modesty, but also conceptual clarity is urgently needed in AI, perhaps more than in many other disciplines. AI research has been coined by hypes and hubris since its early beginnings in the 1950s. For instance, the Nobel laureate Herbert Simon predicted after his participation in the Dartmouth workshop that “machines will be capable, within 20 years, of doing any work that a man can do”. And expectations are in some circles still high to overblown today. This paper addresses the demand for conceptual clarity and introduces precise definitions of “strong AI”, “superintelligence”, the “technological singularity”, and “artificial general intelligence” which ground in the work by the computer scientist Judea Pearl and the psychologist Howard Gardner. These clarifications allow us to embed famous arguments from the philosophy of AI in a more analytic context.
Similar content being viewed by others
Notes
From those sympathies, it cannot be inferred that we would embrace Gardner’s “theory” of multiple intelligences, MI, or take it for granted which would be premature given that it has engendered abrasive criticisms due to its apparently little experimental evidence (Waterhouse 2006; Herrnstein & Murray 1994; Traub & Gardner 1999). We do not engage in psychology here, a field where this author is not qualified to contribute to, but in philosophy. And what matters for our philosophical position is that Gardner’s proposal is grounded in a systemic perspective, which is what we embrace (not the complete or exact theory by Gardner). Of course, we invite readers to critically respond to this premise, i.e., our fundamental belief (in systemics).
The overly mechanistic and, thus, inadequate parlance to refer to the complex system “intelligence” aside (cf. Weaver, 1948, who shows that (organized) complexity and mechanics do not go together), the authors not only make one out of two routes to “greater intelligence” about speed (speeding up the hardware), but overall intelligence appears to be reduced to a speedup.
For instance, in respect to the controversy on singularity, Sandberg & Bostrom (2008: 15) assume that “brain activity is Turing-computable, or if it is uncomputable, the uncomputable aspects have no functionally relevant effects on actual behaviour”. According to Proudfoot (2012: 375), this assumption is mere speculation. Also Gödel seemed to be against computational functionalism (Wang 1996: 184).
References
Andrews K, Beck J (2018) Introduction. In: Andrews K, Beck J (eds) The Routledge handbook of philosophy of animal minds. Routledge, New York City, pp 1–10
Baum S (2018) Superintelligence skepticism as a political tool. Information 9:209
Benacerraf P (1967) God, the devil, and Gödel. The Monist LI 1:9–32
Berger M (1982) The scientific approach” to intelligence: an overview of its history with special references to mental speed. In: Eysenck HJ (ed) A model for intelligence. Springer, Berlin, pp 13–43
Berto F (2011) There’s something about gödel: the complete guide to the incompleteness theorem. Wiley-Blackwell, London
Boden MA (2015) GOFAI. In: Frankish K, Ramsey WM (eds) The cambridge handbook of artificial intelligence. Cambridge University Press, Cambridge, pp 89–107
Brentano F (1874/1973) Psychology from an empirical standpoint. In: Rancurello AC, Terrell DB, McAlister LL (eds) Leipzig: Duncker and Humblot. Routledge, London
Bringsjord S, Bringsjord A, Bello P (2012) On Schmidhuber’s “new millennium ai and the convergence of history 2012.” In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 81–82
Bringsjord S, Govindarajulu NS (2018) Artificial intelligence. In: Zalta EN (Ed) Stanford encyclopedia of philosophy. https://plato.stanford.edu/entries/artificial-intelligence/ (30–08–2020).
Brockman J (2015) What do you think about machines that think? Annual question. Edge.org. Available at: https://www.edge.org/annual-question/what-do-you-think-about-machines-that-think (25–11–20).
Brown RL (2018) Animal traditions: what they are, and why they matter. In: Andrews K, Beck J (eds) The routledge handbook of philosophy of animal minds. Routledge, New York City, pp 362–371
Cantwell Smith B (2019) The promise of artificial intelligence. MIT Press, London
Chalmers DJ (1995) Minds, machines, and mathematics: a review of shadows of the mind by Roger Penrose. J Psyche II:11–20
Chalmers DJ (1996) The conscious mind. Search of a fundamental theory. Oxford University Press, Oxford
Chalmers DJ (2010) The singularity: a philosophical analysis. J Conscious Stud 17:7–65
Cole D (2020) The Chinese room argument. In: Zalta EN (Ed) Stanford encyclopedia of philosophy. URL https://plato.stanford.edu/entries/chinese-room/ (25–02–2021).
Crosby M (2020) Building thinking machines by solving animal cognition. Mind Mach 30:589–615
Darwin C (1871) The descent of man and selection in relation to sex, 2nd edn. D. Appleton, New York City
Davidson JE, Downing CL (2000) Contemporary models of intelligence. In: Sternberg RJ (ed) Handbook of intelligence. Cambridge University Press, Cambridge, pp 34–49
Dehn N, Schank R (1982) Artificial and human intelligence. In: Sternberg RJ (ed) Handbook of human intelligence. Cambridge University Press, Cambridge, pp 225–307
Dretske F (1988) Explaining behavior. Reasons in a World of causes. MIT Press, Cambridge
Eden AH, Steinhart E, Pearce D, Moor JH (2012) Singularity hypotheses: an overview. Introduction. In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 1–12
Elster J (1999) Alchemies of the mind. Rationality and the emotions. Cambridge University Press, Cambridge
Flynn M (1997) The concept of intelligence in psychology as a fallacy of misplaced concreteness. Interchange 28:231–244
Franzén T (2005) Gödel’s theorem: an incomplete guide to its use and abuse. Wellesley, Peters
Gardner H (1983/2011) Frames of mind: the theory of multiple intelligences. Basic Books, New York
Garis HD, Halioris S (2009) The artilect debate. why build superhuman machines, and why not? In: Epstein R, Roberts G, Beber G (eds) Parsing the turing test: philosophical and methodological issues in the quest for the thinking computer. Springer, Heidelberg, pp 487–509
Gödel K (1931) Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I. Monatshefte Für Mathematik Und Physik 38:173–198
Gödel K (1951/1995) Some basic theorems on the foundations of mathematics and their implications. In: S. Feferman et al (eds) Reprinted in collected works, Vol III: unpublished essays and lectures. Oxford University Press, New York, 304–323
Godfrey-Smith P (2018) Other minds: the octopus and the evolution of intelligent life. WilliamCollins, London
Good IJ (1965) The Mystery of Go. In: The New Scientist, 172ff.
Haugeland J (1997) What is mind design? In: Haugeland J (ed) Mind design II: philosophy, psychology, and artificial intelligence. Bradford Books, Cambridge, pp 1–28
Herrnstein R, Murray C (1994) The Bell curve. Free Press, New York City
Hiraiwa-Hasegawa M (2019) Evolution of intelligence on the earth. In: Yamagishi A, Kakegawa T, Usui T (eds) Astrobiology. Springer, Singapore, pp 167–176
Hobbes T (1651/1885) Leviathan. Routledge, London
Hodos W (1988) Comparative neuroanatomy and the evolution of intelligence. In: Jerison HJ, Jerison I (eds) Intelligence and evolutionary biology. Springer, New York City
Hofstadter DR (1979) Gödel, escher, bach: an eternal golden braid. Basic Books, New York City
Horgan J (2008) The consciousness conundrum. IEEE Spectr 45:36–41
Jones EE, Pittman TS (1982) Toward a general theory of strategic self-presentation. In: Suls J (ed) Psychological perspectives on the self. Erlbaum, Hillsdale, pp 231–262
Kihlstrom JF, Cantor N (2000) Social intelligence. In: Sternberg RJ (ed) Handbook of intelligence. Cambridge University Press, Cambridge, pp 359–379
Kistler M (2016) L’Esprit matériel : réduction et émergence. Ithaque, Paris
Knight LN, Hargis CH (1977) Math language ability: its relationship to reading in math. Lang Arts 54:423–428
Koellner P (2018a) On the question of whether the mind can be mechanized, I: from Gödel to Penrose. J Philos 7:337–360
Koellner P (2018b) On the question of whether the mind can be mechanized, II: Penrose’s new argument. J Philos 7:453–484
Krubitzer L (2015) Lessons from evolution. In: Marcus G, Freeman J (eds) The future of the brain. Princeton University Press, Oxford, pp 186–193
Kurzweil R (2006) The singularity is near: when humans transcend biology. Penguin USA, New York City
Kurzweil R (2012) On modis’ “why the singularity cannot happen.” In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 343–348
Levesque HJ (2018) Common sense, the Turing test, and the quest for real AI. MIT Press, Cambridge
Loosemore R, Goertzel B (2012) Why an intelligence explosion is probable. In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 83–96
Lucas JR (1961) Minds, machines, and Gödel. Philosophy 36:112–127
Mack CA (2011) Fifty years of Moore’s law. IEEE Trans Semicond Manuf 24:202–207
Marcus G (2004) The birth of the mind. How a tiny number of genes creates the complexities of human thought. Basic Books, New York City
Marcus G (2018) Deep learning: a critical appraisal. Available at: https://arxiv.org/abs/1801.00631 (25–09–2020)
Marcus G (2020) The next decade in AI: four steps towards robust artificial intelligence. arXiv: 2002.06177v3.
Millikan RG (1984) Language, thought, and other biological categories: new foundations of realism. MIT Press, Cambridge
Mindell DA (2015) Our robots, ourselves. Robotics and the myths of autonomy. Viking, New York City
Modis T (2012) Why the singularity cannot happen. In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 311–339
Moore GE (1975) Progress in digital integrated electronics. Tech Digest IEEE Int Electron Dev Meet 21:11–13
Moore GE (2008) Tech luminaries address singularity. IEEE Spectrum. June 2008. Available at: https://spectrum.ieee.org/computing/hardware/tech-luminaries-address-singularity (19–02–21). [interviewed in]
Moravec H (1988) Mind children. The future of robot and human intelligence. Harvard University Press, Cambridge
Moravec H (1998) When will computer hardware match the human brain? J Evolut Technol 1:1–12
Moravec H (1999) Robot: mere machine to transcendant mind. Oxford University Press, Oxford
Muehlhauser L, Salamon A (2012). In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 15–40
Nagel E, Newman JR (2001) Gödel’s proof. With a new foreword by Douglas R. Hofstadter. New York University Press, New York City
National Academies of Sciences, Engineering, and Medicine (2019) Quantum computing: progress and prospects. The National Academies Press, Washington, DC
Newell A, Simon HA (1963) GPS, a program that simulates human thought. In: Feigenbaum EA, Feldman JA (eds) Computers and thought. McGraw-Hill, New York City, pp 279–293
Pearl J (2018a) The book of why. The new science of cause and effect. In: MacKenzie D (ed) Cowritten. Basic Books, New York
Pearl J (2018b) Theoretical impediments to machine learning. In: with seven sparks from the causal revolution. arXiv: 1801.04016.
Penrose R (1989) The emperor’s new mind. Oxford University Press, Oxford
Penrose R (1994) Shadows of the mind. Oxford University Press, Oxford
Penrose R (1996) Beyond the doubting of a shadow: a reply to commentaries on shadows of the mind. Psyche, 2.3. Available at: http://journalpsyche.org/files/0xaa2c.pdf (22–02–21).
Plebe A, Perconti P (2012) The slowdown hypothesis. In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 349–362
Proudfoot D (2012) Software immortals: science or faith? In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 367–389
Raatikainen P (2020) Gödel’s incompleteness theorems. In: Zalta EN (ed) Stanford encyclopedia of philosophy. URL: https://plato.stanford.edu/entries/goedel-incompleteness/ (23–02–2021).
Rajani S (2011) Artificial intelligence—man or machine. Int J Inf Technol 4:173–176
Rescorla M (2020) The computational theory of mind. In: Zalta EN (ed) Stanford encyclopedia of philosophy. URL: https://plato.stanford.edu/entries/computational-mind/ (19–02–2021).
Robinson WS (2015) Philosophical challenges. In: Frankish K, Ramsey WM (eds) The Cambridge handbook of artificial intelligence. Cambridge University Press, Cambridge, pp 64–85
Sandberg A, Bostrom N (2008) Whole brain emulation: a roadmap. In: Technical report 2008–3, future for humanity institute. Oxford University. Available at: http://www.fhi.ox.ac.uk/Reports/2008-3.pdf. (19–02–21).
Schank RC, Abelson RP (1977) Scripts, plans, goals, and understanding. Erlbaum, Hillsdale
Schank RC, Towle B (2000) Artificial intelligence. In: Sternberg RJ (ed) Handbook of intelligence. Cambridge University Press, Cambridge, pp 341–356
Schmidhuber J (2012) New millennium AI and the convergence of history: update of 2012. In: Eden AH, Moor JH, Søraker JH, Steinhart E (eds) Singularity hypotheses: a scientific and philosophical assessment. Springer, New York, pp 61–78
Schulz L, Kushnir T, Gopnik A (2007) Learning from doing. Intervention and causal inference. In: Gopnik A, Schulz L (eds) Causal learning. Psychology, philosophy, and computation. Oxford University Press, Oxford, pp 67–85
Searle J (1980) Minds, brains, and programs. Behav Brain Sci 3:417–457
Searle J (1984) Minds, brains and science. Harvard University Press, Cambridge
Searle J (1999) The Chinese room. In: Wilson RA, Keil F (eds) The MIT encyclopedia of the cognitive sciences. MIT Press, Cambridge, pp 115–116
Searle J (2014) What your computer can’t know. New York Review of Books, October 9.
Select Committee on Artificial Intelligence (2018) AI in the UK: ready, willing, and able? No. HL 100 2017–19. Available from House of Lords Website at: https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf (19–11–2020).
Sloman A (2002) The irrelevance of turing machines to artificial intelligence. In: Scheutz M (ed) Computationalism: new directions. MIT Press, Cambridge, pp 87–127
Sternberg RJ (1997) The concept of intelligence and its role in lifelong learning and success. Am Psychol 52:1030–1045
Tegmark M (2018) Life 3.0. Being human in the age of artificial intelligence. Penguin, London
Tetlock PE (2005) Expert political judgment: how good is it? How can we know? Princeton University Press, Princeton
Tieszen R (2011) After gödel: platonism and rationalism in mathematics and logic. Oxford University Press, Oxford
Toulmin S (1963) Foresight and understanding: an enquiry into the aims of science. Harper Torchbooks, New York City
Traub J, Gardner H (1999) A debate on multiple intelligences. The Dana Foundation. Available at: http://www.dana.org/Cerebrum/Default.aspx?id=39332.
Turing AM (1950) Computing machinery and intelligence. Mind 59:433–460
Vernon PA, Wickett JC, Bazana BG, Stelmack RM (2000) The neuropsychology and psychophysiology of human intelligence. In: Sternberg RJ (ed) Handbook of intelligence. Cambridge University Press, Cambridge, pp 245–264
Vinge V (1993) The coming technological singularity: how to survive in the post-human era. Vision 21: Interdiscip Sci Eng Era Cybersp 1: 11–22.
Walsh T (2017) It’s alive! Artificial intelligence from the logic piano to killer robots. La Trobe University Press, Melbourne
Wang H (1996) A Logical Journey. MIT Press, From Gödel to Philosophy, Cambridge, MA
Wasserman EA, Zentall TR (2006) Comparative cognition: experimental explorations of animal intelligence. Oxford University Press, Oxford
Waterhouse L (2006) Multiple intelligences, the Mozart effect, and emotional intelligence: a critical review. Educ Psychol 41:207–225
Wechsler D (1958) The measurement and appraisal of adult intelligence. Williams & Wilkins, Baltimore
Wells MJ (1966) Learning in the octopus. Symp Soc Exp Biol 20:477–507
Winograd T (1990) Thinking machines: can there be? Are we? In: Partridge D, Wilks Y (eds) The foundations of artificial intelligence: a sourcebook. Cambridge University Press, Cambridge, pp 167–189
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
None of the authors have any competing interests in the manuscript.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hoffmann, C.H. A philosophical view on singularity and strong AI. AI & Soc 38, 1697–1714 (2023). https://doi.org/10.1007/s00146-021-01327-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00146-021-01327-5