Imagination machines, Dartmouth-based Turing tests, & a potted history of responses

  • Melvin ChenEmail author
Curmudgeon Corner


Mahadevan (2018, AAAI Conference. proposes that we are at the cusp of imagination science, one of whose primary concerns will be the design of imagination machines. Programs have been written that are capable of generating jokes (Kim Binsted’s JAPE), producing line-drawings that have been exhibited at such galleries as the Tate (Harold Cohen’s AARON), composing music in several styles reminiscent of such greats as Vivaldi and Mozart (David Cope’s Emmy), proving geometry theorems (Herb Gelernter’s IBM program), and inducing quantitative laws from empirical data (Pat Langley, Gary Bradshaw, Jan Zytkow, and Herbert Simon’s BACON). In recent years, Dartmouth has been hosting Turing Tests in creativity in three categories: short stories, sonnets, and dance music DJ sets. In this post, I will provide a brief and non-exhaustive survey of some plausible responses to these imagination machines and the related prospects for our understanding of the imagination.


Imagination machine Creative imagination Turing Test Definitional problem Attributional problem Creativity 


Curmudgeon Corner

Curmudgeon Corner is a short opinionated column on trends in technology, arts, science and society, commenting on issues of concern to the research community and wider society. Whilst the drive for super-human intelligence promotes potential benefits to wider society, it also raises deep concerns of existential risk, thereby highlighting the need for an ongoing conversation between technology and society. At the core of Curmudgeon concern is the question: What is it to be human in the age of the AI machine? -Editor.


  1. Brooks RA (1990) Elephants don’t play chess. Robot Auton Syst 6:3–15CrossRefGoogle Scholar
  2. Chen M (2018) Criterial problems in creative cognition research. Philos Psychol 31(3):368–382CrossRefGoogle Scholar
  3. Dyson G (1997) Darwin among the machines: the evolution of global intelligence. Helix Books, New YorkGoogle Scholar
  4. Harnad S (1992) The Turing test is not a trick: Turing indistinguishability is a scientific criterion. SIGART Bull 3(4):9–10CrossRefGoogle Scholar
  5. Hobbes T (1651) Leviathan, ed. & intro. Basil Blackwell, Michael OakeshottGoogle Scholar
  6. Kim J (1996) Philosophy of mind. Westview Press, BoulderGoogle Scholar
  7. LaChat M (1986) Artificial intelligence and ethics: an exercise in the moral imagination. AI Mag 7(2):70–79Google Scholar
  8. Lehman J, Clune J, Misevic D, Adami C, Beaulieu J, Bentley PJ, Bernard S, Beslon G, Bryson DM, Chrabaszcz P, Cheney N, Cully A, Doncieux S, Dyer FC, Ellefsen KO, Feldt R, Fischer S, Forrest S, Frénoy A, Gagné C, Goff LL, Grabowski L, Hodjat B, Hutter F, Keller L, Knibbe C, Krcah P, Lenski RE, Lipson H, MacCurdy R, Maestre C, Miikkulainen R, Mitri S, Moriarty DE, Mouret JB, Nguyen A, Ofria C, Parizeau M, Parsons D, Pennock RT, Punch WF, Ray TS, Schoenauer M, Shulte E, Sims K, Stanley KO, Taddei F, Tarapore D, Thibault S, Weimer W, Watson R, Yosinksi J (2018) The surprising creativity of digital evolution: a collection of anecdotes from the evolutionary computation and artificial life research communities. arxiv:1803.03453Google Scholar
  9. Lewis D (1972) Psychophysical and theoretical identifications. Aust J Philos 50:249–58Google Scholar
  10. Lovelace A (1953) Notes on Manabrea’s Sketch of the Analytical Engine Invented by Charles Babbage’. In: Bowden BV (ed) Faster than thought. Sir Isaac Pitman & Sons, LondonGoogle Scholar
  11. Mahadevan S (2018) Imagination machines: a new challenge for artificial intelligence. AAAI Conference, link available at Accessed 17 May 2018
  12. Minsky M (2006) The emotion machine: commonsense thinking, artificial intelligence, & the future of the human mind. Simon & Schuster, New YorkGoogle Scholar
  13. Nichols S, Stephen S (2003) Mindreading: an integrated account of pretense, self-awareness & understanding other minds. Oxford University Press, OxfordCrossRefGoogle Scholar
  14. Nilsson N (1995) Eye on the prize. AI Mag 16(2):9–17Google Scholar
  15. Nilsson N (2010) The quest for artificial intelligence. Cambridge University Press, CambridgeGoogle Scholar
  16. Penrose R (1989) The emperor’s new mind. Oxford University Press, OxfordGoogle Scholar
  17. Polger T (2002) Putnam’s intuition. Philos Stud 109(2):143–70CrossRefGoogle Scholar
  18. Putnam H (1967) Psychological predicates. In: Capitan WH, Merrill DD (eds) Art, mind, & religion. University of Pittsburgh Press, Pittsburgh, pp 37–48Google Scholar
  19. Turing AM (1950) Computing machinery and intelligence. Mind 59(236):433–60MathSciNetCrossRefGoogle Scholar
  20. Weinberg J, Meskin A (2006) Puzzling over the imagination: philosophical problems, architectural solutions. In: Nichols S (ed) The architecture of the imagination: new essays on pretence, possibility, & fiction. Oxford University Press, Oxford, pp. 175–202Google Scholar
  21. Weizenbaum J (1966) ELIZA—a computer program for the study of natural language communication between man and machine. Commun ACM 9(1):36–45CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.University Scholars ProgrammeNanyang Technological UniversitySingaporeSingapore

Personalised recommendations