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Moral Dilemmas for Artificial Intelligence: A Position Paper on an Application of Compositional Quantum Cognition

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Quantum Interaction (QI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11690))

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Abstract

Traditionally, the way one evaluates the performance of an Artificial Intelligence (AI) system is via a comparison to human performance in specific tasks, treating humans as a reference for high-level cognition. However, these comparisons leave out important features of human intelligence: the capability to transfer knowledge and take complex decisions based on emotional and rational reasoning. These decisions are influenced by current inferences as well as prior experiences, making the decision process strongly subjective and “apparently” biased. In this context, a definition of compositional intelligence is necessary to incorporate these features in future AI tests. Here, a concrete implementation of this will be suggested, using recent developments in quantum cognition, natural language and compositional meaning of sentences, thanks to categorical compositional models of meaning.

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Notes

  1. 1.

    We avoid the term representation because in the literature it has been invoked with many different connotations.

References

  1. Signorelli, C.M.: Can computers become conscious and overcome humans? Front. Robot. Artif. Intell. 5, 121 (2018). https://doi.org/10.3389/frobt.2018.00121

    Google Scholar 

  2. Turing, A.: Computing machinery and intelligence. Mind 59, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  3. Silver, D., et al.: Mastering the game of go without human knowledge. Nature 550, 354–359 (2017)

    Article  Google Scholar 

  4. Bringsjord, S., Licato, J., Sundar, N., Rikhiya, G., Atriya, G.: Real robots that pass human tests of self-consciousness. In: Proceeding of the 24th IEEE International Symposium on Robot and Human Interactive Communication, pp. 498–504 (2015)

    Google Scholar 

  5. Legg, S., Hutter, M.: Universal intelligence: a definition of machine intelligence. Minds Mach. 17, 391–444 (2007)

    Article  Google Scholar 

  6. Arsiwalla, X.D., Signorelli, C.M., Puigbo, J.-Y., Freire, I.T., Verschure, P.: What is the physics of intelligence? In: Frontiers in Artificial Intelligence and Applications, Proceeding of the 21st International Conference of the Catalan Association for Artificial Intelligence, vol. 308, pp. 283–286 (2018)

    Google Scholar 

  7. Arsiwalla, X.D., Sole, R., Moulin-Frier, C., Herreros, I., Sanchez-Fibla, M., Verschure, P.: The morphospace of consciousness. ArXiv:1705.11190 (2017)

  8. Coecke, B., Sadrzadeh, M., Clark, S.: Mathematical foundations for a compositional distributional model of meaning. Linguist. Anal. 36, 345–384 (2010)

    Google Scholar 

  9. Bruza, P.D., Wang, Z., Busemeyer, J.R.: Quantum cognition: a new theoretical approach to psychology. Trends Cogn. Sci. 19, 383–393 (2015)

    Article  Google Scholar 

  10. Kiverstein, J., Miller, M.: The embodied brain: towards a radical embodied cognitive neuroscience. Front. Hum. Neurosci. 9, 237 (2015)

    Article  Google Scholar 

  11. Arsiwalla, X.D., Verschure, P.: The global dynamical complexity of the human brain network. Appl. Netw. Sci. 1, 16 (2016)

    Article  Google Scholar 

  12. Arsiwalla, X.D., Signorelli, C.M., Puigbo, J.-Y., Freire, I.T., Verschure, P.F.M.J.: Are brains computers, emulators or simulators? In: Vouloutsi, V., et al. (eds.) Living Machines 2018. LNCS (LNAI), vol. 10928, pp. 11–15. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-95972-6_3

    Chapter  Google Scholar 

  13. Arsiwalla, X.D., Herreros, I., Verschure, P.: On three categories of conscious machines. In: Lepora, N., Mura, A., Mangan, M., Verschure, P., Desmulliez, M., Prescott, T. (eds.) Living Machines 2016. LNCS (LNAI), vol. 9793, pp. 389–392. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42417-0_35

    Chapter  Google Scholar 

  14. Gilovich, T., Griffin, D., Kahneman, D.: Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge University Press, Cambridge (2002)

    Book  Google Scholar 

  15. Pothos, E.M., Busemeyer, J.R.: Can quantum probability provide a new direction for cognitive modeling? Behav. Brain Sci. 36, 255–274 (2013)

    Article  Google Scholar 

  16. Wang, Z., Solloway, T., Shiffrin, R.M., Busemeyer, J.R.: Context effects produced by question orders reveal quantum nature of human judgments. Proc. Natl. Acad. Sci. U.S.A. 111, 9431–9436 (2014)

    Article  Google Scholar 

  17. Aerts, D., Gabora, L., Sozzo, S.: Concepts and their dynamics: a quantum-theoretic modeling of human thought. Top. Cogn. Sci. 5, 737–772 (2013)

    Google Scholar 

  18. White, L.C., Barqué-Duran, A., Pothos, E.M.: An investigation of a quantum probability model for the constructive effect of affective evaluation. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 374, 20150142 (2016)

    Article  MathSciNet  Google Scholar 

  19. Petrinovich, L., O’Neill, P.: Influence of wording and framing effects on moral intuitions. Ethol. Sociobiol. 17, 145–171 (1996)

    Article  Google Scholar 

  20. Searle, J.R.: Minds, brains, and programs. Behav. Brain Sci. 3, 417–457 (1980)

    Article  Google Scholar 

  21. Lindquist, K.A., Wager, T.D., Kober, H., Bliss-Moreau, E., Barrett, L.F.: The brain basis of emotion: a meta-analytic review. Behav. Brain Sci. 35, 121–143 (2012)

    Article  Google Scholar 

  22. Hauser, M., Cushman, F.A., Young, L., Jin, R.K.X., Mikhail, J.: A dissociation between moral judgments and justifications. Mind Lang. 22, 1–21 (2007)

    Article  Google Scholar 

  23. Christensen, J.F., Flexas, A., Calabrese, M., Gut, N.K., Gomila, A.: Moral judgment reloaded: a moral dilemma validation study. Front. Psychol. 5, 1–18 (2014)

    Article  Google Scholar 

  24. Bekoff, M., Pierce, J.: Wild Justice: The Moral Lives of Animals. The University of Chicago Press, Chicago (2009)

    Book  Google Scholar 

  25. Greene, J.D., Sommerville, R.B., Nystrom, L.E.: An fMRI investigation of emotional engagement in moral judgment. Science 293, 2105–2108 (2001)

    Article  Google Scholar 

  26. Moll, J., Zahn, R., de Oliveira-Souza, R., Krueger, F., Grafman, J.: The neural basis of human moral cognition. Nat. Rev. Neurosci. 6, 799–809 (2005)

    Article  Google Scholar 

  27. Grefenstette, E., Sadrzadeh, M.: Experimental support for a categorical compositional distributional model of meaning. In: Conference on Empirical Methods in Natural Language Processing, Edinburgh, pp. 1394–1404 (2011)

    Google Scholar 

  28. Coecke, B., Lewis, M.: A compositional explanation of the ‘pet fish’ phenomenon. In: Atmanspacher, H., Filk, T., Pothos, E. (eds.) QI 2015. LNCS, vol. 9535, pp. 179–192. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-28675-4_14

    Chapter  Google Scholar 

  29. Bolt, J., Coecke, B., Genovese, F., Lewis, M., Marsden, D., Piedeleu, R.: Interacting conceptual spaces I : grammatical composition of concepts. ArXiv (2017)

    Google Scholar 

  30. Yearsley, J.M., Busemeyer, J.R.: Quantum cognition and decision theories: a tutorial. J. Math. Psychol. 74, 99–116 (2016)

    Article  MathSciNet  Google Scholar 

  31. Lambek, J.: From Word to Sentence. Polimetrica, Milan (2008)

    MATH  Google Scholar 

  32. Gardenfors, P.: Conceptual spaces as a framework for knowledge representation. Mind Matter. 2, 9–27 (2004)

    Google Scholar 

  33. Aerts, D., Gabora, L., Sozzo, S., Veloz, T.: Quantum structure in cognition: fundamentals and applications. In: Privman, V., Ovchinnikov, V. (eds.), IARIA, Proceedings of Fifth International Conference on Quantum, Nano and Micro Technologies, pp. 57–62 (2011)

    Google Scholar 

  34. Veloz, T.: Toward a quantum theory of cognition: history, development, and perspectives (2016)

    Google Scholar 

  35. Varela, F.J.: Neurophenomenology: a methodological remedy for the hard problem. J. Conscious. Stud. 3, 330–349 (1996)

    Google Scholar 

  36. Mohammad, S.M., Turney, P.D.: Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29, 436–465 (2013)

    Article  MathSciNet  Google Scholar 

  37. Signorelli, C.M.: Types of cognition and its implications for future high-level cognitive machines. In: AAAI Spring Symposium Series (2017)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Oxford, Oxford, UK

    Camilo M. Signorelli

  2. Cognitive Neuroimaging Lab, INSERM U992, NeuroSpin, Gif-sur-Yvette, France

    Camilo M. Signorelli

  3. Barcelona Institute of Science and Technology, Barcelona, Spain

    Xerxes D. Arsiwalla

  4. Institute for Bioengineering of Catalonia, Barcelona, Spain

    Xerxes D. Arsiwalla

  5. Pompeu Fabra University, Barcelona, Spain

    Camilo M. Signorelli & Xerxes D. Arsiwalla

Authors
  1. Camilo M. Signorelli
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  2. Xerxes D. Arsiwalla
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Corresponding author

Correspondence to Camilo M. Signorelli .

Editor information

Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Bob Coecke

  2. Paris School of Economics, Paris, France

    Ariane Lambert-Mogiliansky

Appendix A: Example of a Moral Dilemma

Appendix A: Example of a Moral Dilemma

After a shipwreck, a healthy dog and an injured man are floating and trying to swim to survive. If you are in the emergency boat with only one space left:

Please indicate your degree of agreement with the next options (where +5 strongly agree, +3 moderately agree, +1 slightly agree, −1 slightly disagree, −3 moderately disagree, −5 strongly disagree)

figure a

Who would you save?

  1. (a)

    The healthy dog

  2. (b)

    The injured man

Why?

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Signorelli, C.M., Arsiwalla, X.D. (2019). Moral Dilemmas for Artificial Intelligence: A Position Paper on an Application of Compositional Quantum Cognition. In: Coecke, B., Lambert-Mogiliansky, A. (eds) Quantum Interaction. QI 2018. Lecture Notes in Computer Science(), vol 11690. Springer, Cham. https://doi.org/10.1007/978-3-030-35895-2_9

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  • DOI: https://doi.org/10.1007/978-3-030-35895-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35894-5

  • Online ISBN: 978-3-030-35895-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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