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A Path to Generative Artificial Selves

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Progress in Artificial Intelligence (EPIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14116))

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Abstract

Artificial intelligence output are undeniably creative, but it has been argued that creativity should be assessed in terms of, not external products, but internal self-transformation through immersion in a creative task. Self-transformation requires a self, which we define as a bounded, self-organizing, self-preserving agent that is distinct from, and interacts with, its environment. The paper explores how self-hood, as well as self-transformation as a result of creative tasks, could be achieved in a machine using autocatalytic networks. The autocatalytic framework is ideal for modeling systems that exhibit emergent network formation and growth. The approach readily scales up, and it can analyze and detect phase transitions in vastly complex networks that have proven intractable with other approaches. Autocatalytic networks have been applied to both (1) the origin of life and the onset of biological evolution, and (2) the origin of minds sufficiently complex and integrated to participate in cultural evolution. The first entails the emergence of self-hood at the level of the soma, or body, while the second entails the emergence of self-hood at the level of a mental models of the world, or worldview; we suggest that humans possess both. We discuss the feasibility of an AI with creative agency and self-hood at the second (cognitive) level, but not the first (somatic) level.

Supported by the Natural Sciences and Engineering Research Council of Canada, grant number GR01855.

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Notes

  1. 1.

    The AI’s environment need not be the same one as our environment; it could, for example, be an artificial environment that exists in a computer.

  2. 2.

    See also [38] on the related concept of autopoiesis.

  3. 3.

    If there is an agent external to the machine that will repair it when it breaks, it may not have to exhibit RAF structure at all levels.

References

  1. Arya, N.: Baby agi: the birth of a fully autonomous ai. KDnuggets Artif. Intell. (2023)

    Google Scholar 

  2. Bach, J.: Modeling motivation in micropsi 2. In: Proceedings of AGI: 12th International Conferences, vol. 8, pp. 3–13. Springer, Berlin (2015)

    Google Scholar 

  3. Bach, J., Coutinho, M., Lichtinger, L.: Extending micropsi’s model of motivation and emotion for conversational agents. In: Proceedings of AGI: 12th International Conferences, vol. 12, pp. 32–43. Springer, Berlin (2019)

    Google Scholar 

  4. Baronchelli, A., Ferrer-i-Cancho, R., Pastor-Satorras, R., Chater, N., Christiansen, M.H.: Networks in cognitive science. Trends Cogn. Sci. 17, 348–360 (2013). https://doi.org/10.1016/j.tics.2013.04.010

    Article  Google Scholar 

  5. Cetinic, E., She, J.: Understanding and creating art with ai: review and outlook. ACM Trans. Multimed. Comput. Commun. Appl. (TOMM) 18, 1–22 (2022)

    Google Scholar 

  6. DiPaola, S., Gabora, L.: Incorporating characteristics of human creativity into an evolutionary art algorithm. Genet. Program Evolvable Mach. 10, 97–110 (2009)

    Article  Google Scholar 

  7. Friston, K.: The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. 16(1), 127–138 (2010). https://doi.org/10.1186/s13322-014-0006-2

    Article  Google Scholar 

  8. Gabora, L.: Recognizability of creative style within and across domains: preliminary studies. In: Proceedings of the Annual Meeting of the Cognitive Science Society, pp. 2350–2355. Cognitive Science Society, Austin TX (2010)

    Google Scholar 

  9. Gabora, L.: Honing theory: a complex systems framework for creativity. Nonlinear Dyn. Psychol. Life Sci. 21, 35–88 (2017)

    Google Scholar 

  10. Gabora, L., Beckage, N., Steel, M.: Modeling cognitive development with reflexively autocatalytic networks. Top. Cogn. Sci. 14, 163–188 (2022)

    Article  Google Scholar 

  11. Gabora, L., O’Connor, B., Ranjan, A.: The recognizability of individual creative styles within and across domains. Psychol. Aesthet. Creat. Arts 6, 335–346 (2012)

    Google Scholar 

  12. Gabora, L., Smith, C.: Two cognitive transitions underlying the capacity for cultural evolution. J. Anthropol. Sci. 96, 27–52 (2018). https://doi.org/10.4436/jass.96008

    Article  Google Scholar 

  13. Gabora, L., Steel, M.: Autocatalytic networks in cognition and the origin of culture. J. Theor. Biol. 431, 87–95 (2017). https://doi.org/10.1016/j.jtbi.2017.07.022

    Article  Google Scholar 

  14. Gabora, L., Steel, M.: A model of the transition to behavioral and cognitive modernity using reflexively autocatalytic networks. Proc. R. Soc. Interface 17, 20200545 (2020). https://doi.org/10.1098/rsif.2020.0545

    Article  Google Scholar 

  15. Gabora, L., Steel, M.: Modeling a cognitive transition at the origin of cultural evolution using autocatalytic networks. Cogn. Sci. 44 (2020)

    Google Scholar 

  16. Gabora, L., Steel, M.: An evolutionary process without variation and selection. J. R. Soc. Interface 18 (2021). 10.1098/rsif.2021.0334

    Google Scholar 

  17. Gabora, L., Steel, M.: From uncertainty to insight: an autocatalytic framework. In: Beghetto, R., Jaeger, G. (eds.) Uncertainty: A Catalyst for Creativity, Learning and Development, pp. 125–158. Springer, Berlin (2022)

    Chapter  Google Scholar 

  18. Goertzel, B.: Artificial selfhood: the path to true artificial intelligence. Informatica 19, 469–477 (1995)

    Google Scholar 

  19. Harnad, S.: The symbol grounding problem. Phys. D 42, 335–346 (1990)

    Article  Google Scholar 

  20. Hélie, S., Sun, R.: Incubation, insight, and creative problem solving: a unified theory and a connectionist model. Psychol. Rev. 117, 994–1024 (2010)

    Article  Google Scholar 

  21. Hordijk, W., Hein, J., Steel, M.: Autocatalytic sets and the origin of life. Entropy 12(7), 1733–1742 (2010). https://doi.org/10.3390/e12071733

    Article  Google Scholar 

  22. Hordijk, W., Kauffman, S.A., Steel, M.: Required levels of catalysis for emergence of autocatalytic sets in models of chemical reaction systems. Int. J. Mol. Sci. 12(5), 3085–3101 (2011). https://doi.org/10.3390/ijms12053085

    Article  Google Scholar 

  23. Hordijk, W., Steel, M.: Detecting autocatalytic, self-sustaining sets in chemical reaction systems. J. Theor. Biol. 227(4), 451–461 (2004). https://doi.org/10.1016/j.jtbi.2003.11.020

    Article  MathSciNet  Google Scholar 

  24. Hordijk, W., Steel, M.: Predicting template-based catalysis rates in a simple catalytic reaction model. J. Theor. Biol. 295, 132–138 (2012)

    Article  MathSciNet  Google Scholar 

  25. Hordijk, W., Steel, M.: Autocatalytic sets and boundaries. J. Syst. Chem. 6(1), 1–5 (2015). https://doi.org/10.1186/s13322-014-0006-2

    Article  Google Scholar 

  26. Hordijk, W., Steel, M.: Chasing the tail: The emergence of autocatalytic networks. Biosystems 152, 1–10 (2016). https://doi.org/10.1016/j.biosystems.2016.12.002

    Article  Google Scholar 

  27. Hordijk, W., Steel, M., Dittrich, P.: Autocatalytic sets and chemical organizations: modeling self-sustaining reaction networks at the origin of life. New J. Phys. 20, 015011 (2018)

    Article  Google Scholar 

  28. Hordijk, W., Steel, M., Kauffman, S.: Molecular diversity required for the formation of autocatalytic sets. Life 9(23), 1–14 (2019)

    Google Scholar 

  29. Horvath, A.O.: Research on the alliance: knowledge in search of a theory. Psychother. Res. 28(4), 499–516 (2017). https://doi.org/10.1080/10503307.2017.1373204

    Article  Google Scholar 

  30. Horvath, A.O., Del Re, A.C., Flückiger, C., Symonds, D.: Alliance in individual psychotherapy. Psychotherapy 48(1), 9–16 (2011). https://doi.org/10.1037/a0022186

    Article  Google Scholar 

  31. Kahneman, D.: Thinking, Fast and Slow. Macmillan, London UK (2011)

    Google Scholar 

  32. Kauffman, S., Steel, M.: The expected number of viable autocatalytic sets in chemical reaction systems. Artif. Life 1–14 (2021). arXiv:2007.10518(27)

  33. Kauffman, S.A.: Autocatalytic sets of proteins. J. Theor. Biol. 119, 1–24 (1986). https://doi.org/10.3390/ijms12053085

    Article  Google Scholar 

  34. Kauffman, S.A.: The Origins of Order. Oxford University Press (1993)

    Google Scholar 

  35. Kind, C., Ebinger-Rist, N., Wolf, S., Beutelspacher, T., Wehrberger, K.: The smile of the lion man. recent excavations in stadel cave (baden-württemberg, southwestern germany) and the restoration of the famous upper palaeolithic figurine. Quartär 61, 129–145 (2014)

    Google Scholar 

  36. Kiverstein, J., Kirchhoff, M.D., Froese, T.: The problem of meaning: the free energy principle and artificial agency. Front. Neurorobotics 16 (2022)

    Google Scholar 

  37. Lomas, J.D., Lin, A., Dikker, S., Forster, D., Lupetti, M.L., Huisman, G., Habekost, J., Beardow, C., Pandey, P. Ahmad, N., Miyapuram, K., Mullen, T., Cooper, P., Willem van der Maden, W., Cross, E.S.: Resonance as a design strategy for ai and social robots. Front. Neurorobot. 16, 850489 (2022)

    Google Scholar 

  38. Maturana, H., Varela, F.: Autopoiesis and cognition: the realization of the living. In: Cohen, R.S., Wartofsky, M.W. (eds.) Boston Studies in the Philosophy of Science, vol. 42. Reidel, Dordecht (1973)

    Google Scholar 

  39. Mossel, E., Steel, M.: Random biochemical networks and the probability of self-sustaining autocatalysis. J. Theor. Biol. 233, 327–336 (2005). https://doi.org/10.1016/j.jtbi.2004.10.011

    Article  MathSciNet  Google Scholar 

  40. Pribram, K.H.: Origins: Brain and Self-Organization. Lawrence Erlbaum, Hillsdale NJ (1994)

    Google Scholar 

  41. Runco, M., Jaeger, G.: The standard definition of creativity. Creat. Res. J. 24, 92–96 (2012)

    Article  Google Scholar 

  42. Sen, R.S., Sharma, N.: Through multiple lenses: Implicit theories of creativity among Indian children and adults. J. Creat. Beh. 45, 273–302 (2011)

    Article  Google Scholar 

  43. Sousa, F., Hordijk, W., Steel, M., Martin, W.: Autocatalytic sets in e. coli metabolism. J. Syst. Chem. 6, 4 (2015)

    Google Scholar 

  44. Steel, M.: The emergence of a self-catalyzing structure in abstract origin-of-life models. Appl. Math. Lett. 13, 91–95 (2000)

    Article  MathSciNet  Google Scholar 

  45. Steel, M., Hordijk, W., Xavier, J.C.: Autocatalytic networks in biology: structural theory and algorithms. J. R. Soc. Interface 16, (2019). https://doi.org/10.1098/rsif.2018.0808

  46. Steel, M., Xavier, J.C., Huson, D.H.: Autocatalytic networks in biology: structural theory and algorithms. J. R. Soc. Interface 17, 20200488 (2020)

    Article  Google Scholar 

  47. Stephen, D.G., Boncoddo, R.A., Magnuson, J.S., Dixon, J.: The dynamics of insight: mathematical discovery as a phase transition. Mem. Cogn. 37, 1132–1149 (2009)

    Article  Google Scholar 

  48. Steyvers, M., Tenenbaum, J.B.: The large-scale structure of semantic networks: statistical analyses and a model of semantic growth. Cogn. Sci. 29, 41–78 (2005)

    Article  Google Scholar 

  49. Tschantz, A., Seth, A.K., Buckley, C.L.: Learning action-oriented models through active inference. PLoS Comput. Biol. 16(1), e1007805 (2020). https://doi.org/10.1186/s13322-014-0006-2

    Article  Google Scholar 

  50. Varela, F., Thompson, E., Rosch, E.: The Embodied Mind. MIT Press, Cambridge MA (1991)

    Book  Google Scholar 

  51. Wang, P.: On defining artificial intelligence. J. Artif. Gen. Intel. 10, 1–37 (2019)

    Google Scholar 

  52. Xavier, J.C., Hordijk, W., Kauffman, S., Steel, M., Martin, W.F.: Autocatalytic chemical networks at the origin of metabolism. Proc. R. Soc. Lond. Ser. B: Biol. Sci. 287, 20192377 (2020)

    Google Scholar 

  53. Zhang, S., Gong, C., Wu, L., Liu, X., Zhou, M.: AutoML-GPT: automatic machine learning with GPT (2023). https://arxiv.org/abs/2305.02499

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Authors and Affiliations

  1. University of British Columbia, Kelowna, V1V 1V7, Canada

    Liane Gabora

  2. Thistledown Foundation, Ottawa, K1P 1H4, Canada

    Joscha Bach

  3. ABC Institute, Rupert-Karls-University Heidelberg, Heidelberg, Germany

    Joscha Bach

Authors
  1. Liane Gabora
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  2. Joscha Bach
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Correspondence to Liane Gabora .

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Editors and Affiliations

  1. Lucy Family Institute for Data and Society, Notre Dame, IN, USA

    Nuno Moniz

  2. GECAD, Polytechnic of Porto, Porto, Portugal

    Zita Vale

  3. GRIA—LIACC, University of Azores, Ponta Delgada, Portugal

    José Cascalho

  4. CISUC, University of Coimbra, Coimbra, Portugal

    Catarina Silva

  5. IEETA, University of Aveiro, Aveiro, Portugal

    Raquel Sebastião

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Gabora, L., Bach, J. (2023). A Path to Generative Artificial Selves. In: Moniz, N., Vale, Z., Cascalho, J., Silva, C., Sebastião, R. (eds) Progress in Artificial Intelligence. EPIA 2023. Lecture Notes in Computer Science(), vol 14116. Springer, Cham. https://doi.org/10.1007/978-3-031-49011-8_2

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  • DOI: https://doi.org/10.1007/978-3-031-49011-8_2

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