428
views
0
recommends
+1 Recommend
1 collections
    0
    shares
       
      • Record: found
      • Abstract: found
      • Conference Proceedings: found
      Is Open Access

      Creative Artificial Intelligence within the Artificial Life Installation “Infranet”

      proceedings-article
      ,
      Proceedings of EVA London 2021 (EVA 2021)
      AI and the Arts: Artificial Imagination
      5th July – 9th July 2021
      Artificial intelligence, Artificial life, Data art, Computational creativity
      Bookmark

            Abstract

            The authors explore how current mainstream data-driven AI approaches can be questioned critically from a perspective of computational creativity and ecosystemic art. This centres on a critique of the future as being over-determined by the past; both from the data used, and in the questions or objectives assumed by training. The main contributions of this paper are to apply alternative creative approaches to nature-inspired artificial intelligence, and to detail some of these through their embodiment in the authors’ artwork “Infranet”. Infranet is a neuro-evolutionary art installation that exhibited at three international locations over 2018-2019. It uses geospatial data of the host city not as a training material but as a habitat for artificial life. In contrast to training-based AI systems, in Infranet there is no objective or fitness function and very little evolutionary pressure or competition. Moreover, it eschews the trend of a large and pre-specified neural network structure in favour of a population of thousands of small interacting neural networks, each with distinct structure, in a "liquid" process of continuous reorganization; resonating with some contemporary theories and models of non-conscious cognition in biological and ecological systems.

            Content

            Author and article information

            Contributors
            Conference
            July 2021
            July 2021
            : 199-206
            Affiliations
            [0001]York University

            Toronto, Canada
            [0002]OCAD University

            Toronto, Canada
            Article
            10.14236/ewic/EVA2021.34
            6c659a95-e6f1-43e2-b540-0647988a6513
            © Wakefield et al. Published by BCS Learning & Development Ltd. Proceedings of EVA London 2021, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of EVA London 2021
            EVA 2021
            London
            5th July – 9th July 2021
            Electronic Workshops in Computing (eWiC)
            AI and the Arts: Artificial Imagination
            Product
            Product Information: 1477-9358BCS Learning & Development
            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/EVA2021.34
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Artificial life,Data art,Computational creativity,Artificial intelligence

            REFERENCES

            1. , , and (2019) No free lunch theorem: A review. Approximation and optimization, pp.57-82.

            2. , and (2014) Two decades of evolutionary art using computational ecosystems and its potential for virtual worlds. Journal of Virtual Worlds Research, 7(3).

            3. (2020) CG-Art: demystifying the anthropocentric bias of artistic creativity. Connection Science, 32(4), pp.398-405.

            4. , and (2018) The biomass distribution on Earth. Proceedings of the National Academy of Sciences, 115(25), pp.6506-6511.

            5. (1998) Creative evolution. 1911. Trans. . New York: Dover.

            6. (2017) What is it like to be a robot? [Website]. https://rodneybrooks.com/what-is-it-like-to-be-a-robot (retrieved March 2021)

            7. (2019) The hundred-page machine learning book (Vol. 1). Vancouver: Andriy Burkov.

            8. , and (2009) Converging on the divergent: The history (and future) of the international joint workshops in computational creativity. AI magazine, 30(3), pp.15-15.

            9. and (2011) April. When novelty is not enough. In European Conference on the Applications of Evolutionary Computation, pp. 234-243. Springer, Berlin, Heidelberg.

            10. (1990) Bergsonism. Trans. & . Zone Books.

            11. , , , , , and (2020) Ecosystem antifragility: beyond integrity and resilience. PeerJ, 8, p.e8533.

            12. , 2006. The topology of the possible. In Understanding Change, pp. 67-84. Palgrave Macmillan, London.

            13. (2020) Unthought. University of Chicago Press.

            14. (2020) Computers do not make art, people do. Communications of the ACM, 63(5), pp.45-48.

            15. (2012) A standardised procedure for evaluating creative systems: Computational creativity evaluation based on what it is to be creative. Cognitive Computation, 4(3), pp.246-279.

            16. (2002) Investigations. Oxford University Press, USA.

            17. , and (2012) Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, 25, pp.1097-1105.

            18. and (2011) Abandoning objectives: Evolution through the search for novelty alone. Evolutionary computation, 19(2), pp.189-223.

            19. and (2013) Evolvability is inevitable: Increasing evolvability without the pressure to adapt. PloS one, 8(4), p.e62186.

            20. (2020) Creative ai through evolutionary computation. In Evolution in Action: Past, Present and Future, pp. 265-269. Springer, Cham.

            21. (2001) Sen to Chihiro no Kamikakushi (Spirited Away) , Directred by [Film], Japan, Studio Ghibli.

            22. (2011) Novelty-based multiobjectivization. In New horizons in evolutionary robotics, pp. 139-154. Springer, Berlin, Heidelberg.

            23. , and (2015) Deep neural networks are easily fooled: High confidence predictions for unrecognizable images. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 427-436.

            24. , and (2015) Innovation engines: Automated creativity and improved stochastic optimization via deep learning. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, pp. 959-966.

            25. and (2019) Statistical physics of liquid brains. Philosophical Transactions of the Royal Society B, 374(1774), p.20180376.

            26. , and (2020) AI-generated vs. Human Artworks. A Perception Bias Towards Artificial Intelligence? In Extended abstracts of the 2020 CHI conference on human factors in computing systems, pp. 1-10.

            27. , and (2019) Managing bias in AI. In Companion Proceedings of The 2019 World Wide Web Conference, pp. 539-544.

            28. and (2002) Evolving neural networks through augmenting topologies. Evolutionary computation,10(2), pp.99-127.

            29. , , , , , and (2013) Intriguing properties of neural networks. arXiv preprint arXiv:1312.6199.

            30. (2017). Neataptic. https://github.com/wagenaartje/neataptic (retrieved March 2021)

            31. and (1995) No free lunch theorems for search. Technical Report SFITR-95-02-010, Santa Fe Institute.

            32. and (2011) On the deleterious effects of a priori objectives on evolution and representation. In Proceedings of the 13th annual conference on Genetic and evolutionary computation, pp. 957-964.

            Comments

            Comment on this article