Hostname: page-component-76fb5796d-9pm4c Total loading time: 0 Render date: 2024-04-25T16:37:28.031Z Has data issue: false hasContentIssue false
  • English
  • Français

Digital life, a theory of minds, and mapping human and machine cultural universals

Published online by Cambridge University Press:  28 May 2020

Kevin B. Clark Open the ORCID record for Kevin B. Clark [Opens in a new window]
Kevin B. Clark*
Affiliation:
Research and Development Service, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA90073 Felidae Conservation Fund, Mill Valley, CA94941 Campus Champions, Extreme Science and Engineering Discovery Environment (XSEDE), National Center for Supercomputing Applications, University of Illinois at Urbana–Champaign, Urbana, IL61801 Expert Network, Penn Center for Innovation, University of Pennsylvania, Philadelphia, PA19104 Virus Focus Group, NASA Astrobiology Institute, NASA Ames Research Center, Moffett Field, CA 94035. kbclarkphd@yahoo.com www.linkedin.com/pub/kevin-clark/58/67/19a
Get access Rights & Permissions [Opens in a new window]

Abstract

Emerging cybertechnologies, such as social digibots, bend epistemological conventions of life and culture already complicated by human and animal relationships. Virtually-augmented niches of machines and organic life promise new free-energy-governed selection of intelligent digital life. These provocative eco-evolutionary contexts demand a theory of (natural and artificial) minds to characterize and validate the immersive social phenomena universally-shaping cultural affordances.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 43 , 2020 , e98
Check for updates
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Arbib, M. A. & Fellous, J. M. (2004) Emotions: From brain to robot. Trends in Cognitive Science 8(12):554–61.CrossRefGoogle Scholar
Asada, M (2015) Development of artificial empathy. Neuroscience Research 90:41–50.CrossRefGoogle ScholarPubMed
Bostrom, N. (2014) Superintelligence: Paths, dangers, strategies. Oxford: Oxford University Press. ISBN 978-0199678112.Google Scholar
Briegel, H. J. (2012) On creative machines and the physical origins of freedom. Scientific Reports 2:522.CrossRefGoogle ScholarPubMed
Cardon, A. (2006) Artificial consciousness, artificial emotions, and autonomous robots. Cognitive Processes 7(4):245–67.CrossRefGoogle ScholarPubMed
Chew, Y. H., Wenden, B., Flis, A., Mengin, V., Taylor, J., Davey, C. L., Tindal, C., Thomas, H., Ougham, H. J., de Reffye, P., Stitt, M., Williams, M., Muetzelfeldt, R., Halliday, K. J. & Millar, A. J. (2014) Multiscale digital Arabidopsis predicts individual organ and whole-organism growth. Proceedings of the National Academy of Science of the USA 111(39):E4127–36.CrossRefGoogle ScholarPubMed
Clark, K. B. (2012) A statistical mechanics definition of insight. In Computational intelligence, ed. Floares, A. G., pp. 139–62. Nova Science. ISBN 9781620819012.Google Scholar
Clark, K. B. (2015) Insight and analysis problem solving in microbes to machines. Progress in Biophysics and Molecular Biology 119:183–93.CrossRefGoogle ScholarPubMed
Clark, K. B. (2017) The humanness of artificial nonnormative personalities. Behavioral and Brain Sciences 40:e259.CrossRefGoogle Scholar
Clark, K. B. (2019) Unpredictable homeodynamic and ambient constraints on irrational decision making of aneural and neural foragers. Behavioral and Brain Sciences 42:e40.CrossRefGoogle ScholarPubMed
Clark, K. B. (in press a) Humanizing social digibots for personalized mobile health applications. In Artificial intelligence in precision health, ed. Barh, D.. Elsevier.Google Scholar
Davies, J. (2016) Program good ethics into artificial intelligence. Nature 538(7625):291. doi:10.1038/538291a.Google ScholarPubMed
Derex, M. & Boyd, R. (2015) The foundations of the human cultural niche. Nature Communications 6:8398.CrossRefGoogle ScholarPubMed
Fan, X. & Markram, H. (2019) A brief history of simulation neuroscience. Frontiers in Neuroinformatics 13:32.CrossRefGoogle ScholarPubMed
Fortuna, M. A., Zaman, L., Wagner, A. P. & Ofria, C. (2013) Evolving digital ecological networks. PLoS Computational Biology 9(3):e1002928.CrossRefGoogle ScholarPubMed
Fung, P. (2015) Robots with heart. Scientific American 313(5):60–63.CrossRefGoogle ScholarPubMed
Gillings, M. R., Hibert, M. & Kemp, D. J. (2016) Information in the biosphere: Biological and digital worlds. Trends in Ecology and Evolution 31(3):180–89.CrossRefGoogle ScholarPubMed
Gödel, K. (1931) Über formal unentscheidbare Säze der Principia Mathematica und verwandter Systeme I. Monatshefte für Mathematik und Physik 38:173–98.CrossRefGoogle Scholar
Gowdy, J. & Krall, L. (2016) The economic origins of ultrasociality. Behavioral and Brain Sciences 39:e92.CrossRefGoogle ScholarPubMed
Han, M. J., Lin, C. H. & Song, K. T. (2013) Robotic emotional expression generation based on mood transition and personality model. IEEE Transactions on Cybernetics 43(4):1290–1303.CrossRefGoogle ScholarPubMed
Kaipa, K. N., Bongard, J. C. & Meltzoff, A. N. (2010) Self discovery enables robot social cognition: Are you my teacher? Neural Networks 23(8–9):1113–24.CrossRefGoogle Scholar
Lake, B. M., Ullman, T. D., Tenenbaum, J. B. & Gershman, S. J. (2018) Building machines that learn and think like people. Behavioral and Brain Sciences 40:e25.Google Scholar
Laland, K. N. & Galef, B. G., eds. (2009) The question of animal culture. Harvard University Press. ISBN 9780674031265.Google Scholar
Langton, C. G. (1990) Computation at the edge of chaos: Phase transitions and emergent computation. Physica D 42:12–37.CrossRefGoogle Scholar
Lenski, R. E., Ofria, C., Collier, T. C. & Adami, C. (1999) Genome complexity, robustness and genetic interactions in digital organisms. Nature 400(6745):661–64.CrossRefGoogle ScholarPubMed
Libin, A. & Libin, E. (2005) Cyber-anthropology: A new study on human and technological co-evolution. Studies in Health and Technology and Informatics 118:146–55.Google Scholar
Lumaca, M. & Baggio, G. (2017) Cultural transmission and evolution of melodic structure in multi-generational signaling games. Artificial Life 23(3):406–23.CrossRefGoogle ScholarPubMed
Mathews, N., Christensen, A. L., O'Grady, R., Mondada, F. & Dorigo, M. (2017) Mergeable nervous systems for robots. Nature Communications 8:439.CrossRefGoogle ScholarPubMed
McShea, D. W. (2013) Machine wanting. Studies on the History and Philosophy of Biological and Biomedical Sciences 44(4 pt B):679–87.CrossRefGoogle ScholarPubMed
Millar, A. J., Urquiza, U., Freeman, P. L., Hume, A., Plotkin, G. D., Sorokina, O., Zardilis, A. & Zielinski, T. (2019) Practical steps to digital organism models, from laboratory model species to ‘Crops in silico. Journal of Experimental Botany 70(9):2403–418.CrossRefGoogle ScholarPubMed
Parisi, D. (1997) An artificial life approach to language. Brain and Language 59(1):121–46.CrossRefGoogle Scholar
Ranjan, R., Logette, E., Marani, M., Herzog, M., Tâche, V., Scantamburlo, E., Buchillier, V. & Markram, H. (2019) A kinetic map of the homomeric voltage-gated potassium channel (Kv) family. Frontiers in Cellular Neuroscience 13:358.CrossRefGoogle ScholarPubMed
Russon, A. E., Bard, K. A. & Parker, S. T., eds. (1996) Reaching into thought: The minds of the great apes. Cambridge University Press. ISBN 0521644968.Google Scholar
Sarma, G. P., Lee, C. W., Portegys, T., Ghayoomie, V., Jacobs, T., Alicea, B., Cantarelli, M., Currie, M., Gerkin, R. C., Gingell, S., Gleeson, P., Gordon, R., Hasani, R. M., Idili, G., Khayrulin, S., Lung, D., Palyanov, A., Watts, M. & Larson, S. D. (2018) OpenWorm: Overview and recent advances in integrative biological simulation of Caenorhabditis elegans. Philosophical Transactions of the Royal Society of London B: Biological Sciences 373(1758):20170382. doi:10.1098/rstb.2017.0382.CrossRefGoogle ScholarPubMed
Thomaz, A. L. & Cakmak, M. (2013) Active social learning in humans and robots. In Social learning theory: Phylogenetic considerations across animal, plant, and microbial taxa, ed. Clark, K. B., pp. 113–28. Nova Science. ISBN 978-1-62618-268-4.Google Scholar
Wallach, W., Franklin, S. & Allen, C. (2010) A conceptual and computational model of moral decision making in human and artificial agents. Topics in Cognitive Science 2:454–85.CrossRefGoogle ScholarPubMed
Wolfram, S. (1984) Universality and complexity in cellular automata. Physica D 10:1–35.CrossRefGoogle Scholar