IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v65y2021ics0160791x21000282.html
   My bibliography  Save this article

The development of machine intelligence in a computational universe

Author

Listed:
  • De Luca, Gabriele

Abstract

The paper is dedicated to the study of the theoretical and technological development that occurred, in particular in the XX century, in the sector of Artificial Intelligence. According to the theoretical framework of mechanical rationalism, we study how the development of machine intelligence is a continuation, through different means, of the old process of outsourcing of cognitive activities by humans onto parts of their physical environments. Because of this process, an increasingly larger portion of the non-human environment performs perceptive and cognitive activities. From this follows that machine systems, not necessarily humans anymore, are the components of the physical environment that perform measurements on the universe of which the humans are also components. We suggest that the scientific discussion on the topic of AI development could be framed in the context of a more general phenomenon of an increase in the computational and perceptual capabilities of the physical universe, as opposed to a merely human and technological problem. This is because, ever so slightly, humans are being removed from the cognitive processes of technological systems they created, which continue to perceive and think autonomously. The act of machine cognition, or rather, of machine measurements, causes an effect on the environment in which humans live, and ever more so than the human measurements. Finally, we discuss the current approach to the development of viable AI systems that aim at increasing the reciprocal intelligence of humans and machines, rather than the replacement of the former's cognitive faculties by the latter.

Suggested Citation

  • De Luca, Gabriele, 2021. "The development of machine intelligence in a computational universe," Technology in Society, Elsevier, vol. 65(C).
    • Handle: RePEc:eee:teinso:v:65:y:2021:i:c:s0160791x21000282
    DOI: 10.1016/j.techsoc.2021.101553
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X21000282
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techsoc.2021.101553?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fleming, Lee & Sorenson, Olav, 2001. "Technology as a complex adaptive system: evidence from patent data," Research Policy, Elsevier, vol. 30(7), pages 1019-1039, August.
    2. James P. Crutchfield, 1998. "Dynamical Embodiments of Computation in Cognitive Processes," Working Papers 98-02-016, Santa Fe Institute.
    3. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    4. Mogoutov, Andrei & Kahane, Bernard, 2007. "Data search strategy for science and technology emergence: A scalable and evolutionary query for nanotechnology tracking," Research Policy, Elsevier, vol. 36(6), pages 893-903, July.
    5. Burmaoglu, Serhat & Sartenaer, Olivier & Porter, Alan, 2019. "Conceptual definition of technology emergence: A long journey from philosophy of science to science policy," Technology in Society, Elsevier, vol. 59(C).
    6. Taalbi, Josef, 2020. "Evolution and structure of technological systems - An innovation output network," Research Policy, Elsevier, vol. 49(8).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ahmad Barirani & Bruno Agard & Catherine Beaudry, 2013. "Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1111-1136, March.
    2. Leila Tahmooresnejad & Catherine Beaudry & Andrea Schiffauerova, 2015. "The role of public funding in nanotechnology scientific production: Where Canada stands in comparison to the United States," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 753-787, January.
    3. Parraguez, Pedro & Škec, Stanko & e Carmo, Duarte Oliveira & Maier, Anja, 2020. "Quantifying technological change as a combinatorial process," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    4. Tohru Yoshioka-Kobayashi & Tomofumi Miyanoshita & Daisuke Kanama, 2020. "Revisiting incremental product innovations in the food-manufacturing industry: an empirical study on the effect of intellectual property rights," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 9(1), pages 1-19, December.
    5. Avimanyu Datta, 2016. "Antecedents To Radical Innovations: A Longitudinal Look At Firms In The Information Technology Industry By Aggregation Of Patents," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 20(07), pages 1-31, October.
    6. Coccia, Mario & Wang, Lili, 2015. "Path-breaking directions of nanotechnology-based chemotherapy and molecular cancer therapy," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 155-169.
    7. Boeker, Warren & Howard, Michael D. & Basu, Sandip & Sahaym, Arvin, 2021. "Interpersonal relationships, digital technologies, and innovation in entrepreneurial ventures," Journal of Business Research, Elsevier, vol. 125(C), pages 495-507.
    8. Orsatti, Gianluca & Pezzoni, Michele & Quatraro, Francesco, 2017. "Where Do Green Technologies Come From? Inventor Teams’ Recombinant Capabilities and the Creation of New Knowledge," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201711, University of Turin.
    9. Ramani, Shyama V. & Chowdhury, Nupur & Coronini, Roger & Reid, Susan, 2011. "On India's plunge into Nanotechnology: What are good ways to catch-up?," MERIT Working Papers 2011-020, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Yuchen Zhang & Wei Yang, 2022. "Breakthrough invention and problem complexity: Evidence from a quasi‐experiment," Strategic Management Journal, Wiley Blackwell, vol. 43(12), pages 2510-2544, December.
    11. Tian Heong Chan & Shi-Ying Lim, 2023. "The Emergence of Novel Product Uses: An Investigation of Exaptations in IKEA Hacks," Management Science, INFORMS, vol. 69(5), pages 2870-2892, May.
    12. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    13. Sai Yayavaram & Wei-Ru Chen, 2015. "Changes in firm knowledge couplings and firm innovation performance: The moderating role of technological complexity," Strategic Management Journal, Wiley Blackwell, vol. 36(3), pages 377-396, March.
    14. Chattergoon, B. & Kerr, W.R., 2022. "Winner takes all? Tech clusters, population centers, and the spatial transformation of U.S. invention," Research Policy, Elsevier, vol. 51(2).
    15. Battke, Benedikt & Schmidt, Tobias S. & Stollenwerk, Stephan & Hoffmann, Volker H., 2016. "Internal or external spillovers—Which kind of knowledge is more likely to flow within or across technologies," Research Policy, Elsevier, vol. 45(1), pages 27-41.
    16. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "Reprint of The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(8).
    17. Barankay, Iwan & Contigiani, Andrea & Hsu, David, 2018. "Trade Secrets and Innovation: Evidence from the “Inevitable Disclosure†Doctrine," CEPR Discussion Papers 13077, C.E.P.R. Discussion Papers.
    18. Angélica Pigola & Priscila Rezende Costa, 2022. "In search of understanding about knowledge and learning on innovation performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3995-4022, July.
    19. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    20. Patrick Herron & Aashish Mehta & Cong Cao & Timothy Lenoir, 2016. "Research diversification and impact: the case of national nanoscience development," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 629-659, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:65:y:2021:i:c:s0160791x21000282. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.