Two methods of information processing in deep neural networks and features of systems of intelligence. An attempt of testing and comparison
Journal cover Człowiek i Społeczeństwo, volume 58, year 2024
PDF (Język Polski)

Keywords

mortal computing
immortal computing
GAIA tests
AI systems
model of world tests

How to Cite

Sołoducha, K. (2025). Two methods of information processing in deep neural networks and features of systems of intelligence. An attempt of testing and comparison. Człowiek I Społeczeństwo, 58, 89–107. https://doi.org/10.14746/cis.2024.58.5

Abstract

The rapid development of AI technology in recent years has resulted, among other consequences, in renewal and dominance of connectionistic way of description of cognitive activities of both humans and computational machines. This approach results in new possibilities to compare the performance of digital AI-type computational artefacts with information processing systems of biological and evolutionary origin. The aim of this paper is to show how consequences of this approach towards the problem of computational intelligence look like. The second goal of presented research is to test the thesis of the possible superiority of systems described as immortal computing type over systems presented as mortal computing type.

https://doi.org/10.14746/cis.2024.58.5
PDF (Język Polski)

References

Bolter, D. (1990). Człowiek Turinga. Warszawa: PIW.

Brooks, R.A. (1991). Intelligence without Representation. Artificial Intelligence, 47, 139–159. DOI: https://doi.org/10.1016/0004-3702(91)90053-M

Christian, B. (2020). The Alignment Problem: Machine Learning and Human Values. New York: W. W. Norton & Company.

Gunkel, D. (2022). Person, Thing, Robot: A Moral and Legal Ontology for the 21st Century and Beyond. Boston: MIT Press. DOI: https://doi.org/10.7551/mitpress/14983.001.0001

Hinton, G. (2023). The Forward-Forward Algorithm: Some Preliminary Investigations. https://arxiv.org/abs/2212.13345

Jackson, R., Williams, T. (2020). On Perceived Social and Moral Agency in Natural Language Capable Robots. 2019 HRI Workshop on the Dark Side of Human-Robot Interaction: Ethical Considerations and Community Guidelines for the Field of HRI; HRI Workshop: Daegu, Korea.

Latour, B. (2005). Reassembling the Social: An Introduction to the Actor-Network Theory. Oxford: Oxford University Press. DOI: https://doi.org/10.1093/oso/9780199256044.001.0001

Maley, C. (2011). Analog and Digital, Continuous and Discrete. Philosohical Studies, 155, 117–13. DOI: https://doi.org/10.1007/s11098-010-9562-8

Malle, B.F., Scheutz, M. (2014). Moral Competence in Social Robots. Paper presented at 2014 IEEE Ethics Conference. Chicago, IL. DOI: https://doi.org/10.1109/ETHICS.2014.6893446

Marciszewski, W., Stacewicz, P. (2011). Umysł – komputer – świat. O zagadce umysłu z informatycznego punktu widzenia. Warszawa: EXIT.

Mialon, G., Fourrier, C., Swift, C., Wolf, T., LeCun, Y., Scialom, T. (2023). GAIA: A Benchmark for General AI Assistants. arXiv:2311.12983v1 [cs.CL] 21

Moor, J.H. (2006). The Nature, Importance, and Difficulty of Machine Ethics. IEEE Intelligent Systems, 21(4), 18–21. DOI: https://doi.org/10.1109/MIS.2006.80

Polak, P., Krzanowski, R. (2020). Phronetic Ethics in Social Robotics: A New Approach to Building Ethical Robots. Studies in Logic, Grammar and Rhetoric, 63 (76), 165–173. DOI: https://doi.org/10.2478/slgr-2020-0033

Primiero, G. (2016). Information in the Philosophy if Computer Science. W: L. Floridi (red.), The Routledge Handbook of Philosophy of Information (ss. 90–106). London: Routledge.

Rabiza, P. (2022). Point and Network Notions of Artificial Intelligence Agency. Proceedings 81, 18. DOI: https://doi.org/10.3390/proceedings2022081018

Sobal, V., Jyothir, S.V., Jalagam, S., Carion, N., LeCun, Y. (2022). Joint Embedding Predictive Architectures Focus On Slow Features. arXiv:2211.10831v1 [cs.LG], 1–4.

Véliz, C. (2021). Moral Zombies: Why Algorithms Are Not Moral Agents. AI & SOCIETY, 36, 487–497. DOI: https://doi.org/10.1007/s00146-021-01189-x