This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and AI researchers regarding ChatGPT’s ability to pass the Turing Test. It introduces a hierarchical categorization of the test versions, suggesting that ChatGPT approaches success in the test, albeit primarily with na?ve users. Expert users, conversely, can easily identify its limitations. The paper presents various theories of consciousness, with a particular focus on the Integrated Information Theory proposed by Tononi. This theory serves as the framework for assessing ChatGPT’s level of consciousness. Through an evaluation based on the five axioms and theorems of IIT, the study finds that ChatGPT surpasses previous AI systems in certain aspects; however, ChatGPT significantly falls short of achieving a level of consciousness, particularly when compared to biological sentient beings. The paper concludes by emphasizing the importance of recognizing ChatGPT and similar generative AI models as highly advanced and intelligent tools, yet distinctly lacking the consciousness attributes found in advanced living organisms.
References
[1]
Bubeck, S., et al. (2023) Sparks of Artificial General Intelligence: Early Experiments with GPT-4. arXiv: 2303.12712.
[2]
Blum, L. and Blum, M. (2023) A Theoretical Computer Science Perspective on Consciousness and Artificial General Intelligence. Engineering, 25, 12-16. https://doi.org/10.1016/j.eng.2023.03.010
[3]
Gonçalves, B. (2022) The Turing Test Is a Thought Experiment. Minds and Machines, 33, 1-31. https://doi.org/10.1007/s11023-022-09616-8
[4]
Floridi, L. and Chiriatti, M. (2020) GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30, 681-694. https://doi.org/10.1007/s11023-020-09548-1
[5]
Gams, M. (2001) Weak Intelligence: Through the Principle and Paradox of Multiple Knowledge. Nova Science, Huntington.
[6]
Oizumi, M., Albantakis, L. and Tononi, G. (2014) From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0. PLOS Computational Biology, 10, e1003588. https://doi.org/10.1371/journal.pcbi.1003588
[7]
Hameroff, S. and Penrose, R. (2014) Consciousness in the Universe. Physics of Life Reviews, 11, 39-78. https://doi.org/10.1016/j.plrev.2013.08.002
[8]
Crick, F. and Koch, C. (2003) A Framework for Consciousness. Nature Neuroscience, 6, 119-126. https://doi.org/10.1038/nn0203-119
[9]
Coeckelbergh, M. and Gunkel, D.J. (2023) ChatGPT: Deconstructing the Debate and Moving It Forward. AI & Society. https://doi.org/10.1007/s00146-023-01710-4
[10]
Mudrik, L., Mylopoulos, M., Negro, N. and Schurger, A. (2023) Theories of Consciousness and a Life Worth Living, Current Opinion in Behavioral Sciences, 53, Article ID: 101299. https://doi.org/10.1016/j.cobeha.2023.101299
[11]
Turing, A. (1950) Computing Machinery and Intelligence. Mind, 59, 433-460. https://doi.org/10.1093/mind/LIX.236.433
[12]
Moor, J.H. (1976) An Analysis of the Turing Test. Philosophical Studies, 30, 249-257. https://doi.org/10.1007/BF00372497
[13]
Dennett, D. C. (2004). Can Machines Think? In: Teuscher, C., Ed., Alan Turing: Life and Legacy of a Great Thinker, Springer, Berlin, 295-316. https://doi.org/10.1007/978-3-662-05642-4_12
[14]
Moor, J.H. (2001) The Status and Future of the Turing Test. Minds and Machines, 11, 77-93. https://doi.org/10.1023/A:1011218925467
[15]
Piccinini, G. (2000) Turing’s Rules for the Imitation Game. Minds and Machines, 10, 573-582. https://doi.org/10.1023/A:1011246220923
[16]
Shieber, S.M. (2007) The Turing Test as Interactive Proof. Nous, 41, 686-713. https://doi.org/10.1111/j.1468-0068.2007.00636.x
[17]
Epstein, R., Roberts, G. and Beber, G. (2009) Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer. Springer Science + Business Media, New York.
[18]
Weizenbaum, J. (1966) ELIZA—A Computer Program for the Study of Natural Language Communication between Man and Machine. Communications of the ACM, 9, 36-45. https://doi.org/10.1145/365153.365168
[19]
Epstein, R. (1992) The Quest for the Thinking Computer. AI Magazine, 13, 81.
[20]
Warwick, K. and Shah, H. (2014) Human Misidentification in Turing Tests. Journal of Experimental & Theoretical Artificial Intelligence, 27, 123-135. https://doi.org/10.1080/0952813X.2014.921734
[21]
Schweizer, P. (1998) The Truly Total Turing Test. Minds and Machines, 8, 263-272. https://doi.org/10.1023/A:1008229619541
[22]
Vardi, M.Y. (2014) Would Turing have Passed the Turing Test? Communications of the ACM, 57, 5. https://doi.org/10.1145/2643596
[23]
Nov, O., Singh, N. and Mann, D. (2023) Putting ChatGPT’s Medical Advice to the (Turing) Test (Preprint). JMIR medical education, 9, e46939. https://doi.org/10.2196/46939
[24]
Graham-Cumming, J. (2009) The Real Turing Test. New Scientist, 203, 24-25. https://doi.org/10.1016/S0262-4079(09)62402-7
[25]
Saygin, A.P., Cicekli, I. and Akman, V. (2000) Turing Test: 50 Years Later. Minds and Machines, 10, 463-518. https://doi.org/10.1023/A:1011288000451
[26]
Shieber, S.M. (1994) Lessons from a Restricted Turing Test. Communications of the ACM, 37, 70-78. https://doi.org/10.1145/175208.175217
[27]
Traiger, S. (2003) Making the Right Identification in the Turing Test. Studies in Cognitive Systems, 30, 99-110. https://doi.org/10.1007/978-94-010-0105-2_4
[28]
Bringsjord, S., Bello, P. and Ferrucci, D. (2001) Creativity, the Turing Test, and the (Better) Lovelace Test. Minds and Machines, 11, 3-27. https://doi.org/10.1023/A:1011206622741
[29]
Avraham, G., Nisky, I., Fernandes, H.L., Acuna, D.E., Kording, K.P., Loeb, G.E. and Karniel, A. (2012) Toward Perceiving Robots as Humans: Three Handshake Models Face the Turing-Like Handshake Test. IEEE Transactions on Haptics, 5, 196-207. https://doi.org/10.1109/TOH.2012.16
[30]
Harnad, S. (2000) Minds, Machines and Turing. Journal of Logic, Language, and Information, 9, 425-445. https://doi.org/10.1023/A:1008315308862
[31]
Tononi, G. (2008) Consciousness as Integrated Information: A Provisional Manifesto. Biological Bulletin, 215, 216-242. https://doi.org/10.2307/25470707
[32]
Browning, J. (2023) Personhood and AI: Why Large Language Models Don’t Understand Us. AI & Society. https://doi.org/10.1007/s00146-023-01724-y
[33]
Agüera y Arcas, B. (2022) Do Large Language Models Understand Us? Daedalus, 151, 183-197. https://doi.org/10.1162/daed_a_01909
[34]
Yang, X., Li, Y., Zhang, X., Chen, H. and Cheng, W. (2023) Exploring the Limits of ChatGPT for Query or Aspect-Based Text Summarization. arXiv: 2302.0808.
[35]
Lozić, E. and Štular, B. (2023) Fluent but Not Factual: A Comparative Analysis of ChatGPT and Other AI Chatbots’ Proficiency and Originality in Scientific Writing for Humanities. Future Internet, 15, Article 336. https://doi.org/10.3390/fi15100336
[36]
Kauf, C., et al., (2023) Event Knowledge in Large Language Models: The Gap between the Impossible and the Unlikely. Cognitive Science, 47, e13386. https://doi.org/10.1111/cogs.13386
[37]
Trott, S., Jones, C., Chang, T., Michaelov, J. and Bergen, B. (2023) Do large Language Models Know What Humans Know? Cognitive Science, 47, e13309. https://doi.org/10.1111/cogs.13309
[38]
Kocoń, J., et al. (2023) ChatGPT: Jack of All Trades, Master of None. Information Fusion, 99, Article ID: 101861. https://doi.org/10.1016/j.inffus.2023.101861
[39]
Moon, K. (2019) Exclusion and Underdetermined Qualia. Entropy, 21, Article 405. https://doi.org/10.3390/e21040405
[40]
Tononi, G., Boly, M., Massimini, M. and Koch, C. (2016) Integrated Information Theory: From Consciousness to Its Physical Substrate. Nature Reviews Neuroscience, 17, 450-461. https://doi.org/10.1038/nrn.2016.44
[41]
Penrose, R. (1994) Shadows of the Mind: A Search for the Missing Science of Consciousness. Oxford University Press, Oxford.
[42]
Koch, C. and Crick, F. (2001) The Zombie within. Nature, 411, 893. https://doi.org/10.1038/35082161
[43]
Bianchini, M. and Scarselli, F. (2014) On the Complexity of Neural Network Classifiers: A Comparison between Shallow and Deep Architectures. IEEE Transactions on Neural Networks and Learning Systems, 25, 1553-1565. https://doi.org/10.1109/TNNLS.2013.2293637
[44]
Gams, M. (2001) Cognitive Systems and Knowledge Engineering. IEEE Intelligent Systems, 16, 34-41.
[45]
Dunlop, C.E.M., Gams, M., Paprzycki, M. and Wu, X. (1997) Mind versus Computer: Were Dreyfus and Winograd Right? (Frontiers in Artificial Intelligence and Applications, Vol. 43). IOS Press. ISBN 90-5199-357-9. Minds and Machines, 10, 289-296. https://doi.org/10.1023/A:1008361713173
[46]
Descartes, R. (2008) Meditations on First Philosophy. Oxford University Press, London.
[47]
Britannica, T. (2020) Panpsychism. Encyclopedia Britannica. https://www.britannica.com/topic/panpsychism
[48]
Baars, B.J. (1988) A Cognitive Theory of Consciousness. Cambridge University Press, New York.
[49]
Chalmers, D.J. (1995) Facing up to the Problem of Consciousness. Journal of Consciousness Studies, 2, 200-219.
[50]
Bennett, M.T. (2023) Can Machines Be Self-Aware? New Research Explains How This Could Happen. Singularity Hub. https://singularityhub.com/2023/05/05/can-machines-be-self-aware-new-research-explains-how-this-could-happen/
[51]
Chalmers, D.J. (2023) Could a Large Language Model Be Conscious? arXiv: 2303.07103.
