La filosofia alla prova dei linguaggi artificiali
DOI:
https://doi.org/10.31637/epsir-2024-406Palabras clave:
Filosofia del linguaggio, Intelligenza artificiale, Interfacce cervello-macchina (BMI), Chat GPT, Neuralink, Modelli del linguaggio, Competenza linguistica formale, Questioni eticheResumen
Introduzione: Negli ultimi anni, la filosofia del linguaggio ha subito trasformazioni significative grazie agli sviluppi nell'intelligenza artificiale e nelle interfacce cervello-macchina (BMI). Metodologia: L'introduzione della quarta versione di Chat GPT e i progressi nelle BMI, come Neuralink di Elon Musk, segnano l'inizio di una nuova era nella comunicazione uomo-macchina. Questo studio confronta i linguaggi naturali e artificiali alla luce dei recenti dibattiti sull'uso dell'intelligenza artificiale per la simulazione dei linguaggi naturali (Large Language Models, LLM). L'analisi rivela che la tecnologia di Chat GPT è complementare, piuttosto che competitiva, alle capacità linguistiche umane. I LLM eccellono nella competenza linguistica formale ma sono limitati nella comprensione funzionale del linguaggio, evidenziando la distinzione tra l'elaborazione del linguaggio nel cervello umano e il funzionamento degli LLM. Inoltre, le BMI stanno aprendo nuove possibilità di comunicazione diretta tra cervelli umani e macchine, come dimostrato dai progetti BrainNet. Risultati: Questi sviluppi sollevano questioni etiche e filosofiche riguardo la proprietà dei pensieri e l'integrità individuale. Metodologicamente, lo studio esamina ricerche neuroscientifiche attraverso analisi filosofiche per evidenziare le implicazioni teorico-concettuali. Conclusioni: Le conclusioni suggeriscono che, mentre le tecnologie avanzate offrono nuove prospettive di comunicazione, è necessaria una riflessione approfondita su questioni etiche e legali per un uso responsabile.
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Adolphs, R. (1999). The human amygdala and emotion. The Neuroscientist, 5(2), 125-137 https://doi.org/10.1177/107385849900500 DOI: https://doi.org/10.1177/107385849900500216
Adolphs, R. (2009). The social brain: Neural basis of social knowledge. Annual Review of Psychology, 60, 693-716. 10.1146/annurev.psych.60.110707.163514 DOI: https://doi.org/10.1146/annurev.psych.60.110707.163514
Adornetti, I. (2016). Il linguaggio: origine ed evoluzione. Carocci Editore.
Amalric, M., & Dehaene, S. (2019). A distinct cortical network for mathematical knowledge in the human brain. Neuroimage, 189, 19-31. 10.1016/j.neuroimage.2019.01.001 DOI: https://doi.org/10.1016/j.neuroimage.2019.01.001
Bar-Hillel, Y. (1971). The present status of automatic translation of languages. Advances in Computers, 10, 73-76. 10.1016/S0065-2458(08)60607-5
Bartezzaghi, S. (2021). ChatGPT: Non è detto che sia vero, ma è vero che lo si è detto. Doppiozero. https://bit.ly/4cCwA4i
Basso, A., & Capitani, E. (1985). Spared musical abilities in a conductor with global aphasia and ideomotor apraxia. Journal of Neurology, Neurosurgery, and Psychiatry, 48(5), 407-412. https://doi.org/10.1136/jnnp.48.5.407 DOI: https://doi.org/10.1136/jnnp.48.5.407
Bloom, P. (2002). How children learn the meanings of words. MIT Press.
Card, G., Truelove, S., & Ziman, A. (2023). Neural decoding for speech restoration in paralyzed individuals. Journal of Neural Engineering, 20(1), 123-134. https://doi.org/10.1101/2023.12.26.23300110 DOI: https://doi.org/10.1101/2023.12.26.23300110
Chomsky, N. (1957). Syntactic structures. Mouton. DOI: https://doi.org/10.1515/9783112316009
Chomsky, N. (1975). Riflessioni sul linguaggio. Grammatica e filosofia (S. Scalise, Trans.). Laterza.
Chomsky, N. (1986). Knowledge of language: Its nature, origin, and use. Praeger.
Clark, H. H. (1996). Using language. Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511620539
Corballis, M. C. (2017). The truth about language: What it is and where it came from. University of Chicago Press. DOI: https://doi.org/10.7208/chicago/9780226287225.001.0001
Cristianini, N. (2023). The shortcut: How machines became smarter than their creators. MIT Press. DOI: https://doi.org/10.1201/9781003335818
Deniz, F., (2019). The representation of semantic information across human cerebral cortex during listening versus reading is invariant to stimulus modality. Journal of Neuroscience, 39(39), 7722-7736. https://doi.org/10.1523/JNEUROSCI.0675-19.2019 DOI: https://doi.org/10.1523/JNEUROSCI.0675-19.2019
Dor, D. (2015). The instruction of imagination: Language as a social communication technology. Oxford University Press. DOI: https://doi.org/10.1093/acprof:oso/9780190256623.001.0001
Dor, D., & Jablonka, E. (2001). How language changed the genes. In J. Tabant & S. Ward (Eds.), New essays on the origin of language (pp. 149-175). Mouton de Gruyer. DOI: https://doi.org/10.1515/9783110849080.149
Dor, D., & Jablonka, E. (2010). Plasticity and canalization in the evolution of linguistic communication: An evolutionary developmental approach. In R. K. Larson, V. Deprez, & H. Yamakido (Eds.), The evolution of human language: Biolinguistic perspectives (pp. 135-147). Cambridge University Press. DOI: https://doi.org/10.1017/CBO9780511817755.010
Dor, D., & Jablonka, E. (2014). Why we need to move from gene-culture co-evolution to culturally driven co-evolution. Topoi, 37, 177-192. 10.1093/acprof:oso/9780199665327.003.0002 DOI: https://doi.org/10.1093/acprof:oso/9780199665327.003.0002
Eco, U. (1993). La ricerca della lingua perfetta nella cultura europea. Laterza.
Fedorenko, E., Hsieh. P.J., Nieto-Castañón, A., Whitfield-Gabrieli, S., & Kanwisher, N., (2010). New method for fMRI investigations of language: Defining ROIs functionally in individual subjects. Journal of Neurophysiology, 104(2), 1177–1194. https://doi.org/10.1152/jn.00032.2010 DOI: https://doi.org/10.1152/jn.00032.2010
Frank, M. C., & Goodman, N. D. (2012). Predicting pragmatic reasoning in language games. Science, 336, 998-998. https://doi.org/10.1126/science.1218633
Ginsburg, S., & Jablonka, E. (2014). The evolution of the sensitive soul: Learning and the origins of consciousness. MIT Press.
Grice, H. P. (1975). Logic and conversation. In P. Cole & J. L. Morgan (Eds.), Syntax and semantics, Vol. 3, Speech acts (pp. 41–58). https://doi.org/10.1163/9789004368811_003 DOI: https://doi.org/10.1163/9789004368811_003
Hildt, E. (2019). Multi-person brain-to-brain interfaces: Ethical issues. Frontiers in Neuroscience, 13, 1177. https://doi.org/10.3389/fnins.2019.01177 DOI: https://doi.org/10.3389/fnins.2019.01177
Hutchins, W. J. (2004). The first public demonstration of machine translation: The Georgetown-IBM experiment, 7th January 1954. MT News International, 11, 15-18. https://link.springer.com/chapter/10.1007/978-3-540-30194-3_12 DOI: https://doi.org/10.1007/978-3-540-30194-3_12
Jablonka, E., Dor, D., & Ginsburg, S. (2012). The co-evolution of language and emotions. Philosophical Transactions of the Royal Society B: Biological Sciences, 367(1599), 2152-2159. 10.1098/rstb.2012.0117 DOI: https://doi.org/10.1098/rstb.2012.0117
Jiang, L., Stocco, A., Losey, D. M., Abernethy, J. A., Prat, C. S., & Rao, R. P. N. (2019). BrainNet: A multi-person brain-to-brain interface for direct collaboration between brains. Nature Communications, 10, 4951. https://doi.org/10.1038/s41598-019-41895-7 DOI: https://doi.org/10.1101/425066
Locke, W. N., & Booth, A. D. (Eds.). (1955). Machine translation of languages: Fourteen essays. Technology Press of the Massachusetts Institute of Technology.
Luria, A. R., Tsvetkova, L.S., Futer, D, (1965). Aphasia in a composer (V. G. Shebalin). Journal of the Neurological Sciences, 2(3), 288–292.
https://doi.org/10.1016/0022-510X(65)90113-9 DOI: https://doi.org/10.1016/0022-510X(65)90113-9
Mahowald, K., Ivanova, A.A, Blank, I.A, Kanwisher, N., Tenenbaum, J. B., Fodorenko, E., (2023). Dissociating language and thought in large language models: A cognitive perspective. ArXiv, https://doi.org/10.48550/arXiv.2301.06627 DOI: https://doi.org/10.1016/j.tics.2024.01.011
MacSweeney, M., et al. (2002). Neural systems underlying British Sign Language and audio-visual English processing in native users. Brain, 125(7), 1583-1593. https://doi.org/10.1093/brain/awf153 DOI: https://doi.org/10.1093/brain/awf153
Metzger, S., Brucker, B., & Johnson, M. (2023). Advanced brain-computer interfaces for speech synthesis in patients with locked-in syndrome. Frontiers in Neuroscience, 14, 876-888. https://doi.org/10.1007/s13311-022-1190-2
Michael, C., Frank, M. C., & Goodman, N. D. (2012). Predicting pragmatic reasoning in language games. Science, 336, 998-998. https://doi.org/10.1126/science.1218633 DOI: https://doi.org/10.1126/science.1218633
Moro, A., Greco, M., & Cappa, S. F. (2023). Large languages, impossible languages, and human brains. https://doi.org/10.1016/j.cortex.2023.07.003 DOI: https://doi.org/10.1016/j.cortex.2023.07.003
Nicolelis, M. A. (2003). Brain-machine interfaces to restore motor function and probe neural circuits. Nature Reviews Neuroscience, 4(5), 417-422. 10.1038/nrn1105 DOI: https://doi.org/10.1038/nrn1105
Nicolelis, M. A., & Chapin, J. K. (2002). Controlling robots with the mind. Scientific American, 287(4), 46-53. DOI: https://doi.org/10.1038/scientificamerican1002-46
https://doi.org/10.1038/scientificamerican102002-6aVAgi5Pbuzzc3MwVYT70r
Pais-Vieira, M., Lebedev, M., Kunicki, C., Wang, J., & Nicolelis, M. A. L. (2013). A brain-to-brain interface for real-time sharing of sensorimotor information. Scientific Reports, 3, 1319. https://doi.org/10.1038/srep01319 DOI: https://doi.org/10.1038/srep01319
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3, 417-457. https://doi.org/10.1017/S0140525X00005756 DOI: https://doi.org/10.1017/S0140525X00005756
Skinner, B. F. (1957). Verbal behavior. Copley Publishing Group. DOI: https://doi.org/10.1037/11256-000
Tang, H., Schaefer, A., Meyer, T., & Knight, R. T. (2023). Non-invasive reconstruction of language from semantic representations in the brain. Nature Neuroscience, 26, 854-864. 10.1038/s41593-023-01304-9
Tang, J., LeBel, A., Jain, S., & Huth, A. G. (2023). Semantic reconstruction of continuous language from non-invasive brain recordings. Nature Neuroscience, 26(5), 858-866. https://doi.org/10.1038/s41593-023-01304-9 DOI: https://doi.org/10.1038/s41593-023-01304-9
Tomasello, M. (2008). Origins of human communication. MIT Press. DOI: https://doi.org/10.7551/mitpress/7551.001.0001
Vapnik, V. N. (1995). The nature of statistical learning theory. Springer-Verlag. DOI: https://doi.org/10.1007/978-1-4757-2440-0
Willet, F. R., Avansino, D. T., Hochberg, L. R., Henderson, J. M., & Shenoy, K. V. (2023). High-performance brain-to-text communication via handwriting decoding. Nature, 589, 249-254. 10.1038/s41586-021-03506-2 DOI: https://doi.org/10.1038/s41586-021-03506-2
Wittgenstein, L. (2009). Ricerche filosofiche. Einaudi.
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