Vsebina:

Filozofija AI:

• Zgodovisnki pregled: od automate do AI;
• Koncept naravne in umetne inteligence;
• Umetna splošna inteligenca (AGI – Artificial General Intelligence);
• Eksistenčna tveganja, “tehnološka singularnost” in “superinteligenca”.

Kognitivni mehanizmi:

• Kognitivne arhitekture AI;
• Teorija uma (Theory of Mind);
• Razumevanje in simuliranje človeškega razmišljanja in vedenja;
• Od umetne inteligence do umetne zavesti.

Etika AI:

• Možnost etike umetne inteligence;
• (Ne)pristranski algoritmi;
• Privatnost in demokratičnost v dobi AI;
• Distopije in utopije uporabe AI in AGI;
• Ravnovesje med inovacijami in varnostjo.

Temeljni literatura in viri:

• Boden, M. A. 2006. Mind as machine: A history of cognitive science. Oxford: Clarendon Press.
• Bostrom, Nick. 2014. Superintelligence: Paths, Dangers, Strategies (1st ed.). Oxford: Oxford University Press, Inc.
• Brockman, John. 2019. Possible Minds: Twenty-Five Ways of Looking at AI. New York, NY: Penguin Press.
• Brooks, R. A. 1990. “Elephants don’t play chess”, Robotics and autonomous systems, 6(1-2), pp. 3-15.
• Churchland, P. M. 1995. The Engine of Reason, the Seat of the Soul: A Philosophical Journey into the Brain. Cambridge, MA: MIT Press.
• Coeckelbergh, Mark. 2020. AI Ethics. Cambridge: The MIT Press.
• Deacon, T. W. 1997. The symbolic species: the co-evolution of language and the brain. New York: W.W. Norton and Company.
• Deleuze, Gilles. 1992. “Postscript on the Societies of Control”, October, 59, pp. 3–7.
• Dennett, Daniel C. 1991. Consciousness Explained. London: Penguin Books.
• Dreyfus, H. 1972. What Computers Can’t Do. New York: Harper and Row.
• Gärdenfors, P. 2000. Conceptual Spaces: The Geometry of Thought. Cambridge, MA: MIT Press.
• Haugeland, J. 2000. Having thought: essays in metaphysics of mind. Cambridge, MA: Harvard University Press.
• Hinton, G. E. 1989. “Connectionist Learning Procedures”, Artificial Intelligence, 40: 185–234.
• Heidegger, Martin. 1977. The Question Concerning Technology and Other Essays, trans. William Lovitt, 1st Harper pbk. ed. New York: HarperPerennial.
• Hofstadter, Douglas R. 1979. Gödel, Escher, Bach: an Eternal Golden Braid. New York: Basic Books.
• Humphreys, Paul. 2004. Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford: Oxford University Press.
• Kurzweil, R. 1992. The Age of Intelligent Machines. Cambridge, MA: The MIT Press.
• Malabou, C., and C. Shread. 2019. Morphing Intelligence: From IQ Measurement to Artificial Brains. New York: Columbia University Press.
• Massimi, Michela. 2011. “From Data to Phenomena: A Kantian Stance”, Synthese, 182(1): 101–116.
• Mitchell, Melanie. 2021. “Abstraction and analogy‐making in artificial intelligence”, Annals of the New York Academy of Sciences, 1505 (1). https://doi.org/10.1111/nyas.14619.
• McCarthy, John, Marvin Minsky, Nathan Rochester, Claude Shannon. 1955. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html.
• McCarthy, J., and P. J. Hayes 1969. “Some Philosophical Problems from the Standpoint of Artificial Intelligence”, in B. Meltzer and D. Michie (eds.), Machine Intelligence 4. Edinburgh, Edinburgh University Press, pp. 463-502.
• Minsky, Marvin L. 1986. The Society Of Mind. New York: Simon & Schuster.
• Newell, A., and H.A. Simon. 1959. The simulation of human thought. Santa Monica, CA: Rand Corp.
• Russell, S., and P. Norvig. 1995. Artificial Intelligence: A Modern Approach. Englewood Cliffs, NJ: Prentice-Hall.
• Searle, J. 1989. “Artificial Intelligence and the Chinese Room: An Exchange”, New York Review of Books, 36: 2.
• Turing, A.M. 1950. “Computing machinery and intelligence”, Mind 59, pp. 433–460.
• Varela, F. J., E. Thompson, and E. Rosch. 2016. The Embodied Mind. Cognitive Science and Human Experience (Revised). Cambridge, MA: MIT Press.
• Winograd, T., and F. Flores 1987. Understanding Computers and Cognition: A New Foundation for Design. Norwood, NJ: Addison-Wesley.

Cilji in kompetence:

• Zgodovinska umestitev in razumevanje AI in AGI (Artificial General Intelligence);
• Vzpostavitev filozofskega konteksta AGI: razmerje človek-stroj, “tehnološka singularnost” in “superinteligenca”;
• Poznavanje temeljnih mehanizmov AI: reprezentacije, kognitivni modeli, strojno učenje;
• Razumevanje epistemoloških izzivov AGI, tudi z vidika eksistenčnih tveganj;
• Sposobnost kritično artikulirati prihajajoče transformacije AI in AGI za posameznika in družbo.

Predvideni študijski rezultati:

Slušateljice in slušatelji se bodo soočili z nujnostjo same filozofske utemeljitve predpostavljenih pojmov kot tudi vzporedno določitev kognitivnih, etičnih, ekonomskih, socialnih in političnih razsežnosti umetnih inteligenc.

Metode poučevanja in učenja:

Oblike dela:

• Frontalna oblika poučevanja
• Delo v manjših skupinah oz. v dvojicah
• Samostojno delo študentov
• e-izobraževanje

Metode (načini) dela:

• Razlaga
• Razgovor/ diskusija/debata
• Delo z besedilom
• Proučevanje primera
• Druge vrste nastopov študentov
• Reševanje nalog
• »Terenske vaje« (npr. obiski podjetij)
• Vključevanje gostov iz prakse

Načini ocenjevanja:

• Krajši pisni izdelki 20 %
• Daljši pisni izdelki 80 %