doi.org/10.26112/kw.2024.129.01

Bibliography

Crawford, Kate. Atlas of AI. Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press, 2021.

Dreyfus, Hubert L. What Computers Can’t Do: The Limits of Artificial Intelligence. Cambridge: The MIT Press, 1972.

Dreyfus, Hubert L. What Computers Still Can’t Do. A Critique of Artificial Reason. Cambridge: The MIT Press, 1992.

Parisi, Luciana. „AI (Artificial Intelligence)”. W: Posthuman Glossary, red. Rosi Braidotti, Maria Hlavajova. London: Bloomsbury Academic, 2019.

Turing, Alan M. „Computing machinery and intelligence”. Mind 59, 236 (1950).

doi.org/10.26112/kw.2024.129.02

This article aims to map the discourse on Artificial Intelligence (AI) in the humanities, proposing the establishment of a new research field: critical AI studies. The author explores the potential scope and implications of such studies, considering their relevance both globally and in the Polish humanities, with a particular focus on cultural studies. The analysis begins by identifying two types of AI: (1) technological, driven by developments in exact sciences; and (2) socio-cultural, which has emerged as a subject of humanistic inquiry. The text explores the philosophical foundations underpinning critical approaches to AI in its socio-cultural dimension and discusses the theoretical and methodological aspects of this burgeoning research area. It introduces three potential conceptualisations of AI – as technology, discourse and infrastructure – that each give rise to distinct research practices. The latter are illustrated through the works of Kate Crawford and Vladan Joler, who exemplify the experimental approaches in this field. The article concludes by reflecting on the implications for contemporary humanities, particularly cultural studies. Can critical AI studies enrich Polish humanities? Can the Polish insight of cultural studies offer a meaningful contribution to this field?

Key words: Artificial Intelligence (AI), engaged humanities, critical studies of Artificial Intelligence, cultural studies of technology, future of the humanities

Bibliography

Bode, Katherine, Lauren M.E. Goodlad. „Data worlds: An introduction”. Critical AI 1, 1–2 (2023). https://read.dukeupress.edu/critical-ai/article/doi/10.1215/2834703X-10734026/382463/Data-Worlds-An-Introduction.

Coeckelbergh, Mark. AI Ethics. Cambridge: The MIT Press, 2020.

Crawford, Kate. Atlas of AI. Power, Politics, and the Planetary Costs of Artificial Intelligence. New Haven: Yale University Press, 2021.

Crawford, Kate, Vladan Joler. Anatomy of an AI System. 2018. https://anatomyof.ai/.

Czapliński, Przemysław. „Sploty”. Teksty Drugie 1 (2017).

Derra, Aleksandra. „Laboratorium myślenia współczesnej humanistyki. Na marginesie tekstu Izabelli Bukraby-Rylskiej”. Kultura Współczesna 86, 2 (2015).

Dziamski, Grzegorz. Kulturoznawstwo, czyli wprowadzenie do kultury ponowoczesnej. Gdańsk: Wydawnictwo Naukowe Katedra, 2016.

Dziamski, Grzegorz. „Kulturoznawstwo – nowa dyscyplina czy nowy obszar badań?”. Człowiek i Społeczeństwo 49 (2020).

Feher, Katalin, Attila I. Katona. „Fifteen shadows of socio-cultural AI: A systematic review and future perspectives”. Futures 132 (2021). https://www.sciencedirect.com/science/article/pii/S0016328721001269.

Goodlad, Lauren M.E. „Editor’s introduction: Humanities in the loop”. Critical AI 1, 1–2 (2023). https://read.dukeupress.edu/critical-ai/article/doi/10.1215/2834703X-10734016/382460/Editor-s-Introduction-Humanities-in-the-Loop.

Krzysztofek, Kazimierz. „Człowiek – społeczeństwo – technologie. Między humanizmem a transhumanizmem i posthumanizmem”. Ethos 111, 3 (2015).

Lindgren, Simon, red., Handbook of Critical Studies of Artificial Intelligence. Northampton MA: Edward Elgar, 2023.

Pankau, Joanna. „Artywistyczne praktyki mapowania przeciw kryzysom. W stronę miejskiej potencjalności”. Przegląd Kulturoznawczy 46, 4 (2020).

Raley, Rita, Jennifer Rhee. „Critical AI: A field in formation”. American Literature 95, 2 (2023).

Zeidler-Janiszewska, Anna. „Filozoficzne zaplecze i społeczny kontekst współczesnego kulturoznawstwa”. W: Anna Zeidler-Janiszewska. Bezinteresowna ciekawość… Humanistyka, kultura, sztuka. Warszawa: Instytut Badań Literackich PAN, 2019.

doi.org/10.26112/kw.2024.129.03

This article discusses the art of Artificial Intelligence (AI) in the context of selected trends that characterise the radical avant-garde movements of 20th-century art. It shows that many of the characteristics and controversies surrounding AI art can also be found in earlier and parallel developments in avant-garde art. As a result, AI art – conceptually – does not introduce a revolutionary break in the field of art; rather, it adopts, modifies, intensifies and expands pre-existing artistic tendencies. The distinctly innovative and original nature of AI art lies primarily in its technical and media-specific aspects. In this discussion, AI is not depicted in terms of the traditional debate over AI as either a tool for artists or an autonomous creator, but it is presented as a novel artistic medium – an environment for (co-)creative collaborations – whose properties fundamentally shape the character and aesthetics of AI art. Key properties of this medium include automation, autonomy, digitality, generativity, participatory activity/interactivity, networking and grounding in databases or data sets.

Key words: Artificial Intelligence (AI) art, autonomy, authorship, agency, new media art

Bibliography

Audry, Sofian. Art in the Age of Machine Learning. Cambridge MA: The MIT Press, 2021.

Boden, Margaret A. Creativity & Art: Three Roads to Surprise. New York: Oxford University Press, 2011.

Brockman, John, red., Człowiek na rozdrożu: sztuczna inteligencja – 25 punktów widzenia. Tłum. Marcin Machnik. Gliwice: Helion, 2020.

Del Campo, Matias, Neil Leach, red., „Machine hallucinations: Architecture and artificial intelligence”. Architectural Design 3 (2022).

Figoli, Fabio A., Francesca Mattioli, Lucia Rampino. Artificial Intelligence in the Design Process: The Impact on Creativity and Team Collaboration. Milano: Franco Angeli, 2022.

Hultén K.G., Pontus. Jean Tinguely: „Méta”. London: Thames and Hudson, 1975.

Kaplan, Louis. „The telephone paintings: Hanging up Moholy”. Leonardo 26, 2 (1993).

Kluszczyński, Ryszard W. New Media Art. https://www.academia.edu/72942169/New_Media_Art.

Kluszczyński Ryszard W. „Paradygmat sztuk nowych mediów”. Kwartalnik Filmowy 85 (2014).

Lister, Martin, Jon Dovey, Seth Giddings, Ian Grant, Kieran Kelly. Nowe media. Wprowadzenie. Tłum. Agata Sadza, Marta Lorek, Katarzyna Sawicka. Kraków: Wydawnictwo UJ, 2009.

Machado, Penousal, Juan Romero, Gary Greenfield, red., Artificial Intelligence and the Arts: Computational Creativity, Artistic Behavior, and Tools for Creatives. Cham: Springer, 2021.

Sautoy du, Marcus. Kod kreatywności. Sztuka i innowacje w epoce sztucznej inteligencji. Tłum. Tadeusz Chawziuk. Warszawa: Copernicus Center Press, 2020.

Stocker, Gerfried, Markus Jandl, Andreas J. Hirsch, red., The Practice of Art and AI. Berlin: Ars Electronica, Hatje Cantz, 2021.

Trillo, Roberto A., Marek Poliks, red., Choreomata: Performance and Performativity after AI. Boca Raton FL: CRC Press, 2024.

Voigts, Eckart, Robin M. Auer, Dietmar Elflein, Sebastian Kunas, Jan Röhnert, Christoph Seelinger, red., Artificial Intelligence – Intelligent Art? Human-Machine Interaction and Creative Practice. Bielefeld: transcript, 2024.

doi.org/10.26112/kw.2024.129.04

This article explores the creative potential of machines, questioning traditional human-centred concepts of creativity. By examining historical and contemporary attempts to leverage computers in creative processes, the author reflects on the nature of creativity and dismantles cultural myths designed to uphold human-centric frameworks of thought regarding humans and their role in the world. The examples of critical AI art presented in the article highlight a model of human-technology collaboration that does not aim to eliminate the humanistic subject but rather redefines it within the interconnected complex ecologies in which it operates. The article further discusses how AI art fosters new aesthetic concepts that incorporate artificial intelligence as a medium, aiming to mirror the complexity of the contemporary reality where agency is shared with non-human beings. The relatively short but rapidly evolving history of AI art represents significant shifts in the field of art, provoking questions about creative norms and pushing audiences towards new perspectives on both seeing and making art. Generative AI systems challenge established artistic conventions and encourage a critical re-evaluation of creative potential that may ultimately expand our understanding beyond the anthropocentric lens.

Key words: AI art, artificial intelligence, creativity, computer art, posthumanism

Bibliography

Bennett, Jane. Vibrant Matter: A Political Ecology of Things. Durham: Duke University Press, 2010.

Kelomees, Raivo, Varvara Guljajeva, Oliver Laas, red., The Meaning of Creativity in the Age of AI. Tallinn: Estonian Academy of Arts, 2022.

Latour, Bruno. Splatając na nowo to, co społeczne: wprowadzenie do teorii aktora-sieci. Tłum. Aleksandra Derra, Krzysztof Abriszewski. Kraków: Universitas, 2010.

Navas, Eduardo. The Rise of Metacreativity. AI Aesthetics After Remix. London: Routledge, 2023.

Paul, Christiane. Digital Media. London: Thames & Hudson, 2008.

Rettberg, Jill W. Machine Vision. How Algorithms are Changing the Way We See The World. Cambridge: Polity Press, 2023.

Sautoy du, Marcus. Kod kreatywności. Sztuka i innowacja w epoce sztucznej inteligencji. Tłum. Tadeusz Chawziuk. Kraków: Copernicus Center Press, 2020.

Sofian, Audry. Art in the Age of Machine Learning. Cambridge: The MIT Press, 2021.

Stiegler, Bernard. The Age of Disruption: Technology and Madness in Computational Capitalism. New York: Polity Press, 2019.

Wittgenstein, Ludwig. Dociekania filozoficzne. Tłum. Bogusław Wolniewicz. Warszawa: Wydawnictwo Naukowe PWN, 2000.

Zeilinger, Martin. Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property. Lüneburg: Meson Press, 2021.

Zylinska, Joanna. AI Art. Machine Visions and Warped Dreams. London: Open Humanities Press, 2020.

doi.org/10.26112/kw.2024.129.05

This article presents a case study of the painting The Innocent Eye Test (1981) by Mark Tansey through the lens of eye-tracking technology. The study uses two eye-tracking methods: regular eye-tracking, with a device that records actual eye movement, and predictive eye tracking tools, a method based on machine learning. Notably, in predictive eye tracking, the presence of a human viewer is not required. Using Tansey’s painting, the author conducts a comparative analysis of both methods, examining cultural implications of eye-tracking that occurs without the human gaze. The article also traces the historical development of automated perception, a concept originating in early cybernetics. By studying the differences between human and machine-mediated perception, the author ponders on the validity of today’s mechanical-biological dualism that separates natural human perception from its mathematical representations.

Key words: eye-tracking research, predictive eye-tracking, machine learning, visual perception

Bibliography

Anderson, Steve. Technologies of Vision. Cambridge MA: The MIT Press, 2017.

Danto, Arthur. Mark Tansey: Visions and Revisions. New York: Abrams, 1992.

Duchowski, Andrew T. Eye Tracking Methodology. Theory and Practice. Springer-Verlag: London, 2007.

Francuz, Piotr. Imagia. W kierunku neurokognitywnej teorii obrazu. Lublin: Wydawnictwo KUL, 2013.

Gombrich, Ernst H. Art and Illusion. A Study in the Psychology of Pictorial Representation. New York: Pantheon Books, 1960.

Goodman, Nelson. Languages of Art. An Approach to a Theory of Symbols. Indianapolis: The Bobbs-Merrill, 1968.

Holmqvist, Kenneth, Marcus Nyström, Richard Andersson, Richard Dewhurst, Halszka Jarodzka, Joost van de Weijer. Eye Tracking. A comprehensive Guide to Methods and Measures. Oxford: Oxford University Press, 2011.

Pasquinelli, Matteo. The Eye of the Master: A Social History of Artificial Intelligence. London: Verso, 2023.

Pernice, Kara, Jakob Nielsen. How to Conduct Eyetracking Studies. Nielsen Norman group, 2009. https://www.nngroup.com/reports/how-to-conduct-eyetracking-studies/.

Ruskin, John. The Elements of Drawing: In Three Letters to Beginners. London: Smith, Elder & Co., 1857.

Szeliski, Richard. Computer Vision. Algorithms and Applications. Springer Nature: Cham, 2022.

Torralba, Antonio, Phillip Isola, William T. Freeman. Foundations of Computer Vision. Cambridge MA: The MIT Press, 2024.

Virilio, Paul. The Vision Machine. Tłum. Julie Rose. Bloomington: Indiana University Press, 1994.

Zylinska, Joanna. The Perception Machine. Our Photographic Future between the Eye and AI. Cambridge MA: The MIT Press, 2023.

doi.org/10.26112/kw.2024.129.06

This article examines the use of Artificial Intelligence (AI) models in synthetic video game ecologies, focusing on patterns of user interaction with non-player characters (NPCs) in Computer Role-Playing Games (CRPGs). The author integrates concepts from Timothy Morton’s ecological criticism – specifically, the notion of ‘ecology without nature’ – and insights from cognitive psychology to analyse transformations in the production and experience of user interactions with AI-enhanced game objects. Traditionally, NPCs in video games have operated on closed algorithms, which limits their responsiveness to users. However, the introduction of generative AI, particularly Large Language Models (LLMs), enables the creation of NPCs capable of dynamic and open-ended conversations. While this interaction fosters an immersive user experience, it is significantly constrained by LLM ‘hallucinations’, a phenomenon that ultimately disrupts immersion, causing a detachment from the narrative experience (‘emersion’). Additionally, the article addresses the impact of voice interfaces in NPC interactions.

Key words: synthetic ecology, Artificial Intelligence (AI), video games, interaction patterns, Large Language Models (LLMs)

Bibliography

Bennett, Jane. Vibrant Matter: A Political Ecology of Things. Durham NC: Duke University Press, 2010.

Bogost, Ian. Persuasive Games: The Expressive Power of Videogames. Cambridge MA: The MIT Press, 2010.

Deleuze, Gilles, Félix Guattari. Tysiąc plateau. Warszawa: Fundacja Nowej Kultury Bęc Zmiana, 2015.

Gibson, James J. The Ecological Approach to Visual Perception. New York: Psychology Press, 2015.

Juul, Jesper. Half-Real: Video Games between Real Rules and Fictional Worlds. Cambridge MA: The MIT Press, 2005.

Kahn, Peter, Erika Lev, Susan Perrins, Tonia Weiss, Todd Ehrlich, David Feinberg. „Human-nature interaction patterns: Constituents of a nature language for environmental sustainability”. Journal of Biourbanism 6, 1–2 (2017).

Kubiński, Piotr. Gry wideo: zarys poetyki. Kraków: Universitas, 2016.

Morton, Timothy. Dark Ecology: For a Logic of Future Coexistence. New York: Columbia University Press, 2022.

Parikka, Jussi. Insect Media: An Archeology of Animals and Technology. Minneapolis: University of Minnesota Press, 2010.

Salen Tekinbas, Katie, Eric Zimmerman. Rules of Play: Game Design Fundamentals. Cambridge MA: The MIT Press, 2004.

Sicart, Miguel. Beyond Choices: The Design of Ethical Gameplay. Cambridge MA: The MIT Press, 2013.

doi.org/10.26112/kw.2024.129.07

Zylinska, Joanna. „The ethics of AI, or how to tell better stories about technology”. W: Joanna Zylinska. AI Art: Machine Visions and Warped Dreams. London: Open Humanities Press, 2020.

Translate into Polish: Aleksandra Kosior

doi.org/10.26112/kw.2024.129.08

Zylinska, Joanna. „Why now? AI as the Anthropocene Imperative”. W: Joanna Zylinska. AI Art: Machine Visions and Warped Dreams. London: Open Humanities Press, 2020.

Translate into Polish: Sylwia Szykowna

doi.org/10.26112/kw.2024.129.09

This article explores the relationship between humans and technology – particularly Artificial Intelligence (AI) – through the lens of integrating technical intelligence with a humanistic approach. The humanisation of intelligent systems is becoming essential for the social assimilation of AI, necessitating an ethical framework to address concerns such as potential inaccuracies in AI-generated content and tendencies towards political correctness in intelligent systems. Central to these considerations is the concept of responsibility, which, on the one hand, drives a critical approach to AI products and, on the other hand, highlights the importance of building trust in AI-based systems. The latter increasingly make decisions that influence our lives, well-being and the world. The future of the human-machine relationship may hinge on the development of a ‘humantech’ perspective – a balanced approach free from ideological influence which may prove to be a crucial tool for building technology that ultimately serves humanity.

Key words: technical intelligence, humanism, responsibility, Artificial Intelligence (AI), ethics

Bibliography

Bense, Max. „Egzystencja techniczna”. W: Kultura techniki, red. Edhard Schutz. Tłum. Izabela Sellmer, Sven Sellmer. Poznań: Wydawnictwo Poznańskie, 2001.

Crawford, Kate. Atlas sztucznej inteligencji. Władza, pieniądze i środowisko naturalne. Tłum. Tadeusz Chawziuk. Kraków: Wydawnictwo UJ, 2024.

Ess, Charles. „Virtues, robots, and good lives: Who cares?”. W: Social Robotics and the Good Life. The Normative Side of Forming Emotional Bonds with Robots, red. Janina Loh, Wulf Loh. Bielefeld: transcript, 2023.

Flew, Terry. „Mediated trust, the internet and artificial intelligence. Ideas, interests, institutions and futures”. Policy & Internet 16, 2 (2024).

Floridi, Luciano. „Information ethics. On the philosophical foundation of computer ethics”. Ethics and Information Technology 1 (1999).

Fromm, Erich. Rewolucja nadziei. Ku uczłowieczonej technologii. Tłum. Halina Adamska. Poznań: Dom Wydawniczy Rebis, 1996.

Gibson, Abraham. „Digital humanities in the deepfake era”. W: Debates in the Digital Humanities 2023, red. Matthew K. Gold, Lauren F. Klein. Minneapolis: University of Minnesota Press, 2023. https://dhdebates.gc.cuny.edu/read/debates-in-the-digital-humanities-2023/section/cf75f49e-8a03-4c7e-a820-01c8c9476182#ch10.

Goode, J. Paul. „Artificial intelligence and the future of nationalism”. Nations and Nationalism 27, 2 (2021).

Mumford, Lewis. Technika a cywilizacja. Historia rozwoju maszyny i jej wpływ na cywilizację. Tłum. Ewa Danecka. Warszawa: Państwowe Wydawnictwo Naukowe, 1966.

Pee, L.G., Shan L. Pan, Lili Cui. „Artificial intelligence in healthcare robots. A social informatics study of knowledge embodiment”. Journal of the Association for Information Science and Technology 70, 4 (2019).

Sætra, Henrik Skaug. „Social robot deception and the culture of trust”. Paladyn, Journal of Behavioral Robotics 12, 1 (2021).

Schaich Borg, Jana, Vincent Conitzer, Walter Sinnott-Armstrong. Moralna AI. Czy bać się sztucznej inteligencji. Tłum. Bogumił Bieniok, Ewa L. Łokas. Warszawa: Prószyński i S-ka, 2024.

Sloterdijk, Peter. „Man and machine will fuse into one being”. New Perspectives Quarterly 36, 4 (2019).

Smith, Brian Cantwell. „Granice poprawności w komputerach”. W: Filozofia informatyki. Antologia. Tłum. Roman Murawski. Poznań: Wydawnictwo Naukowe UAM, 2014.

doi.org/10.26112/kw.2024.129.10

This article addresses the question of narratives about Artificial Intelligence (AI): What narratives about AI do we need? The author argues that current tales, frequently dominated by fear and dystopian perspectives, do not adequately represent AI’s potential to solve social problems. He advocates for new, inclusive narratives that reflect the diverse experiences and needs of different groups. In his analysis of prevailing ideas and visions – such as fear of losing control, dystopian futures and existential threats to humanity – he illustrates how such stories shape public perception of AI. In contrast, alternative narratives highlighting AI’s positive potential as a tool for social and environmental harmony and advancing social justice suggest a promising path for the development of not only AI narratives themselves but also AI-related regulations and public policies. By focusing on real, current issues with AI – such as algorithmic exclusion, discrimination and privacy concerns – we can better hold AI companies accountable for their promises of making our technology-modelled society more diverse and inclusive.

Key words: Artificial Intelligence (AI), narratives, science fiction, inclusivity

Bibliography

Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell. „On the dangers of stochastic parrots: Can language models be too big?”. W: FAccT’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. New York: Association for Computer Machinery, 2021.

Cave, Stephen, Claire Craig, Kanta Dihal, Sarah Dillon, Jessica Montgomery, Beth Singler, Lindsay Taylor. Portrayals and Perceptions of AI and Why They Matter. London: The Royal Society, 2018. https://royalsociety.org/-/media/policy/projects/ai-narratives/ai-narratives-workshop-findings.pdf.

Cave, Stephen, Kanta Dihal, Sarah Dillon, red., AI Narratives: A History of Imaginative Thinking about Intelligent Machines. Oxford: Oxford University Press, 2020.

Chubb, Jennifer, Darren Reed, Peter Cowling. „Expert views about missing AI narratives: is there an AI story crisis?”. AI & Soc 39 (2024). https://link.springer.com/article/10.1007/ s00146-022-01548-2.

Crawford, Kate. Atlas sztucznej inteligencji. Władza, pieniądze i środowisko naturalne. Tłum. Tadeusz Chawziuk. Kraków: Wydawnictwo UJ, 2024.

De Vynck, Gerrit. „Big Tech wants AI regulation. The rest of Silicon Valley is skeptical”. The Washington Post, 9 listopada 2023. https://www.washingtonpost.com/technology/2023/11/09/ai-regulation-silicon-valley-skeptics/.

Filiciak, Mirosław, Kuba Piwowar. „Narrating AI stories: selected strategies”. W: Algorithms, Artificial Intelligence and Beyond. Theorising Society and Culture of the 21st Century, red. Dariusz Brzeziński, Kamil Filipek, Kuba Piwowar, Małgorzata Winiarska-Brodowska. Routledge: London, 2024.

Gebru, Timnit, Emily M. Bender, Angelina McMillan-Major, Margaret Mitchell. „Statement from the listed authors of Stochastic Parrots on the «AI pause» letter”. Dair, 31 marca 2023. https://www.dair-institute.org/blog/letter-statement-March2023/.

Guenduez, Ali A., Tobias Mettler. „Strategically constructed narratives on artificial intelligence: What stories are told in governmental artificial intelligence policies?”. Government Information Quarterly 40, 1 (2023).

Hohendanner, Michel, Chiara Ullstein, Yosuke Buchmeier, Jens Grossklags. „Exploring the reflective space of AI narratives through speculative design in Japan and Germany”. W: GoodIT ’23: Proceedings of the 2023 ACM Conference on Information Technology for Social Good. New York: Association for Computing Machinery, 2023.

Ipsos. Global Views on A.I. in 2023. How people across the world feel about artificial intelligence and expect it will impact their life. A 31-country Global Advisor survey. Czerwiec 2023. https://www.ipsos.com/sites/default/files/ct/news/documents/2023-07/Ipsos%20Global%20AI%202023%20Report-WEB.pdf.

Mamak, Kamil. Robotics, AI and Criminal Law. Crimes Against Robots. London: Routledge, 2024.

Pause Giant AI Experiments: An Open Letter. Future of Life, 22 marca 2023. https://futureoflife.org/open-letter/pause-giant-ai-experiments/.

Sartori, Laura, Andreas Theodorou. „A sociotechnical perspective for the future of AI: narratives, inequalities, and human control”. Ethics and Information Technology 24, 4 (2022).

doi.org/10.26112/kw.2024.129.11

This article examines the evolving role and functions of history and historians in an era increasingly shaped by advanced technologies, particularly Artificial Intelligence (AI). Social media platforms and their users are beginning to assume roles traditionally assigned to professional historians in the discovery and interpretation of past events. By addressing the contemporary significance of history as an academic discipline and the place of experts in the discourse on the past, the author assesses whether historiography – and, by extension, collective memory – is transforming from humanistic phenomena to data sets, increasingly interpreted by AI. On the one hand, the increasing digitised material contributes to broader research and interpretation options, frequently enhanced by AI; on the other hand, the datafication of sources inevitably risks marginalising the role of historians and may reduce history itself to a narrative assembled by machine learning algorithms. The article considers the foundational principles of traditional historiography in the context of the digital turn in the humanities – an era marked by ‘the proliferation of digital devices and internet connectivity’. Although this shift began in the 1990s, it is the recent advancement of machine learning algorithms that most profoundly challenges the notion of history as a science. The innovative contribution of the paper lies in its integration of the humanistic and technological discourses.

Key words: history, historian, Artificial Intelligence (AI), datafication of sources, technological development

Bibliography

Burdick, Anne, Johanna Drucker, Peter Lunenfeld, Todd Presner, Jeffrey Schnapp, red., Digital Humanities. Cambridge MA: The MIT Press, 2012.

Carr, Edward H. What is History? London: Penguin Classics, 2018.

Carr, Helen, Suzannah Lipscomb, red., What is History, Now? How the Past and Present Speak to Each Other. London: Weidenfeld & Nicolson, 2021.

Evans, Richard J. In Defence of History. London: Granta Books, 2018.

Hong, Joo-Wha, Dmitri Williams. „Racism, responsibility and autonomy in HCI. Testing perceptions of an AI agent”. Computers in Human Behavior 100 (2019).

Jaillant, Lise, Arran Rees. „Applying AI to digital archives. Trust, collaboration and shared professional ethics”. Digital Scholarship in the Humanities 38, 2 (2023).

Markowski, Michał P. „Esencje i podpórki. Pamięć i zapomnienie od Platona do Google”. W: Od pamięci biodziedzicznej do postpamięci, red. Teresa Szostek, Roma Sendyka, Ryszard Nycz. Warszawa: Instytut Badań Literackich PAN, 2013.

Nichols, Tom M. The Death of Expertise. The Campaign Against Established Knowledge and Why it Matters. New York: Oxford University Press, 2017.

Radomski, Andrzej. Wprowadzenie do humanistyki cyfrowej. Lublin: Wydawnictwo UMCS, 2023.

White, Hayden. Proza historyczna. Tłum. Rafał Borysławski. Kraków: Universitas 2010.

Zuboff, Shoshana. Wiek kapitalizmu inwigilacji. Walka o przyszłość ludzkości na nowej granicy władzy. Tłum. Alicja Unterschuetz. Poznań: Wydawnictwo Zysk i S-ka, 2022.

doi.org/10.26112/kw.2024.129.12

This article focuses on Artificial Intelligence (AI) in the context of aesthetic practice, moving beyond the conventional perception of AI as merely a computational tool or programme designed to perform analytical tasks. Neither does it discuss the issue of ‘intelligence’ or learning and cognitive models. Instead, it presents AI as an entity existing in contrast to both Nature and Culture. The central premise of the text is that AI can contribute to building a common space of ‘nature-culture’ where an entirely different, ‘artificial’ form of ‘intelligence’ will emerge. Within this space, AI will operate according to a ‘smart’ and self-determined formula, capable of engaging in aesthetic practices traditionally associated with Nature and Culture. The analysis centres on the works of Marco Donnarumma, an Italian artist of the young generation, who bridges biological, natural elements with artificial, cultural forms. Recently, he has increasingly incorporated AI-based components in his works, adding a new layer to his art that prompts further theoretical exploration. This study seeks to demonstrate that AI can be perceived both as a creator and co-creator, as well as a distinct universe for exploring previously unknown forms of being.

Key words: art, aesthetics, Artificial Intelligence (AI), Marco Donnarumma

Bibliography

Audry, Sofian. Art in the Age of Machine Learning. Cambridge MA: The MIT Press, 2021.

Braidotti, Rosi. „Discontinuous becomings. Deleuze on the becoming-woman of philosophy”. Journal of the British Society for Phenomenology 24, 1 (1993). https://www.tandfonline.com/doi/abs/10.1080/00071773.1993.11644270.

Descola, Philippe. Beyond Nature and Culture. Tłum. Janet Lloyd. Chicago: The University of Chicago Press, 2014.

Donnarumma, Marco. „Against the norm: Othering and otherness in AI aesthetics”. Digital Culture & Society 8, 2 (2022). https://www.degruyter.com/document/doi/10.14361/dcs-2022-0205/html.

Donnarumma, Marco. Alia: Zu- tài. https://7c.marcodonnarumma.com/alia-zu-tai/.

Donnarumma, Marco. Amygdala. https://7c.marcodonnarumma.com/amygdala/.

Donnarumma, Marco. Corpus Nil. https://marcodonnarumma.com/works/corpus-nil/.

Donnarumma, Marco. The AI-Prostheses. https://marcodonnarumma.com/works/the-ai-prostheses/.

Lacan, Jacques. The Sinthome: The Seminar of Jacques Lacan, Book XXIII. Cambridge: Polity Press, 2018.

Viveiros de Castro, Eduardo. Cannibal Metaphysics. Minneapolis: University of Minnesota Press, 2014.

doi.org/10.26112/kw.2024.129.13

This article investigates the transformative role of Artificial Intelligence (AI) in the music industry, focusing on the complexities of copyrights and ethical implications of AI-generated music. It discusses the evolving meaning of the phrase ‘Artificial Intelligence’ in the world of music and proposes an alternative form of conceptualising AI’s performative and active presence = through alternative figurative interpretations. While AI is widely employed to tailor music experiences by analysing user data and preferences, its commercial applications often face criticism for their lack of originality and a tendency to repeat musical structures. In this article, AI is presented from a dual perspective: (1) AI as a support tool for simple engineering tasks in music production; and (2) AI as a technology with the ambition to create music in a human-like manner. However, neither approach suggests that the ‘intelligence’ touted by both enthusiastic and pessimistic perspectives on current and future AI products can approximate what we might define as true ‘musical intelligence’. Despite substantial investment and technological advancements, AI largely remains an imitative tool rather than a truly creative force, raising questions about its authentic value in the music industry.

Key words: Artificial Intelligence (AI) in music, generative music, music personalisation, music technologies, future of music

Bibliography

Bauman, Zygmunt. Dwa szkice o moralności ponowoczesnej. Warszawa: Wydawnictwo Instytut Kultury, 1994.

Benjamin, Walter. Pasaże. Tłum. Ireneusz Kania. Kraków: Wydawnictwo Literackie, 2006.

Hassell, Jon. Atmospherics. Los Angeles: Ndeya, 2021.

Klapuri, Anssi, Manuel Davy, red., Signal Processing Methods for Music Transcription. New York: Springer, 2006.

Kotler, Philip. „Atmospherics as a market tool”. Journal of Retailing 49 (1973–1974).

Lange, Rafał, red., Sztuczna Inteligencja w społeczeństwie i gospodarce. Analiza wyników ogólnopolskiego badania opinii polskich internautów. Warszawa: NASK Państwowy Instytut Badawczy, 2019.

Li, Tao, Mitsunori Ogihara, George Tzanetakis, red., Music Data Mining. CRC Press: Boca Raton, 2012.

Müller, Meinard. Fundamentals of Music Processing: Audio, Analysis, Algorithms, Applications. Cham: Springer, 2015.

Reck Miranda, Eduardo, red., Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity. Cham: Springer Nature, 2021.

Reck Miranda, Eduardo, red., Readings in Music and Artificial Intelligence. London: Routledge, 2000.