Lecturer: Cosima Prahm, Michael Bressler Fields: Computer Science, Biology, Medicine
Content
In this hands-on course, participants will explore how body and brain signals can be used as inputs for immersive interactive applications or games. After a short introduction to physiology and measurement of muscle activity (EMG), brain activity (EEG), heart activity (EKG) as well as user interface design principles and gamification, we will provide a tutorial on the Unity game engine and prefabs for signal processing and interaction design. Using provided hardware, participants will work in a maximum of 5 small teams consisting of 3-4 people to prototype applications using the Unity Game Engine to integrate physiological signals into XR/VR scenarios. Sessions will be structured as hackathon-style workshops, combining brief input lectures, supervised technical guidance, and plenty of time for experimentation. The course will conclude with team presentations in which groups pitch and demo their applications to fellow IK participants and a small jury. The emphasis is on creativity, collaboration, and gaining hands-on experience in turning physiological signals into novel forms of human–computer interaction.
Provided Hardware: – Meta Quest 3/3S (XR/VR Headset with optical hand tracking) – MyoArmband (EMG Bracelet) – Muse S (EEG Headband) – Polar Belt (EKG Chest Belt)
Description for every course Session:
Session 1: Introduction to physiological signals (EMG, EEG, EKG), user interface design and gamification. Overview of measurement devices, introduction to VR/AR/XR, Hardware setup, Unity tutorial, team formation.
Session 2: Prototyping session I – connecting devices, first experiments with devices, developing creative concepts.
Session 3: Prototyping session II – refining signal integration, debugging, testing interaction concepts.
Session 4: Prototyping session III – polishing prototypes, preparing demos and pitches.
Presentation: Final presentation (short PPT as introduction of the team and the project, followed by a demo)
Cosima Prahm graduated from the Medical University Vienna, Austria, in 2019 with a PhD in Medicine – Clinical Neuroscience. During that time, she was a research assistant at the Clinical Laboratory for Bionic Extremity Reconstruction and Rehabilitation lead by Prof. Aszmann at the Medical University in Vienna, at the Clinical Laboratory for Bionic Limb Reconstruction, Austria. At the University of Tuebingen, Germany, she was head of research of the laboratory for Hand, Plastic, Reconstructive and Burn Surgery while actively conducting research herself in both clinical projects and in the field of TechNeuroRehabilitation, where she also established the working group PlayBionic that focuses on digital health applications. She is now working at the Clinic for Hand, Replantation and Microsurgery, Charité University Medicine, and is the director of the Center for Clinical Research at the occupational trauma hospital Unfallkrankenhaus Berlin.
Affiliation: Charité – University Medicine Berlin Homepage:www.playbionic.org
Michael Bressler finished his Master’s degree in Information Technology at the Vienna University of Technology with a focus on human-computer interfaces and user interface design. After several years in the private sector, he returned to research, where he mainly focuses on computer-assisted rehabilitation, virtual and augmented reality, and serious games for health.
Affiliation: BG Klinikum Unfallkrankenhaus Berlin, Zentrum für Klinische Forschung Homepage:www.michaelbressler.at
With a focus on cybernetics and the free energy principle, this course will cover how philosophers and theoretical biologists have attempted to define the unique organisational properties of living systems, the unique difficulties of identifying invariant properties that individuate an organism over time, and how to understand the nature of mathematical models in light of these challenges.
1. Session one will begin with a brief discussion of Aristotle’s philosophy of biology and his account of animal motion, which will provide context for discussion of the cybernetic account of living systems as feedback control systems. 2. Session two will cover the Free Energy Principle as a contemporary revival of the cybernetic picture and explore some of its limitations as a ‘first principle’ for living systems. 3. Session three will introduce an alternative ‘processual’ perspective on the organism and the discuss the limitations this places on our ability to formally describe the essential features of an individual living system.
Literature
Dupré, J. A., & Nicholson, D. J. (2018). A manifesto for a processual philosophy of biology.
Dupuy, J.-P. (2009). On the origins of cognitive science: The mechanization of the mind. MIT Press.
Nave, K. (2025). A drive to survive: The free energy principle and the meaning of life. The MIT Press.
Lecturer
I am a Leverhulme Trust early career research fellow. My research focuses on developing a realist account of autonomy and agency, grounded in the uniquely metabolic existence of living systems, and upon critiquing the machine concept of the organism in light of this distinctive material instability.
Lecturer: Sarah Hayes Fields: Postdigital Inequalities, Artificial Intelligence, Sociology, Bioinformational Philosophy, Human Data Interaction, Ethics,
Content
This course, under the theme: Societies and Blurred Realities, examines postdigital inequalities , as these arise in different contexts, as a result of technologies that merge physical and virtual spaces, bioinformational data and human and artificial intelligence. Beginning with exploring our own postdigital positionalities (Hayes, 2021), where technology, language and our brains merge in our hybrid environments, we question how AI comes to reflect the values and inequities of the world in which it is created. Our changing digital identities, amid data-centric biology, are considered through research that examines the infrastructuring of educational genomics (Williamson, et. al., 2024).. Amid the uncertainty of AI mediation, our human data interactions and skills are explored to seek greater Agency, Legibility and Negotiability for postdigital inclusion of those who are marginalised (Hayes, et. al., 2023). Finally, we consider creative and innovative cross-sector partnerships that build from the ground in communities. A range of recent examples will be discussed, including citizen research and activism, collective articles, community innovation hubs and examining how universities might be centres of postdigital knowledge and collaboration, contributing to local and regional development by aligning their research with real-world policy needs.
Session 1 will cover: Postdigital positionality, where technology, language and our brains merge Session 2 will cover: Digital identity: what exactly do we mean by this in a bioinformational society? Session 3 will cover: Human Data Interaction, disadvantage, skills in the community, towards Ethtech Session 4 will cover: Creative approaches to address postdigital inequalities and regain ourselves
Literature
Costello, E. (2024). Rewild my heart: With pedagogies of love, kindness and the sun and moon. Postdigital Science and Education, 6(2), 610-626.
Hayes, S., Connor, S., Johnson, M. and Jopling, M. (2023). Human Data Interaction, Disadvantageand Skills in the Community: Enabling Cross-Sector Environments for Postdigital Inclusion. Cham: Springer.
Hayes, S. (2021). Postdigital positionality: Developing powerful inclusive narratives for learning, teaching,research and policy in Higher Education. Leiden: Brill.
Hayes, S., Jandrić, P., la Velle, L. et al. (2024) Postdigital Citizen Science and Humanities: Dialogue from the Ground. Postdigit Sci Educ 7, 188–223. https://doi.org/10.1007/s42438-024-00514-z
Jandrić, P., Ryberg, T., Knox, J., Lacković, N., Hayes, S., Suoranta, J., Smith, M., Steketee, A., Peters, M. A., McLaren, P., Ford, D. R., Asher, G., McGregor, C., Stewart, G., Williamson, B., & Gibbons, A. (2019). Postdigital dialogue.Postdigital Science and Education, 1(1), 163-189. https://doi.org/10.1007/s42438-018-0011-x
Kourkoulou, D., Tzirides, A.-O., Cope, B., & Kalantzis, M. (Eds.). (2024). Trust and Inclusion in AI-Mediated Education: Where Human Learning Meets Learning Machines. Cham: Springer. https://doi.org/10.1007/978-3-031-64487-0.
Kotouza, D. (2025). Genetics for ‘equality’? The politics of knowledge production in educational genomics. History of the Human Sciences, 09526951251314314.
Matthewman S (2011) Technology and Social Theory. Basingstoke: Palgrave Macmillan.
Pangrazio, L., & Sefton-Green, J. (2023). Digital literacies as a ‘soft power’of educational governance. In World Yearbook of Education 2024 (pp. 196-211). Routledge.
Peters, M. A., Jandrić, P., & Hayes, S. (Eds.). (2022). Bioinformational philosophy and postdigital knowledge ecologies. Cham: Springer.
Raffaghelli, J.E., Ferrarelli, M. & Rodríguez, N.L. (2025) Slowness as Postdigital Positionality in the Era of Generative AI: A Conversation. Postdigital Science and Education
Reardon, J. (2019). The postgenomic condition: Ethics, justice, and knowledge after the genome. University of Chicago Press.
Ritzer, G., Ryan, J. M., Hayes, S., Elliot, M., & Jandrić, P. (2024). Epilogue: McDonaldization and Artifcial Intelligence. In D. Kourkoulou, A.-O. Tzirides, B. Cope, & M. Kalantzis (Eds.), Trust and Inclusion in AI-mediated Education: Where Human Learning Meets Learning Machines (pp. 303-321). Cham: Springer.
Williamson, B., Kotouza, D., Pickersgill, M., & Pykett, J. (2024). Infrastructuring educational genomics: Associations, architectures, and apparatuses. Postdigital Science and Education, 6(4), 1143-1172.
Lecturer
Sarah Hayes, PFHEA, is Professor of Education & Research Lead at Bath Spa University. Her PhD was in Sociology, from Aston University, UK, and her research includes linguistic analysis of policy and examining society through a postdigital lens. Sarah wrote: ‘The Labour of Words in Higher Education’ (2019), ‘Postdigital Positionality’ (2021) and co-edited ‘Bioinformational Philosophy and Postdigital Knowledge Ecologies (2022) and the EPSRC funded Human Data Interaction, Disadvantage and Skills in the Community. She has taught Sociology, Education and Computing, and is an Associate Editor for the Springer journal: Postdigital Science and Education.
Lecturer: Charlotte Gauvry Fields: Philosophy of mind, Philosophy of Neuroscience, Ethics of AI
Content
Determining the presence of consciousness can be challenging in some cases. Consider individuals with severe brain injuries, such as comatose patients, or those with mental disorders. The question also extends to non-Human animals and even to emerging entities like brain organoids, isolated hemispheres after hemispherotomy or advanced AI systems. These entites might exhibit minimal, say borderline, consciousness. But how can we certain they are conscious at all? The question matters because, if they are conscious, they may require protection from harm. Session 1 will provide a general introduction to the philosophy of consciousness, in order to define the main concepts involved: phenomenal consciousness (p-consciousness), borderline consciousness and synthetic consciousness Session 2 will address methodological questions concerning the detection of p-consciousness providing an overview of the neuro-philosophical theories of consciousness currently available Session 3 will focus on two concrete cases of synthetic consciousness: the isolated hemisphere after hemispherotomy and brain organoids Session 4 will focus on AI-consciousness
Dr. Charlotte Gauvry received her PhD in Philosophy from the University of Paris 1 Panthéon-Sorbonne and was a postdoctoral researcher at the University of Liège (Belgium). She is currently a Teaching and Research Assistant in Philosophy at the University of Bonn (Germany). Her work focuses on the philosophy of consciousness, particularly its metaphysics (with an emphasis on representationalist and illusionism theories), borderline cases, and ethical dimensions. She has published on mental disorders (e.g. depersonalization and derealization) and brain injuries (e.g. hemispherotomy), and co-edited, with Arnaud Dewalque, Consciousness and Representation: An Introduction to Representational Theories of Mind (in French).
This course introduces the participants to the scientific study of sleep and dreams, and examines how contemporary technology can be employed to measure and to modulate the experience of sleep and dreaming.
Session 1 will provide an overview of the foundations of sleep and dreaming. Session 2 will address the question of how sleep and dreams may be measured and modified through technological means—both theoretically and practically, in the laboratory as well as in real-world contexts. Session 3 will explore more advanced topics, including interactive dreaming, targeted memory reactivation during sleep, and the recording of dreams—technologies that establish connections between waking life and the domain of sleep and dreaming. The course will conclude with a discussion on the future directions of sleep and dream research.
Literature
Zadra, A., & Stickgold, R. (2021). When brains dream: Exploring the science and mystery of sleep. W. W. Norton & Company.
Vorster, A. (2019). Warum wir schlafen. Wilhelm Heyne Verlag.
Lecturer
Dr Kristoffer Appel received his PhD in Cognitive Science from Osnabrück University, where he established the university’s sleep laboratory and conducted research at the intersection of sleep, dreaming, and technology. He later founded a non-profit institute for sleep and dream technology in Hamburg, and he is currently also a postdoctoral researcher at the Donders Institute for Brain, Cognition and Behaviour at Radboud University, Nijmegen, where he works on new approaches to sleep research, including citizen science methods.
Affiliation: Institute of Sleep and Dream Technologies, Hamburg; Donders Institute for Brain, Cognition, and Behaviour, Nijmegen Homepage:sd20.org ; dreslerlab.org
Lecturer: David Burden Fields: Artificial Intelligence, Metaverse, Embodied Intelligence, Digital Immortality
Content
Stories and comment around digital immortality seem to be increasingly common in the media, and public reaction (particularly in the West) is often very negative. But what is the true current situation, and how might things evolve in the future? This series of lectures will explore the emergence and evolution of both virtual human and metaverse technology, and how they come together in the form of embodied AI. One possibility, almost an implication of these developments is the creation of digital replicas of real human beings, as well as of synthetic personalities, and how once such entities emerge they may deliberately, or even accidentally, transcend the death of their human models, and take on a form of digital amortality. The lectures will consider both the technical possibilities and the ethical and social implications of such developments. Students will be directed to resources which will enable them to experiment with the technologies discussed, to prompt discussions and explore the future through a matrix or similar narrative game.
Lecture 1 – Conversational AI and Virtual Humans
Lecture 1 will examine at the development of Conversational AI and virtual humans, from Eliza to ChatGPT. In particular it will look at the different elements required to create the ‘mind’ and ‘body’ of a virtual human, and how Large Language Model approaches contrast with some of the more traditional approaches, and whether hybrid approaches are possible or desirable. The lecture will also discuss the current use cases for conversational AI and the challenges, particularly in terms of ethics, privacy and employment. The representation of such AIs in the media, such as in Spike Jonze’s Her will also be considered. The idea of personal replicas will be introduced and attendees will be introduced to tools that will allow them to build their own personal replica during or after the School.
Lecture 2 – The Metaverse
Lecture 2 will explore the evolution of virtual worlds and metaversal spaces, with a particular focus on social virtual worlds. Current models of virtual worlds, such as Fortnite, Robolox etc will be compared to those of almost a generation ago such as There, ActiveWorlds and Second Life. Current use cases and challenges will be considered. Different definitions of the metaverse will be discussed and ten axioms for a future metaverse considered. The lecture will also examine 7 possible futures for the concept of the Metaverse. The idea of information gardens, a memory-palace or second brain made explicit, will also be explored. Media representation of the Metaverse will also be presented, such as Vernor Vinge’s True Names, Ernest Cline’s Ready Player One, Lottie Moggach’s Kiss Me First and the Mindjammer Role-Playing Game (RPG). Attendees will be introduced to tools that will allow them to build their own information gardens during or after the School.
Lecture 3 – Embodiment
Lecture 3 will bring together the two strands of ideas and technology presented in the previous lectures by considering the role of embodiment in the development of intelligence and sentience. The lecture will examine the embodiment of AI in physical (robot/android) and virtual (avatar/robotar) forms, how they compare and their relative affordances. The virtual embodiment model will then be considered in more detail, looking at past and present examples, and future directions for the research, and even dreaming (of electric sheep?) will be considered. Media representation of embodiment, from the physical embodiment of Blade Runner and Battlestar Galactica’s Caprica prequel and the Sentience RPG to Andromeda’s Rommie and the fluid embodiment of Greg Egan’s books will be examined. Attendees will (hopefully) be introduced to tools that will allow them to create their own embodied robotars during or after the School.
Lecture 4 – Digital Amortality
Lecture 4 will push on into the future and, informed by the previous lectures, consider the question of digital amortality – is it viable (or even inevitable) and is it desirable. Digital amortality (a term coined by in Neal Stephenson in Fall; or, Dodge in Hell) is a slightly more ‘realistic’ version of digital immortality where it is accepted that true immortality may be something of a tall order, and that a more reasonable goal may be to have a control over when to end (or pause) one’s existence. Whilst a possible technical pathway will be presented, much of this session will be about the ethical and motivational issues for such developments, and particularly the different perspectives (and goals) of the person themselves and of those left behind. An argument as to why such amortality may be accidental, and inevitable will be presented, along with a consideration of the concept of a thanoverse, and the relationship between digital amortality and space exploration. There will be some live polling to gain attendee feedback on the different issues, and options, discussed, media representations (such as Black Mirror and Upload) will again be examined, and a potential personal pathway towards digital amortality presented.
Evening Session – A Matrix Game of the Future (provisional)
As an evening session a ~2 hour “matrix” game will be presented, focussed on the future development of AI, the metaverse and digital immortality. A Matrix Game is a form of structured argument. Each player takes on the role of a different stakeholder (e.g. country, organisation, pressure group, AI?) in the topic under discussion, and each turn presents an argument for undertaking one action – which can be challenged or supported by other players. A suitable adjudication method (e.g. dice, voting, probability cards) is then used to decide if the action is successful. For this game a turn may represent around 10-20 years so that the next century of human history, and of AI, metaverse and digital immortality can be examined.
Literature
Burden, D. J., Savin-Baden, M., & Bhakta, R. (2016). Covert Implementations of the Turing Test: A More Level Playing Field? In Research and Development in Intelligent Systems XXXIII: Incorporating Applications and Innovations in Intelligent Systems: Vol. XXIV 33 (pp. 195–207). Springer International Publishing.
Burden, D., & Savin-Baden, M. (2019). Virtual Humans: Today and Tomorrow. CRC Press.
Savin-Baden, M., & Burden, D. (2019). Digital immortality and virtual humans. Postdigital Science and Education, 1, 87–103.
Burden, D. J. H. (2020). Building a Digital Immortal. In M. Savin-Baden & V. Mason-Robbie (Eds.), Digital Afterlife. CRC.
Burden, D., & Savin-Baden, M. (2024). The Metaverse: A Critical Introduction. Taylor & Francis.
Lecturer
Biography: For the last 20 years David has run Daden Limited, helping organisations explore and exploit the social and commercial potential of using conversational AI and virtual worlds, delivering over 100 projects for clients across the globe. Daden were finalists in the BCS Machine Intelligence Competition, and chatbots designed by David successfully passed two covert Turing Tests in the 2010s. David spoke at the inaugural TEDxBrum on Digital Immortality, has authored over a dozen papers and book chapters, including co-authoring the books Virtual Humans, and The Metaverse:A Critical Introduction, both published by Routledge, New York. David is currently studying for a PhD on wargaming urban conflict, is an ex-Royal Signals officer, a Chartered European Engineer and is also series co-editor for Taylor & Francis on their Metaverse Series of books.
Lecturer: Benjamin Paassen Fields: Machine Learning
Content
AI systems such as image generators, language models, automatic decision making systems, and much more are widely known. But what are the underlying models and algorithms that make these systems work? How does one take data as input and automatically extract models from them? This is the subject of machine learning.
The course will provide an introduction to machine learning. The core knowledge and skills taught by the course are: – the basic recipe behind machine learning (training data, model architecture, loss function, training/optimization, and inference) – the fundamental mathematical concepts behind machine learning – example models and algorithms, from classic machine learning to neural networks – types of machine learning (supervised, unsupervised, reinforcement) – core notions for responsible machine learning, namely: interpretable models, adversarial examples, and fairness
In more detail, the course will have four sessions with the following topics:
1. Basic Concepts: Functions, learning algorithms, optimization, linear regression (as an example of a learning algorithm), regularization, probability theory, machine learning theory, how to design a ML experiment, how to read an ML paper 2. Recipes for interpretable and robust machine learning: Distance-based models, adversarial examples, and decision trees 3. Artificial neural networks and deep learning: Neural network modules, recipes for neural networks, generative models (diffusion and large language models) 4. Reinforcement learning and ethics
Each session is accompanied by a (voluntary) programming exercise in Python. Exercise sheets (and slides) can be found here: https://bpaassen.gitlab.io/Teaching.html
Literature
Literature is optional and more regarded as ‘further/complementary reading’:
Barocas, S., Hardt, M., and Narayanan, A. (2023). Fairness and Machine Learning. MIT Press. Cambridga, MA, USA. https://fairmlbook.org/
Lecturer
Benjamin Paaßen is Junior Professor for Knowledge Representation and Machine Learning at Bielefeld University and research affiliate at the Educational Technology Lab of the German Research Center for Artificial Intelligence (DFKI). Their research foci are interpretable machine learning, machine learning for education, and limitations of large language models (especially as research tools).
Lecturer: Marieke van Vugt Fields: Cognitive science/Contemplative science
Content
In this course, we will combine first- and third-person methods to explore mind-wandering, as well as meditation, which in some conceptions is a way to get to know one’s mind-wandering. We will learn about the scientific studies of mind-wandering and meditation, but also do some practice ourselves, and discussion about what we notice. Session 1 will mainly explore mind-wandering, how mind-wandering is studied in the laboratory, and involve also a first-person observation of our own mind-wandering. Session 2 will explore the content and phenomenology of mind-wandering, and how those determine its effects, for example in a psychiatric context. We will also try to change the content or phenomenology of our mind-wandering. Session 3 will shift attention more to meditation, and we will discuss the different meditation practices that have been distinguished in the scientific literature, as well as trying them out. We will also bring some attention to the role of the body in mind-wandering.
Literature
Smallwood, J., & Schooler, J. W. (2015). The science of mind wandering: Empirically navigating the stream of consciousness. Annual review of psychology, 66(1), 487-518.
van Vugt, M. K., Soepa, J., Gyaltsen, J., Gyatso, K., Lodroe, T., Aadhentsang, T., … & Mishra, S. (2023). Using the body to think: an analysis of the cognitive mechanisms underlying Thinking at the Edge and Tibetan monastic debate.
Kordeš, U., & Demšar, E. (2023). Horizons of becoming aware: Constructing a pragmatic-epistemological framework for empirical first-person research. Phenomenology and the cognitive sciences, 22(2), 339-367.
Lecturer
Marieke van Vugt received her PhD from the University of Pennsylvania. She is now an associate professor at the AI department of the University of Groningen, the Netherlands. In her lab, she tries to understand when, how and why we mind-wander, using methods from psychology, neuroscience and AI. She is also interested in the effects of contemplative practices on our mind, especially on our mind-wandering. In addition, she collaborates with Tibetan Buddhist monks on the practice of analytical meditation and monastic debate. Besides her work as an academic, she is also a classical ballet dancer with Amsterdam Amateur Ballet.
This course explores how language shapes our capacity to think and communicate about concepts that extend beyond the concrete and immediate, from everyday generalisations to complex scientific ideas. It examines how these abilities are mirrored, tested, and expanded by artificial systems such as large language models.
Participants will discuss how abstract meaning is created, shared, and adapted in human interaction, and how machines approach similar tasks in ways that can be both powerful and limited. Drawing on examples of data gathered from people and generated by language models, we will reflect on how human intuitions and artificial output can be compared and used together to reveal new insights about meaning-making.
Based on themes and research findings from the ERC project ABSTRACTION ( ERC-2021-STG-101039777), this course invites students and researchers to consider how language connects minds, data, and technologies within increasingly blended digital realities.
Literature
Basic introductory literature:
Reilly, J., Shain, C., Borghesani, V. et al. What we mean when we say semantic: Toward a multidisciplinary semantic glossary. Psychonomic Bulletin & Review (2024). https://doi.org/10.3758/s13423-024-02556-7
Barsalou Lawrence W. (2003). Abstraction in perceptual symbol systemsPhil. Trans. R. Soc. Lond. B 358 1177–1187
Bolognesi, M., Burgers, C., & Caselli, T. (2020). On abstraction: decoupling conceptual concreteness and categorical specificity. Cognitive processing, 21(3), 365–381. https://doi.org/10.1007/s10339-020-00965-9
Burgoon, E. M., Henderson, M. D., & Markman, A. B. (2013). There are many ways to see the forest for the trees: A tour guide for abstraction. Perspectives on Psychological Science, 8(5), 501–520. https://doi.org/10.1177/1745691613497964
Ilievski, F., Hammer, B., van Harmelen, F., Paassen, B., Saralajew, S., Schmid, U., Biehl, M., Bolognesi, M., Dong, X. L., Gashteovski, K., Hitzler, P., Marra, G., Minervini, P., Mundt, M., Ngomo, A.-C. N., Oltramari, A., Pasi, G., Saribatur, Z. G., Serafini, L., … Villmann, T. (2024). Aligning Generalisation Between Humans and Machines. arXiv. https://doi.org/10.48550/arXiv.2411.15626
Research findings by the ABSTRACTION research group, which will be discussed during the course:
Ravelli, A. A., & Bolognesi, M. (2024). Yet another approximation of human semantic judgments using LLMs… but with quantized local models on novel data. Italian Journal of Computational Linguistics, 10(2), 146. https://doi.org/10.17454/IJCOL102.04
Puccetti, G., Collacciani, C., Ravelli, A.A., Esuli, A., Bolognesi, M. (2025). ABRICOT – ABstRactness and Inclusiveness in COntexT: A CALAMITA Challenge. Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024). pages: 1161-1167. https://aclanthology.org/2024.clicit-1.128/
Mazzuca, C., Villani, C., Lamarra, T., Bolognesi, M., Borghi, AM (2025). Abstractness impacts conversational dynamics. Cognition (258), 106084. https://doi.org/10.1016/j.cognition.2025.106084
Rambelli, G., Chersoni, E., Collacciani, C., & Bolognesi M. (2024). Can Large Language Models Interpret Noun-Noun Compounds? A Linguistically-Motivated Study on Lexicalized and Novel Compounds. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pp: 11823–11835. https://aclanthology.org/2024.acl-long.637/
Collacciani, C., Rambelli, G., & Bolognesi, M. (2024). Quantifying Generalizations: Exploring the Divide Between Human and LLMs’ Sensitivity to Quantification. Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pp: 11811–11822. https://aclanthology.org/2024.acl-long.636/
Mazzuca, C., Villani, C., Lamarra, T., Bolognesi, M. M, & Borghi, A. (2024). Abstract Sentences elicit more Uncertainty and Curiosity than Concrete Sentences. Proceedings of the Annual Meeting of the Cognitive Science Society, 46. Retrieved from https://escholarship.org/uc/item/7cj2g289
Collacciani, C., Ravelli, A., & Bolognesi, M. (2024). Specifying Genericity through Inclusiveness and Abstractness Continuous Scales. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Pp: 15126–15136. https://aclanthology.org/2024.lrec-main.1315/
Rambelli, G. & Bolognesi, M. (2024). The Contextual Variability of English Nouns: The Impact of Categorical Specificity beyond Conceptual Concreteness. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). Pp: 15854–15860. https://aclanthology.org/2024.lrec-main.1377/
Genovese, F., Bolognesi, M. M., Di Iorio, A., & Vitali, F. (2024). The advantages of gamification for collecting linguistic data: A case study using Word Ladders. Online Journal of Communication and Media Technologies, 14(2), e202426. https://doi.org/10.30935/ojcmt/14443
Villani C, Loia A, Bolognesi MM. (2024). The semantic content of concrete, abstract, specific, and generic concepts. Language and Cognition. Published online 2024:1-28. doi:10.1017/langcog.2023.64
Bolognesi, M.M., Collacciani, C., Ferrari, A., Genovese, F., Lamarra, T., Loia, A., Rambelli, G., Ravelli, A.A., Villani, C. (preprint). Word Ladders: A Mobile Application for Semantic Data Collection. arXiv:2404.00184 [cs.CL] https://doi.org/10.48550/arXiv.2404.00184
Rambelli, G. & Bolognesi, M. (2023). Contextual Variability Depends on Categorical Specificity rather than Conceptual Concreteness: A Distributional Investigation on Italian data. Proceedings (selected papers) of IWCS 2023, Nancy, France. https://aclanthology.org/2023.iwcs-1.2
Collacciani, C., & Rambelli, G. (2023). Interpretation of Generalization in Masked Language Models: An Investigation Straddling Quantifiers and Generics. In Proceedings of the 9th Italian Conference on Computational Linguistics – CLiC-it 2023. https://ceur-ws.org/Vol-3596/paper17.pdf
Lecturer
Marianna Bolognesi is a linguist specializing in cognitive and distributional semantics at the Department of Modern Languages, Literatures and Cultures at the University of Bologna. She was a Marie S. Curie Research Fellow at the University of Amsterdam and a research associate at the University of Oxford before joining UniBo as a tenure-track researcher. In 2022 she was awarded an ERC grant for the project ABSTRACTION, which investigates how abstraction operates in thought, language, and creativity, both in humans and in artificial intelligence. She is also vice-PI and work unit coordinator of the national PRIN 2022 project WEMB, which explores how vector representations of word meaning relate to human mental representations. Her research combines psycholinguistic experiments and computational modelling in a cross-disciplinary perspective.
In this lecture series, I will discuss our lab’s research about how people (and some non-human animals) come to know what they know about the world. The world is a sea of information too vast for anyone to acquire entirely. How do people navigate the information overload, and how do their decisions shape their knowledge and beliefs? We’ll discuss recent empirical work about the core cognitive systems that people use to guide their learning about the world—including attention, curiosity, and metacognition (thinking about thinking). We discuss the evidence that people play an active role in their own learning, starting in infancy and continuing through adulthood, and how many of these mechanisms are shared with non-human animals. We’ll talk about why we are curious about some things but not others, and how our past experiences and existing knowledge shape our future interests. We’ll also discuss why people sometimes hold beliefs that are inconsistent with evidence available in the world, and how we might leverage our knowledge of human curiosity and learning to design systems that better support access to truth and reality.
A running theme throughout this series will be the importance of uncertainty in guiding our learning and collaborative knowledge building. We will be taking a comparative approach in outlining the types of cognitive representations of uncertainty shared among biological intelligence, but lacking in artificial ones, to explain how current generative AI models cannot be trusted to disseminate information to people without problems. We’ll discuss several core tenets of human psychology that can help build a bridge of understanding about what is at stake when discussing regulation and policy options to prevent widespread adoption of these AI technologies from permanently distorting human beliefs in problematic ways.
Lecturer
Celeste Kidd studied print journalism and linguistics at the University of Southern California, where she earned a dual honors degree in 2007. Kidd moved to the University of Rochester for her graduate studies, where she worked in brain and cognitive studies and earned her PhD in 2013. She worked with Richard N. Aslin, an expert on infant learning. Kidd held visiting positions at Stanford University and the Massachusetts Institute of Technology. Kidd is a professor of psychology at the University of California, Berkeley.
