Literature hints are spread over the slides that can be downloaded via the link given in the abstract above.
Lecturer
Herbert Jaeger studied Mathematics in Freiburg (Germany), specializing in formal logic, then did a PhD in Bielefeld (Germany) in the classical AI (knowledge-based systems) group of Ipke Wachsmuth, became interested in dynamical systems modeling in cognitive science, which led to a postdoc in the autonomous robots research team of Thomas Christaller at the (then) German National Research Institute for Mathematics and Computer Science (GMD) in Sankt Augustin (Germany), where he shifted to signal processing, machine learning and recurrent neural networks, which in turn allowed him to found and head a GMD research unit on modeling intelligent dynamical sytsems (MINDS); then from 2001 to 2019 he served as professor in the CS department of the private Jacobs University Bremen (Germany) where he taught theoretical CS and machine learning and continued thinking about mathematical modeling of cognitive dynamics, which somehow got him pulled into the fields of unconventional computing, which in turn in 2019 led to an appointment at the University of Groningen, where he still uses the name MINDS for his group and where he still teaches machine learning but now dedicates all research efforts on unconventional computing theory, often in collaboration with mathematicians, theoretical computer scientists, materials scientists, microchip engineers, cognitive scientists and AI/machine learning colleagues. His lifetime dream is to develop a mathematical language for general information-processing dynamical systems.
The famous song by Queen, was written by Brian May for the 1986 film Highlander, the song is used to frame the scenes in the film where Connor MacLeod must endure his beloved wife Heather MacLeod growing old and dying while he, as an Immortal, remains forever young. Who wants to live forever as a song and as a religious and philosophical question introduces uncomfortable queries about the value and purpose of this life.
The evening talk suggests that Digital afterlife has moved beyond digital memorialisation towards a desire to preserve oneself after death. Preserving oneself or being preserved by someone else may affect both the dying person’s peace of mind and the well-being of the bereaved. Yet it is not clear whether the possibility of digital immortality and the use of digital media alters thoughts about the mind-body connection, and whether interaction with a digital immortal alters one’s spiritual journey through grief. Afterlife and resurrection remain troublesome because they are couched in mystery and philosophical and theological discourse cannot explain resurrection of the body, because the human body itself is not reducible to simple description or ready comprehension.
Literature
Burden, D. (2020). Building a Digital Immortal. In M. Savin-Baden & V. Mason-Robbie (Eds)., Digital Afterlife. Death Matters in a Digital Age. Boca Raton, Florida: CRC Press
Burden, D. & Savin-Baden, M (2019). Virtual Humans: Today and Tomorrow. Florida: CRC Press.
Harbinja, E. (2020). The ‘new(ish)’ property, informational bodies and postmortality. In M. Savin-Baden & V. Mason-Robbie (Eds)., Digital Afterlife. Death Matters in a Digital Age. Boca Raton, Florida: CRC Press.
Kasket, E. (2021). If death is the spectacle , big teach is the lens: How social media frame an age of ‘spectacular death’ In M. H. Jacobsen. (Ed) The Age of Spectacular Death. Oxford: Routledge
Pitsillides, P. (2019). Digital legacy: Designing with things, Death Studies, 43 (7), 426-434. DOI: 10.1080/07481187.2018.1541939
Savin-Baden, M. (2023) Postdigital Theologies in P. Jandrić (Ed) Encyclopedia of Postdigital Science and Education. Cham: Springer.
Savin-Baden, M. (2023) Postdigital Afterlife in P. Jandrić (Ed) Encyclopedia of Postdigital Science and Education. Cham: Springer.
Savin-Baden, M. (2023) Digital afterlife and the spiritual realm: Transcendence. In M. E. Mogseth & F.H. Nilsen. Limits of Life. Critical Interventions, London: Berghahn Series
Lecturer
Professor Maggi Savin-Baden is a Senior Research Fellow at the University of Oxford, UK and has researched and evaluated staff and student experience of learning for over 20 years and gained funding in this area (Leverhulme Trust, JISC, Higher Education Academy, MoD). She gained her Masters and PhD from the University of London and a second Masters in Digital learning from the University of Edinburgh in 2018. Maggi has a strong publication record of over 60 research publications and 25 books which reflect her research interests in the impact of innovative learning, digital fluency, cyber-influence, pedagogical agents, qualitative research methods, and problem-based learning. In her spare time, she runs, bakes, rock climbs, does triathlons and has recently taken up wild swimming and paddle boarding .
Linear algebra has ancient roots, appearing even in cuneiform text millennia ago. However, it has proven itself to be resilient and powers many modern techniques in machine learning, natural language processing, cognitive science, and more. Yet, many people use these tools without truly understanding why they work and when they should be used. The purpose of this course is to provide a deep dive into the intuition behind the tools that linear algebra has to offer. It should be of interest both to students who have taken a course in linear algebra and those who have not. We will also touch on the topic of the responsible use of linear algebra and other mathematical techniques.
Literature
King, E. and Wilson J. “Linear Data” (2023) [open source text to be made available before IK]
Lecturer
Dr. Emily J. King received Ph.D. in mathematics from the University of Maryland in 2009. Since then, she has been an IRTA Postdoctoral Fellow at the National Institutes of Health (USA); a Humboldt Postdoctoral Fellow at Uni Osnabrück, Uni Bonn, and TU Berlin; and a Juniorprofessor at Uni Bremen. She is currently an Associate Professor in the Mathematics Department and member of the data science faculty at Colorado State University. Photo credit: John Eisele/Colorado State University Photography
Lecturer: Philipp Wicke Fields: Artificial Intelligence, Computational Linguistics, Language Models
Content
Most of the thousands of languages in the world share some key properties that enable us to exchange information within our language communities, but also beyond them. At the same time, we experience a shift in artificial intelligence, which heavily relies on the development of large language models for certain languages, which exhibit emergent, general human-like properties such as reasoning and planning. This course has a bipartite structure that combines the theory of robustness in languages from the perspective of cognitive science with the practice of responsible applications of generative language models.
* Session 1: Introduction to Language Robustness In this introductory session, students will gain a profound understanding of language universals and the fundamental role they play in human communication. We explore universal properties of language and linguistic relativity, examining how language shapes our perceptions and thoughts.
* Session 2: Traits of Robust Language: Image Schemas and Embodiment Building on the foundation laid in the previous session, we investigate the connection between language and conceptual understanding. Explore image schemas and embodiment as powerful mechanisms for robust concepts. Additionally, we introduce the concept of “Robustness of Concepts” and explore illustrative examples, including the fusion of language and emojis.
* Session 3: Large Language Models and Image Generation This session opens up new horizons as we look at Large Language Models (LLMs). Learn about the possibilities and challenges of using these sophisticated models for various applications. We delve into multilingual studies involving Large Language Models, such as Glot500, and look at those concerned with embodiment and LLMs. We will also look at text-to-image generational models such as Midjourney, StableDiffusion or Dalle-2. Students will also gain insights into testing different models to identify their strengths and limitations.
* Session 4: Responsible Language Generation Ethics takes center stage in this last session, as we focus on the responsible use of language generation technologies. We focus on the environmental impact of these models, considering factors such as emissions, energy consumption during training and inference, and e-waste generation and storage. Societal implications are also discussed, including bias in language models, data annotation through crowdsourcing, and the ethical challenges posed by deep fakes and fake news generation.
By the end of this course, students will have a comprehensive understanding of language universals, large language models, and ethical considerations.
Literature
Evans, Vyvyan, and Melanie Green. Cognitive linguistics: An introduction. Routledge, 2018.
Boroditsky, Lera. “Does language shape thought?: Mandarin and English speakers’ conceptions of time.” Cognitive psychology 43.1 (2001): 1-22.
Wei, Jason, et al. “Emergent abilities of large language models.” arXiv preprint arXiv:2206.07682 (2022).
ImaniGooghari, Ayyoob, et al. “Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages.” arXiv preprint arXiv:2305.12182 (2023).
Wicke, Philipp. “LMs stand their Ground: Investigating the Effect of Embodiment in Figurative Language Interpretation by Language Models.” arXiv preprint arXiv:2305.03445 (2023).
Wicke, Philipp, and Marianna Bolognesi. “Emoji-based semantic representations for abstract and concrete concepts.” Cognitive processing 21.4 (2020): 615-635.
Lecturer
Philipp Wicke studied Cognitive Science at the University of Osnabrück in the B.Sc. programme. During these studies he interned at Dauwels Lab at the NTU Singapore in the field of neuroinformatics, he also interned at the Creative Language Systems Lab at UCD Dublin at which he later wrote his dissertation on “Computational Storytelling as an Embodied Robot Performance with Gesture and Spatial Metaphor” under supervisor Tony Veale. In his current role at LMU, Philipp is researching on Natural Language Processing and teaches programming in the B.A. and M.A. Computational Linguistics. Philipp Wicke is the Head of AI Applications of the AI for People Association and an Associate Member of the Munich Center for Machine Learning (MCML).
Affiliation: Center for Information and Language Processing (CIS), LMU – Munich Homepage:www.phil-wicke.com
Lecturer: Benjamin Paaßen Fields: Machine Learning
Content
Machine learning is concerned with automatically learning models (patterns, regularities, correlations) from known data which generalize to new data. To do so, it combines concepts from mathematics (esp. statistics, probability theory, linear algebra, and optimization), artificial intelligence, and computer science. This course will provide an introduction to machine learning for the un-initiated. While some math will be necessary, everything will be accompanied by pictures and examples to get the core intuition across 😊
In more detail, the course will have four sessions with the following topics:
Session 1: Basic Concepts: What is Machine learning and how does it relate to Artificial Intelligence? What are types of ML? What does ‘learning’ mean in ML? We will also discuss the basic ingredients of an ML algorithm (loss function, model class, and optimization strategy), linear regression as an example for such an algorithm, underfitting, overfitting (and how to prevent it), how probabilities help us to make precise what ‘generalization’ means, and how to design a basic ML experiment.
Session 2: Classic machine learning tasks and methods to solve them: The distance perspective on ML, Regression, Classification, Dimensionality Reduction, Clustering, with respective methods for each task; and decision trees/forests
Session 3: Artificial neural networks and deep learning: How to build artificial neural networks from single neurons to present-day transformers
Session 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
This is optional literature for people who want to dive in deeper after the course:
Biehl, M. (2023). The Shallow and the Deep: A biased introduction to neural networks and old school machine learning. https://www.cs.rug.nl/~biehl/
Benjamin Paaßen received their doctoral degree in intelligent systems in 2019 from Bielefeld University on the topic of ‘Metric Learning for Structured Data’. Afterwards, they received a DFG research fellowship for a stay at The University of Sydney in Australia and Humboldt-University of Berlin. From 2021-2024, they were deputy head of the educational technology lab at the German Research Center for Artificial Intelligence (DFKI). Since April 2023, they are junior professor for knowledge representation and machine learning (KML, speak ‘camel’) at Bielefeld University. Their research foci are machine learning on structured data and artificial intelligence for education.
Lecturer:Thomas Wolf Fields: Social cognition, interpersonal coordination
Content
Humans are social animals and achieve remarkable things when they coordinate. Coordination in time and space however is not always as easy as it might seem. Joint action research aims to understand the cognitive mechanisms involved in social coordination. In this course we will look at different types of interpersonal coordination, their underlying mechanisms, some effects of coordination and various physical and non-physical devices which support coordination. We will focus on how work songs, such as sea shanties, support the coordination of physical effort.
Pickering, M., Robertson, E., & Korczynski, M. (2017). Rhythms of Labour: The British Work Song Revisited. Folk Music Journal, 9(2), 226–245. https://www.jstor.org/stable/pdf/4522809.pdf
Sebanz, N., Bekkering, H., & Knoblich, G. (2006). Joint action: Bodies and minds moving together. Trends in Cognitive Sciences, 10(2), 70–76. https://doi.org/10.1016/j.tics.2005.12.009
Sebanz, N., & Knoblich, G. (2021). Progress in Joint-Action Research. Current Directions in Psychological Science, 096372142098442. https://doi.org/10.1177/0963721420984425
van der Wel, R. P. R. D., Becchio, C., Curioni, A., & Wolf, T. (2021). Understanding joint action: Current theoretical and empirical approaches. Acta Psychologica, 215, 103285. https://doi.org/10.1016/j.actpsy.2021.103285
Wolf, T., Vesper, C., Sebanz, N., Keller, P. E., & Knoblich, G. (2019). Combining Phase Advancement and Period Correction Explains Rushing during Joint Rhythmic Activities. Scientific Reports, 9(1), 9350. https://doi.org/10.1038/s41598-019-45601-5
Lecturer
Thomas Wolf studied musicology and cognitive science at the University of Vienna, before completing his PhD in cognitive science at the Central European University, Budapest. Currently he is a postdoctoral researcher in the Social Mind and Body (SOMBY) Lab at the Central European University, Vienna, where he directs the SOMBY MusicLab. Embedded in the larger fields of social cognition and joint action, his research interests center around temporal coordination in social interactions, which he investigates through experiments conducted on joint music-making.
There has been a paradigm change in views of the self. The self is no longer an abstract entity, situated or realized by our individual brains. It is seen as embodied instead and likely as being co-constituted through our relations and interactions with others. In this course we explore recent theories of selfhood stemming from the field of so-called embodied and enactive cognition. We will discuss the self both from a third-personal “objective” perspective (as a living entity) and from a first-personal, subjective perspective (as lived or experienced entity). An important question to be explored is the extent to which the embodied self should be seen as a genuinely social and relational phenomenon.
Literature
Di Paolo, E., Rohde, M., & De Jaegher, H. (2010). Horizons for the enactive mind: Values, social interaction, and play. In Enaction: Towards a new paradigm for cognitive science. MIT press
Gallagher, S. (2000). Philosophical conceptions of the self: implications for cognitive science. Trends in cognitive sciences, 4(1), 14-21.
Gallagher, S., & Daly, A. (2018). Dynamical relations in the self-pattern. Frontiers in psychology, 664.Heersmink, R. (2020). Varieties of the extended self. Consciousness and Cognition, 85, 103001.
Hutto, D. D., & Ilundáin-Agurruza, J. (2020). Selfless activity and experience: Radicalizing minimal self-awareness. Topoi, 39(3), 509-520.
Kyselo, M. (2014). The body social: an enactive approach to the self. Frontiers in Psychology, 5, 986.
Lindblom, J. (2020). A radical reassessment of the body in social cognition. Frontiers in Psychology, 11, 987.
Maiese, M. (2019). Embodiment, sociality, and the life shaping thesis. Phenomenology and the Cognitive Sciences, 18(2), 353-374.
Thompson, E. (2005). Sensorimotor subjectivity and the enactive approach to experience. Phenomenology and the cognitive sciences, 4(4), 407-427.
Lecturer
Miriam Kyselo is a philosopher and cognitive scientist. She received a PhD from the Institute of Cognitive Science University of Osnabrueck. Since 2020 she holds the position of Associate Professor at the Norwegian University of Science and Technology. Her expertise is in philosophy of cognition, especially the so-called 4E approaches (enacted, extended, embodied, embedded aspects of the mind), philosophy of psychology, as well as interdisciplinary research in embodied cognitive science.
Lecturer: Prof. Charles Spence Fields: gastrophysics
Content
Most of us are convinced that we can taste the food we eat, and directly savour the drinks that we consume. However, a growing body of gastrophysics research (Spence, 2017) demonstrates that the artefacts that we use to plate food on, drink in, and consume food with (think cutlery) exert far more of an impact on our experience of food and drink than any of us realise. Everything from the weight and material properties of the cutlery, through to the texture and visual appearance of plateware influence people’s perception of the taste/flavour of food. Chefs are starting to question how their guests interact with the food they prepare, and plateware designers are starting to develop neuroscience-inspired plateware. Looking to the future, it is intriguing to consider how digital technologies may increasingly come to modify (and hopefully enhance) the experience of food and drink. But can they (e.g., sensory apps) actually help to nudge people towards eating behaviours that are healthier for the individual, and more sustainable for the planet? Or do they merely entertain?
Literature
Spence, C. (2017). Gastrophysics: The new science of eating. London, UK: Viking Penguin.
Spence, C. (2022). Interacting with food: Tasting with the hands. International Journal of Gastronomy & Food Science, 30:100620. https://doi.org/10.1016/j.ijgfs.2022.100620.
Lecturer: Jan Smeddinck Fields: Human-Computer Interaction, Interaction Design, User Experience, Embodied Interaction, Human-AI Interaction, Tangible Interaction, Natural User Interfaces, Reality-Based Interaction, Multimodal Interaction, Augmented Reality, Virtual Reality, Digital Health
Content
With the realization of Weiser’s vision (Weiser, 1991) and computing becoming truly ubiquitous, pervading application areas including education, health, manufacturing, and many more, human-computer interaction (HCI) – or more generally speaking human-technology interaction – is more relevant than ever. Concepts that arguably originated in the melting-pot of HCI research have been adopted in many areas outside of research labs, including the formation of dedicated professional occupations, e.g. in user experience or interaction design. Looking at our co-existence and co-evolution with ubiquitous and pervasive technologies both at work and in our private lives, HCI as a research field addresses two key questions: I) How do we create/make/design/implement technologies that work well (or better) for people? and II) What does it do to people (individuals and groups) to be living and working so closely with these technologies? Clearly this necessitates in interdisciplinary angle that sits at the heart of HCI and resonates well with the IK interdisciplinary college in combining foundations from computing, psychology, sociology and further fields with technology and societal developments. Across three sessions, the course will provide considerations based on lecturing, discussion and practical elements around human-technology interaction concerning a) minds, b) bodies) and c) things, emphasizing the dynamics of experience that arise when using interactive systems. These elements are arguably important to consider as we turn to recognize that technological progress increasingly does not only concern technological artifacts separately from (or independently of) human beings as the other main subject of study in HCI. Following on ideas of digital tools as extensions of our bodies (McLuhan & Lapham, 1994), recent developments in genetics, implanted technologies and brain-computer interfaces clearly indicate the relevance of beginning to understand humans as augmented beings in complex – often quite literally integrated (Mueller et al., 2020) and ever more rapidly changing – interplay with technologies. In parallel, agent systems and conversational interfaces are becoming more commonplace and frequent interaction partners, enabled by considerable advances in machine learning and artificial intelligence. In the light of the innate human tendency to anthropomorphize, this clearly warrants approaches to HCI development and research that are deeply informed by psychological and sociological theory and methodology. These observations indicate important directions for further socio-digital research in exciting emerging avenues for HCI, particularly around application areas such as digital health and wellbeing, and with stakeholder groups who could greatly benefit from enabling and empowering human-augmentation and technologies, such as older adults. However, in the light of the already considerably challenging impact of relatively loosely coupled technologies, such as social media consumed largely through hand-held personal devices, these developments must also be studied and understood with a critical perspective on the potential dangers and entailing radical societal changes. How to sustain and improve inclusive and equitable technology design in such complex scenarios is an important research motif.
Literature
General Reading:
Dix, A., Finlay, J., Abowd, G. D., & Beale, R. (2003). Human-Computer Interaction (3 edition). Prentice Hall.
Dourish, P. (2001). Where the Action Is: The Foundations of Embodied Interaction. The MIT Press.
Höök, K. (2018). Designing with the Body: Somaesthetic Interaction Design. The MIT Press.
Moggridge, B. (2006). Designing Interactions. MIT Press.
Sharp, H., Preece, J., & Rogers, Y. (2019). Interaction Design: Beyond Human-Computer Interaction (5th edition). John Wiley & Sons.
McLuhan, M., & Lapham, L. H. (1994). Understanding Media: The Extensions of Man (Reprint edition). The MIT Press.
Mueller, F. F., Lopes, P., Strohmeier, P., Ju, W., Seim, C., Weigel, M., Nanayakkara, S., Obrist, M., Li, Z., Delfa, J., Nishida, J., Gerber, E. M., Svanaes, D., Grudin, J., Greuter, S., Kunze, K., Erickson, T., Greenspan, S., Inami, M., … Maes, P. (2020). Next Steps for Human-Computer Integration. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–15. https://doi.org/10.1145/3313831.3376242
Weiser, M. (1991). The computer for the 21st century. Scientific American, 265(3), 94–104.
Further reading:
Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77–91. https://proceedings.mlr.press/v81/buolamwini18a.html
Qian Yang, Aaron Steinfeld, Carolyn Rosé, & John Zimmerman. (2020). Re-examining Whether, Why, and How Human-AI Interaction Is Uniquely Difficult to Design. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–13. https://doi.org/10.1145/3313831.3376301
Lecturer
Jan Smeddinck is currently a Principal Investigator at – and the Co-Director of – the Ludwig Boltzmann Institute for Digital Health and Prevention (LBI-DHP) in Salzburg, Austria. For the LBI-DHP, he leads research programme lines on digital health applications and data analytics. Prior to this appointment he was a Lecturer (Assistant Professor) in Digital Health at Open Lab and the School of Computing at Newcastle University in the UK to which he retains a visiting association. He also spent one year as a postdoc visiting research scholar at the International Computer Science Institute (ICSI) in Berkeley and his PhD alma mater is the TZI Digital Media Lab at the University of Bremen in Germany. Building on his background in interaction design, serious games, web technologies, human computation, machine learning, and visual effects, he has found a home in the research field of human-computer interaction (HCI) research with a focus on digital health.
Lecturer: Dr. Rebecca Böhme Fields: Neuroscience, Psychology, Philosophy
Content
Social touch is one of the earliest ways to experience the own body and the presence of others in the world around us. Therefore, the social other is inherently intertwined with our bodily self perception. Despite the primacy of touch as a social communication channel, social touch has not received much attention in neuroscientific and psychological research. While vision and audition – both distance senses – are by now quite well understood, the tactile sense and especially its social aspects are being investigated in more depth only in recent years. In this course, we will discuss the neurobiological processing of tactile perceptions, social tactile communication, the contribution of social touch to perceiving the own body and to developing a sense of self, and philosophical and ethical implications with a special focus on the covid pandemic and on the digitalization of social interactions. It will incorporate different teaching formats (lecture, group work, practical experience for those comfortable with touch to the arms).
Literature
Ciaunica, A., Constant, A., Preissl, H., & Fotopoulou, K. (2021). The first prior: from co-embodiment to co-homeostasis in early life. Consciousness and cognition, 91, 103117.
Boehme, R., Hauser, S., Gerling, G. J., Heilig, M., & Olausson, H. (2019). Distinction of self-produced touch and social touch at cortical and spinal cord levels. Proceedings of the National Academy of Sciences, 116(6), 2290-2299.
Boehme, R., & Olausson, H. (2022). Differentiating self-touch from social touch. Current Opinion in Behavioral Sciences, 43, 27-33.
Boehme, R., Karlsson, M. F., Heilig, M., Olausson, H., & Capusan, A. J. (2020). Sharpened self-other distinction in attention deficit hyperactivity disorder. NeuroImage: Clinical, 27, 102317.
Fotopoulou, A., & Tsakiris, M. (2017). Mentalizing homeostasis: The social origins of interoceptive inference. Neuropsychoanalysis, 19(1), 3-28.
Frost-Karlsson, M., Capusan, A. J., Perini, I., Olausson, H., Zetterqvist, M., Gustafsson, P. A., & Boehme, R. (2022). Neural processing of self-touch and other-touch in anorexia nervosa and autism spectrum condition. NeuroImage: Clinical, 103264.
Fuchs, T. (2011). The brain–A mediating organ. Journal of Consciousness studies, 18(7-8), 196-221.
McGlone, F., Wessberg, J., & Olausson, H. (2014). Discriminative and affective touch: sensing and feeling. Neuron, 82(4), 737-755.
Lecturer
Dr. Rebecca Böhme is an assistant professor and principle investigator at the Center for Social and Affective Neuroscience in Linköping, Sweden. She is interested in how we establish a bodily self, how we connect with each other, and what happens to the self in psychiatric conditions. Her labs studies body perception and self-other-distinction in states of an altered sense of self. Dr. Böhme studied at Heidelberg University and at the Max Planck research school in Tübingen. For her PhD at Humboldt University & Charité Berlin, she received the For Women in Science Award.
Affiliation: Center for Social and Affective Neuroscience, Linköping University Homepage:https://rebeccaboehme.com/
