Author: Philipp Wicke

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/
• Barber, D. (2012). Bayesian Reasoning and Machine Learning. Cambridge University Press. Cambridge, UK. http://www.cs.ucl.ac.uk/staff/d.barber/brml/
• Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning. MIT Press. Cambridge, MA, USA. https://www.deeplearningbook.org/
• Paaßen, B., Artelt, A., Hammer, B. (2019). Lecture Notes on Applied Optimization. Bielefeld University. https://pub.uni-bielefeld.de/record/2935200
• Shalev-Shwartz, S., and Ben-David, S. (2014). Understanding Machine Learning: From Theory to Algorithms. Cambride University Press. Cambridge, UK. https://www.cs.huji.ac.il/w~shais/UnderstandingMachineLearning/

Lecturer

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.

Affiliation: Bielefeld University
Homepage: https://bpaassen.gitlab.io/

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.

Literature

• Gioia, T. (2006). Work songs. Duke University Press. https://archive.org/details/worksongs00gioi
• 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.

Affiliation: Central European University, Vienna
Homepage: https://www.thomaswolfmusic.com

Lecturer: Miriam Kyselo
Fields: philosophy, cognitive science

Content

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. 

https://www.ntnu.edu/employees/m.kyselo

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

Professor Charles Spence is a world-famous experimental psychologist with a specialization in neuroscience-inspired multisensory design. He has worked with many of the world’s largest companies across the globe since establishing the Crossmodal Research Laboratory (CRL) at the Department of Experimental Psychology, Oxford University in 1997. Prof. Spence has published over 1,100 academic articles and edited or authored, 16 books including, in 2014, the Prose prize-winning “The perfect meal”, and the international bestseller “Gastrophysics: The new science of eating” (2017; Penguin Viking) – winner of the 2019 Le Grand Prix de la Culture Gastronomique from Académie Internationale de la Gastronomie. His latest book Sensehacking was published in 2021. Much of Prof. Spence’s work focuses on the design of enhanced multisensory food and drink experiences, through collaborations with chefs, baristas, mixologists, chocolatiers, perfumiers, and the food and beverage, and flavour and fragrance industries. Prof. Spence has worked extensively in the world of multisensory experiential wine and coffee and has also worked extensively on the question of how technology will transform our dining/drinking experiences in the future. See short video at: Charles Spence – Sensploration (FoST 2016). https://vimeo.com/170509976. And profile at: http://www.newyorker.com/magazine/2015/11/02/accounting-for-taste. \”The Perfect Meal\” | Talks at Google: https://www.youtube.com/watch?v=JgUVjKsP_wc AEG Tasteology: http://www.aeg.co.uk/taste/inspiration/tasteology/ Neurocuisine, The Guardian: https://www.theguardian.com/lifeandstyle/video/2016/may/23/neuro-cuisine-exploring-the-science-of-flavour-video Multisensory Experience and Coffee – RecoSymposium: https://www.youtube.com/watch?v=vVKabsudi1I Unexpected connections — pleasure and pain: Charles Spence at TEDxUHasselt: https://www.youtube.com/watch?v=NVt-QrNFZso Flavour Sense Nation short videos: Prof. Charles Spence – Flavour SenseNation http://flavoursense.com/ask-the-scientist/prof-charles-spence Entomophagy in our world, TEDxCityUniversityLondon: https://www.youtube.com/watch?v=iQEX-kMpz-4 Shitsukan (2019) Japan https://www.youtube.com/playlist?list=PLoDvHIx6ItiODbZgBWEDbWCC-N3h8hW9o Cambridge Biological Society: https://www.youtube.com/watch?v=_dZSlSuRs34 Spence Bar Academy Bulgaria https://www.facebook.com/BarAcademyBulgaria/videos/gastrophysics-a-multisensory-approach-to-cocktails-by-prof-charles-spencesofiaba/361034184762577/ Spence LSE Gastrophysics talk https://www.youtube.com/watch?v=HB_B9hfsNXI Spence Going Underground TV https://www.youtube.com/watch?v=56e5UZJreg0 For multisensory packaging video, see: https://www.youtube.com/watch?v=tV3SRKFpEsg Nuffield Triannual Food Conference: https://www.youtube.com/watch?v=ePguEqCJ7Ks http://www.blog.generalmills.com/2016/09/podcast-making-food-your-five-senses-will-love/ See also: BBC SERIES – The Uncommon Senses; Series 1 Dinnertime: A Multisensory Extravaganza! https://www.bbc.co.uk/sounds/play/b08k5zqw Enhancing Multisensory Experiences: Perspectives from the Food & Beverage, and Flavor & Fragrance Industries | Listen Notes https://hq.quikly.com/blog/the-psychology-of-fast-food-nostalgia.

Affiliation: University of Oxford
Homepage: https://www.psy.ox.ac.uk/research/crossmodal-research-laboratory

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.
• https://www.interaction-design.org/literature/book/the-glossary-of-human-computer-interaction/tangible-interaction
• Cited in course description:
• 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.

Affiliation: Ludwig Boltzmann Institute for Digital Health and Prevention & Open Lab, Newcastle University
Homepage: https://smeddinck.com/ and  https://dhp.lbg.ac.at/

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/

Lecturer: Judith Simon
Fields: Philosophy/Ethics of AI, Philosophy & Ethics of Technology

Content

In this course, I will provide a short introduction into philosophy and ethics of technology, including the role of values in design. I will focus in particular on epistemological, ethical and political questions arising ariding in the context of big data analytics and artificial intelligence.

Literature

• Anderson, C. (2008). The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. In: Wired, [online] https://www.wired.com/2008/06/pb-theory/
• Angwin, J., Larson, J., Mattu, S. and Kirchner, L. (2016, Mai 23). Machine Bias: There’s software used across the country to predict future criminals. And it’s biased against blacks. ProPublica.
• Barocas, S. and Selbst, A. D. (2016). Big Data’s Disparate Impact. 104 California Law Review 671(2016). https://doi.org/10.2139/ssrn.2477899
• Boyd, D. and Crawford, K. (2012). Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon. Information, Communication, & Society 15(5), 662-679.
• Busch, L. (2016). Looking in the Wrong (La)place? The Promise and Perils of Becoming Big Data. Science, Technology & Human Values 42(4), 657 – 678. https://doi.org/10.1177/0162243916677835
• Introna, L. (2005). “Phenomenological Approaches to Ethics and Information Technology.” Retrieved 24.03.2011, from http://plato.stanford.edu/entries/ethics-it-phenomenology/.
• Keyes, O., et al. (2019). A Mulching Proposal: Analysing and Improving and Algorithmic System for Turning the Elderly into High-Nutrient Slurry. CHI 2019, Glasgow, ACM.
• Kitchin, R. (2014). Big Data, New Epistemologies and Paradigm Shifts. Big Data & Society, 1(1).
• Latour, B. (1992). Where Are the Missing Masses? The Sociology of a Few Mundane Artifacts. Shaping Technology/Building Society: Studies in Sociotechnical Change. W. E. Bijker and J. Law. Cambridge, MIT Press: 225-258.
• Leonelli, S. (2014). What difference does quantity make? On the epistemology of Big Data in biology. Big Data & Society, 1(1). https://doi.org/10.1177/2053951714534395
• Moor, J. H. (1985). “What is computer ethics?” Metaphilosophy 16(4): 266-279
• Nissenbaum, H. (2005). Values in Technical Design. In Mitcham, C. (Hrsg.), Encyclopedia of Science, Technology and Ethics, lxvi- lxx. New York: Macmillan.
• Winner, L. (1980). “Do Artifacts Have Politics?” Daedalus 109(1): 121-136.

Lecturer

Judith Simon is Full Professor for Ethics in Information Technologies at the Universität Hamburg. She is interested in ethical, epistemological and political questions arising in the context of digital technologies, in particular in regards to big data and artificial intelligence. Judith Simon is a member of the German Ethics Council as well as various other committees of scientific policy advice and has also been a member of the Data Ethics Commission of the German Federal Government (2018-2019). Her Routledge Handbook of Trust and Philosophy has been published in June 2020.

Affiliation: Universität Hamburg
Homepage: https://www.inf.uni-hamburg.de/en/inst/ab/eit/team/simon.html

Lecturer: Krzysztof Dolega
Fields: Philosophy of Mind, Cognitive Science, Computational Neuroscience

Content

The proposal that probabilistic inference and unconscious hypothesis testing are central to information processing in the brain has been steadily gaining ground in cognitive neuroscience and associated fields. One popular version of this proposal is the new theoretical framework of action-oriented predictive coding or predictive processing, which couples the idea of unconscious perceptual inference with that of ‘active inference’ in which inference and predictive control are applied to action. Together, the two kinds of inference are claimed to offer a unified and exhaustive account of perception and cognition.

The aim of this course is to investigate and evaluate the validity of claims about the explanatory power and credentials of predictive processing. We will explore different interpretations of predictive processing and ask whether the framework supports a representational understanding of cognition or whether it steers cognitive science towards a more enactive approach to mind and life. Finally, we will also try to scrutinize the explanatory scope and the level of analysis on which the framework tries to answer questions about cognition.

Literature

• Bruineberg, J., Kiverstein, J., & Rietveld, E. (2018). The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective. Synthese, 195(6), 2417-2444. https://doi.org/10.1007/s11229-016-1239-1
• Clark, A. (2015). Radical Predictive Processing. The Sou. Journal of Philosophy, 53, 3-27. https://doi.org/10.1111/sjp.12120
• Kirchhoff, M.D. & Robertson, I. (2018) Enactivism and predictive processing: a non-representational view, Philosophical Explorations, 21(2), 264-281, DOI: 10.1080/13869795.2018.1477983
• Sprevak, M. (2021). Predictive coding I: Introduction. http://philsci-archive.pitt.edu/id/eprint/19365
• Sprevak, M. (2021). Predictive coding II: The computational level. http://philsci-archive.pitt.edu/id/eprint/20641
• Sprevak, M. (2021). Predictive coding III: The algorithmic level. http://philsci-archive.pitt.edu/id/eprint/19488
• Sprevak, M. (2021). Predictive coding IV: The implementation level. http://philsci-archive.pitt.edu/id/eprint/19669

Lecturer

Krzysztof Dolega is a postdoc and a member of the situated cognition research group at the Ruhr-Universität Bochum. He has just completed a one and a half year long Volkswagen Stiftung funded grant on the psychology and epistemology of conspiracy theories entitled “Why do people believe weird things: Bayesian brain, conspiracy theories, and epistemic vices”. His doctoral research was also conducted at the Ruhr-Universität, where he was supervised by Tobias Schlicht and Daniel Dennett. Krzysztof was awarded a PhD in Philosophy with a grade of summa cum laude in May 2019. This work was also distinguished by the GfD with the annual prize for the best interdisciplinary dissertation. Krzysztof has published over 15 academic papers and book chapters. Together with Jelle Bruineberg, Joe Dewhurst, and Manuel Baltieri, he is the co-author of the recent Behavioral & Brain Sciences target article “The Emperor’s New Markov Blankets”, which has just appeared in print together with 35 commentaries and a reply from the authors. He has also co-edited a collection of articles on representational explanations by leading researchers titled “Mental Representations: The Foundation of Cognitive Science” (OUP, 2020).

Affiliation: Ruhr-Universität Bochum
Homepage: krysdolega.xyz

Lecturer: Susan Wache, Julia Wache, and Stephan Drechsel
Fields: Cognitive Science

Content

Echolocation is one of the most amazing human sensory perceptions. While sighted people purposefully tune out reflected sound waves, blind people have learned to extract all kinds of information from the echoes. To do this, the brain must generate a processing center in which the size, location, material, and density of surrounding surfaces are represented. It has been scientifically proven that the area of experienced echo sounders is located in the visual cortex and not in the auditory center, which should not be surprising because of the information to be processed.
Can sighted people also learn this technique? How does it feel when the brain builds a new sensory center? How does one program their own brain to process previously hidden sensory perceptions? The course “Echolocation” addresses these questions in a very practical way. Participants learn the basics of the “click sonar” technique (75%) and the theory behind it (25%). The course takes place to a large extent blindfolded. Since we try to intervene as effectively as possible in processing patterns of sensory perceptions, side effects such as elation, migraine or dreams cannot be excluded. No guarantee of consciousness enhancement.

Lecturer

Susan Wache studied Cognitive Science at the University of Osnabrück. She worked in the Research Group feelSpace that investigates human senses and works especially with Compass Belts. In 2015 two colleagues from the same group and herself as CMO founded the startup feelSpace that develops and sells naviBelts, tactile navigation devices especially for the visually impaired.

Affiliation: feelSpace GmbH
Homepage: www.feelSpace.de

Julia Wache studied Cognitive Science in Vienna and Potsdam. She finished her PhD in Trento working on the Emotion Recognition via physiological signals and mental effort in the context of using a tactile belt for orientation. In parallel she participated in the EIT Digital doctoral program to learn entrepreneurial skills. In 2016 she joined the feelSpace GmbH as Head of Marketing. Since feelSpace provides aids for independent mobility of blind people she learned about echo location in this context.

Stephan Drechsel runs a rehabilitation practice for visually impaired and blind persons near Ulm. An important part of his work is to teach blind people echolocation skills. In 2016 he learned active echolocation himself as a sighted person. Since then he has been training sighted colleagues as well as blind students how to use flashsonar, which produces visual images by sound.

Lecturer: Christian Faubel
Fields: Arts, Sonic Arts, Dynamical Systems, Robotics,

Content

In my lecture I critically examine differences between the digital and the analog, which become especially visible in the phenomenon of synchronization. In the lecture I experiment with different analog systems and demonstrate their utopian potential, which I locate especially in the hierarchy-free communication between these systems and I show how polyrhythms emerge from hierarchy-free interaction.

Lecturer

Christian Faubel is an interdisciplinary scholar working in the differing fields of neuroscience, autonomous systems research and media art & design. He holds a PhD in electrical engineering and has completed research on autonomous systems at the Institute for Neural Computation from 2002–2012. From 2012-2018 he was working as artist, researcher and teacher at the academy of media arts cologne. Since 2020 he holds a position as professor for smart connected products at the university of applied sciences cologne, where he teaches in the new bachelor program code & context.

Affiliation: TH-Köln
Homepage: https://christian.faubel.derstrudel.org/