Author: Philipp Wicke

Lecturer: Romina Martin
Fields: Environmental system science, sustainability, complexity

Content

Wicked problems and the polycrises of the Anthropocene are challenging contexts for laying out a perspective for resilient and equitable human well-being within the planetary boundaries. “Humans are embedded in the biosphere” is the underlying assumption for sustainability scientists working with resilience of social-ecological systems. This means that humans shape, for example, lakes, agricultural landscapes, forests and oceans which they in turn depend on. The emerging system dynamics are often non-linear and further influenced by shocks. How could and should this system persist, adapt or transform in order to continue providing life support functions?
This course will introduce resilience principles, complex adaptive systems and demonstrate how simulation models together with complementary methods enable research on regime shifts, poverty traps and common pool resource problems. We will use case study examples to co-develop conceptual models on paper in a participatory process. To reflect, we discuss the inter- and transdisciplinary challenges for using model simulations in resilience thinking.

Literature

• https://www.seslink.org – video on complex adaptive systems
• Schlüter, M., Haider, L., Lade, S., Lindkvist, E., Martin, R., Orach, K., Wijermans, N., Folke, C., 2019. Capturing emergent phenomena in social-ecological systems: an analytical framework. Ecology and Society 24. https://doi.org/10.5751/ES-11012-240311
• Martin, R., Sanga, U., 2023. Participatory modelling: Participatory research methods for sustainability ‐ toolkit #6. GAIA – Ecological Perspectives for Science and Society 32, 230–232. https://doi.org/10.14512/gaia.32.2.5
• Martin, R., Schlüter, M., Blenckner, T., 2020. The importance of transient social dynamics for restoring ecosystems beyond ecological tipping points. PNAS 117, 2717–2722. https://doi.org/10.1073/pnas.1817154117

Lecturer

As a modeller in ecology, Romina investigates complexity in social-ecological interactions to better explain and support sustainable management and governance in European landscapes. She received her PhD 2013 in Biology in Cologne with a study on pastoral livelihood security and rangeland management in drylands using ecological-economic modelling. Since then, Romina pursued research at the Stockholm Resilience Centre on managing regime shifts at lakes, ecosystem services and sustainability transformations. She is teaching systems thinking and sustainability science on the Bachelors and Masters level. Apart from research, Romina enjoys life with her family including two kids on the island Tranholmen close to Stockholm.

Affiliation: Stockholm Resilience Centre, Stockholm University
Homepage: https://www.stockholmresilience.org/meet-our-team/staff/2013-09-12-martin.html

Disciplines/Fields: Ecology, Mathematical modelling, Systems ecology

Dr. Ferenc Jordán will overview how network models help in describing various ecological systems (animal social networks, food webs, habitat networks). We will focus on key nodes and critically important links, and discuss how to connect vertically the above-mentioned, horizontal organization levels. Based on real problems, data, novel methods and approaches we will discuss the limits and perspectives of studying socio-ecological systems. Various hot topics will be discussed, ranging from marine overfishing to the emergence of leadership in social groups, and from systems-based conservation to habitat fragmentation, all from the same systems perspective.

Literature:

• Jordán F 2022. The network perspective: Vertical connections linking organizational levels. Ecological Modelling, 473, 110112, https://doi.org/10.1016/j.ecolmodel.2022.110112.
• Bradshaw CJA, Ehrlich PR, Beattie A, Ceballos G, Crist E, Diamond J, Dirzo R, Ehrlich AH, Harte J, Harte ME, Pyke G, Raven PH, Ripple WJ, Saltré F, Turnbull C, Wackernagel M, Blumstein DT 2021. Underestimating the challenges of avoiding a ghastly future. Frontiers in Conservation Science, 1, 615419, https://doi.org/10.3389/fcosc.2020.615419
• Jordán F, Ehrlich PR, Blumstein DT 2020. Pandemics have multiple, interacting drivers. Psychology Today, 26 July.
• Sagarin R, Taylor T (Editors) 2008. Natural Security: A Darwinian Approach to a Dangerous World. The University of California Press.

Lecturer

Dr. Ferenc Jordán is Hungarian biologist (PhD 1999, Eötvös University, Budapest, Hungary), focusing mostly on part-to-whole problems in ecology, based on network models. These range from food webs to animal social networks and from habitat networks to protein-protein interaction networks. Formerly The Society in Science: Branco Weiss Fellow (ETH Zürich, Switzerland, 2003-2008), Principal Investigator at The Microsoft Research: Centre for Computational and Systems Biology (Trento, Italy, 2008-2014), Fellow at Wissenschaftskolleg zu Berlin (Berlin, Germany, 20162017), presently researcher at University of Parma (Italy, 2022-) and external associate to Stazione Zoologica Anton Dohrn (Napoli, Italy, 2016-). Increasingly interested and active in science communication, panel member of several organizations (e.g. European Research Council, Polish National Science Center) and editor in some journals (e.g. Ecology Letters). Currently lives in Vienna.

Lecturer: Andrea Loettgers
Fields: Epistemology of scientific modelling

Content

Complexity and interdisciplinarity seem to be ubiquitous in today\’s science. As shown in interdisciplinary research areas such as biochemistry, ecology, synthetic and systems biology, neuroscience, and astrobiology, reasoning by models is an integral part of the
scientific practice, which addresses the properties and behavior of complex systems. Philosophers of science have become more insistent in addressing how models generate knowledge about complex systems in their specific interdisciplinary settings. This class will first discuss the traditional view of models as representations of some target systems rooted in the semantic view of theories. From there, we move on to an alternative approach closer to actual scientific practice in which models of complex systems are considered purposefully constructed entities. By doing so, the epistemic capacities inscribed into the model in the construction process become accessible. Models gain autonomy if they are no longer viewed as \’just\’ representing some object in the world.
In discussing the artifactual account of models, we will use examples from systems and synthetic biology, physics such as the Ising and spin glass models, and network models. These discussions of actual cases will lead us to further ‘ingredients’ of modeling practices, such as model templates, which capture essential transdisciplinary practices. Or the transfer of notions from engineering to biology and assumptions about the existence of systems independent design principles underlying the organization of complex systems.
In this course, I will provide some framework for discussions on modeling practices. Everybody is welcome to contribute her/his own experiences by making use of and reflecting on models.
The list of literature is just a selection from which you may get some first idea of what are the topics when it comes to modeling practice in philosophy.

Literature

• Morgan, M. and Morrison, M. (1999). Models as Mediators, Cambridge: Cambridge University Press.
• Weisberg, M. (2007). ‘Who is a Modeler?’, British Journal for the Philosophy of Science 58:207-233.
• Weisberg, M. (2013). Simulation and Similarity: Using Models to Understand the World, New York: Oxford University Press.
• Hughes, R.I.G. (1999) ‘The Ising model, computer simulation, and universal physics’, In M.S.
• Morgan and M. Morrison (Eds.), Models as mediators. Perspectives on natural and social sciences. (pp. 97-145). Cambridge: Cambridge University Press.
• Elowitz, M. and Leiber, S. (2000). ‘A synthetic oscillatory network of transcriptional regulators’, Nature 403: 335-338.
• Hopfield, J. (1982) ‘Neuronal networks and physical systems with emergent collective computational abilities’, Proceedings of the National Academy of Sciences of the USA 79:2554-2558.
• Knuuttila, T. and Loettgers, A. (2013). ‘Basic Science Through Engineering: Synthetic Modeling and the Idea of Biology-inspired Engineering’, Studies in History and Philosophy of Biological and Biomedical Sciences 44:158-169.
• Knuuttila, T. and Loettgers, A. (2023). ‘Model templates: transdisciplinary application and entanglement’, Synthese 201(6):200.

Lecturer

Andrea Loettgers is a senior researcher in the ERC project Possible Life-The Philosophical Significance of Extending Biology at the University of Vienna. She holds a habilitation in philosophy of science from the University of Bern and a PhD. in physics from the University of Göttingen. From 2001 to 2011, she has been a Postdoc at the California Institute of Technology. At Caltech, she held joint appointments in the humanities and the biology department to conduct and philosophical analyse laboratory observations in synthetic biology. During this time, she was awarded a grant from the Swiss National Science Foundation and the Alfred Sloan Foundation. From 2005-2006, she had been appointed as the Hixon-Riggs Visiting Professor for Science, Technology and Social Studies at Harvey Mudd College. After returning to Switzerland, Loettgers has been awarded an additional grant from the Swiss National Science Foundation for a project on synthetic biology at the University of Geneva. From 2016 to 2018, she was appointed as Bernoulli Fellow at the Center of Space and Habitability. In her research, Loettgers investigates modeling practices in physics and biology based on laboratory observations. A special interest concerns the development of organizational principles in biology and their transfer in-between biology and physics. She has published in: British Journal for the Philosophy of Science, Philosophy of Science, European Journal for Philosophy of Science, Studies in History and Philosophy of Science, Studies in History and Philosophy of Biological and Biomedical Sciences, and The Monist.

Affiliation: University of Vienna

Lecturer: Ana-Alexandra Moga
Fields: Coaching | Personal Development | Personal Growth

Content

In the four session course, we’ll take a walk together through the garden of resilience.

Over the duration of the course, we’ll explore some science-based knowledge nuggets to expand on how we think about our mind and body, practice some coaching methods that can anchor us in the present moment, develop our own tools for cultivating resilience and, hopefully, have some fun in the meantime.
As we collectively experience the conference, during the middle part of the course we’ll explore ways to connect deeper and find inspiration and strength from each other and the group.
The closing part of the course is aimed to highlight and review the tools and strategies that we can take home with us to further experiment with and continue to cultivate resilience in our every day life.

Lecturer

Ana-Alexandra Moga is a certified executive and leadership coach. Her background is rooted in software development and engineering management, with a lifelong yearning for artistic expression. Her passion for coaching took an academic route in 2021, when she enrolled at New York University to follow a rigorous education in the coaching domain. Six months after graduation she left her product and engineering leadership role to pursue the coaching path full time. She harnessed her 17+ years experience in both the corporate world and in fast paced start-up environments to create a blended coaching style: creative, playful, goal oriented, highly adaptable and with a strong structural foundation.

Affiliation: N/A
Homepage: https://www.linkedin.com/in/ana-alexandra-moga-86a653b/

Lecturer: Michael Ungar
Fields: Social Science; Psychology; Health Science; Community Development; Cultural Studies

Content

In this short course, Dr. Michael Ungar will explore the many different systems that contribute to experiences of individual and collective resilience, as well as the methods used to research multisystemic resilience. The intent is to integrate perspectives from studies of biological, psychological, social, institutional, and economic resilience, as well as those concerned with the built and natural environments. The course will also focus on how to research resilience in participatory ways to develop knowledge that informs policy and practice. An introduction to the theory of resilience will be followed by an overview of its application to populations under stress, as well as the tools used to assess resilience at individual and community levels. Using examples from studies conducted by Dr. Ungar and his colleagues at the Resilience Research Centre, students will have an opportunity to reflect on how multiple systems influence one another over time and in culturally nuanced ways. Discussion will include topics such as contextualization of the resilience concept, measure development to account for positive developmental processes, and the many aspects of resilience that need to be considered in designing research and developing programs and policies to improve the capacity of populations to cope with atypical stressors. Participants are encouraged to bring questions relating to their own research topics whether from the natural, biological, or social sciences.

Literature

• Ungar, M. & Theron, L. (2019). Resilience and mental health: How multisystemic processes contribute to positive outcomes. Lancet Psychiatry, 7(5), 441-448. Doi:10.1016/S2215-0366(19)30434-1
• Ungar, M. (2018). Systemic resilience: Principles and processes for a science of change in contexts of adversity. Ecology & Society, 23(4). Doi: 10.5751/ES-10385-230434.
• Ungar M. (Ed.)(2021). Multisystemic resilience: Adaptation and transformation in contexts of change. New York: Oxford University Press. (Available open access: https://oxford.universitypressscholarship.com/view/10.1093/oso/9780190095888.001.0001/oso-9780190095888)

Lecturer

Michael Ungar, Ph.D., is a Family Therapist and Professor of Social Work at Dalhousie University where he holds the Canada Research Chair in Child, Family and Community Resilience. His research on resilience around the world and across cultures has made him the number one ranked Social Work scholar in the world, with numerous educational institutions, government agencies, not-for-profits and businesses relying on his research and clinical work to guide their approaches to nurturing child, family, organizational and community wellbeing under stress. He the author of over 250 peer reviewed papers and book chapters, as well as 18 books for researchers, mental health professionals, and lay audiences, including his most recent works The Limits of Resilience: When to Persevere, When to Change, and When to Quit (forthcoming January, 2024), a book for individuals and organizations under stress, Multisystemic Resilience: Adaptation and Transformation in Contexts of Change, an open access compilation of 39 scholarly papers from a dozen different disciplines, and Working with Children and Youth with Complex Needs: 20 Skills to Build Resilience, a book for mental health professionals. As well as having received numerous awards for his work, including the Canadian Association of Social Workers National Distinguished Service Award and being named a Fellow of the Royal Society of Canada, Dr. Ungar maintains a blog titled Nurturing Resilience which can be read on Psychology Today’s website.

Affiliation: Dalhousie University
Homepage: www.resilienceresearch.org; www.michaelungar.com

Lecturer: Anna Förster
Fields: Internet of Things, Machine Learning

Content

This course will offer an overview of the problems and challenges associated with outdoor deployments of internet of things (IoT) applications. After a short introduction to the field of IoT and the discussion of various outdoor applications, we will dive deeper into the threats IoT applications face in these environments. We will showcase some concrete threats and discuss possible solutions and approaches.

Lecturer

Anna Förster obtained her MSc degree in computer science and aerospace engineering from the Free University of Berlin, Germany, in 2004 and her PhD degree in self-organising sensor networks from the University of Lugano, Switzerland, in 2009. She also worked as a junior business consultant for McKinsey&Company, Berlin, between 2004 and 2005. From 2010 to 2014, she was a researcher and lecturer at SUPSI (the University of Applied Sciences of Southern Switzerland). Since 2015, she leads the Sustainable Communication Networks group at the University of Bremen. Currently, she serves as Director of the Bremen Spatial Cognition Center (BSCC) and as a board member of the Center for Computing Technology (TZI). Her main research interests lie in the domain of the Internet of Things. She is mostly interested in self-awareness and resilience, user friendliness and user adoption, self-organisation, and machine learning for IoT applications. All considered scenarios and applications serve the Sustainable Development Goals and contribute to a more sustainable and peaceful future.

Affiliation: University of Bremen
Homepage: comnets.uni-bremen.de

Lecturer: Herbert Jaeger
Fields: All IK disciplines

Content

This is a crash course (4 sessions at 90 minutes each) on dynamical systems, held at the Interdisciplinary College (https://interdisciplinary-college.org) several times. The presentation is meant to be understandable for a general natural / neural / cognitive science audience. The slides from the 2023 presentation can be retrieved from https://www.ai.rug.nl/minds/uploads/DynamicalSystemsPrimer_Jaeger.pdf.

Literature

• 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.

Affiliation: University of Groningen
Homepage: https://www.ai.rug.nl/minds/

Lecturer: Maggi Savin-Baden
Fields: Digital Afterlife/AI

Content

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 .

Lecturer: Emily King
Fields: Mathematics

Content

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

Affiliation: Colorado State University
Homepage: https://www.math.colostate.edu/~king/

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