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IRIS Forschung

Kritische Reflexion über intelligente Systeme in Politik, Wirtschaft, Bildung, Literatur und Gesellschaft.
[Foto: fotografierende von Pexels]

IRIS Forschung

IRIS-Forschung ist interdisziplinär und interfakultär. Sie konzentriert sich auf die gesellschaftlichen Auswirkungen intelligenter Systeme auf die Gesellschaft in den Bereichen Politik, Literatur, maschinelles Lernen, Wirtschaft und Bildung. Neben den drei unabhängigen Forschungsgruppen von IRIS3D und IRIS-ForscherInnen gibt es Projekte, die von SimTech finanziert und von anderen IRIS-Mitgliedern organisiert werden. IRIS steht auch in Verbindung mit den Participation and Deliberation Labs von ZIRIUS und der Platform for Reflection von SimTech.

DALL-E generierte ein Foto der dreifachen Belichtung von Computational Digital Psychology, Ethik generativer KI-Systeme und Diversity-Aware NLP Intelligent Systems zusammen.
DALL-E generierte ein Foto der dreifachen Belichtung von Computational Digital Psychology, Ethik generativer KI-Systeme und Diversity-Aware NLP Intelligent Systems zusammen.

Zu den Forschungsthemen im IRIS gehören

  • Ethische und gesellschaftliche Herausforderungen von intelligenten Systemen
  • Risiken und Nutzen der automatisierten Entscheidungsfindung in verschiedenen Anwendungsfeldern
  • Partizipative/konstruktive Technikfolgenabschätzung (p/cTA)
  • Szenarien, die Kontexte und Voraussetzungen für den Einsatz intelligenter Systeme in der Gesellschaft analysieren
  • Voraussetzungen für einen gesellschaftlich wünschenswerten Einsatz von lernenden Systemen und autonomer Entscheidungsunterstützung bzw. Entscheidungsfindung
  • Verantwortungsvolle Formen von Mensch-Computer-Interaktionen
  • Sozialökologische Auswirkungen der Digitalisierung
  • Grenzen und kritische Aspekte von Datafizierung, künstlicher Intelligenz, lernenden Systemen und Smartification
  • Untersuchung der Frage, wie zeitgenössische literarische Erzählungen, in denen KI und Roboter eine Rolle spielen, als Instrumente zur kritischen Reflexion über intelligente Systeme genutzt werden können

IRIS3D Unabhängige Forschergruppen


  • Interpretierbarkeit und Analyse von NLP-Modellen
  • Erkennen von schädlichen Verhaltensweisen von Sprachsystemen
  • Anwendung von Techniken der Stilometrie und der Autorenschaft zur Vermeidung von Verzerrungen in NLP-Architekturen
  • Computergestützte Modellierung von subtilen linguistischen Verzerrungen
  • Sprachübergreifende Strukturvorhersage


Details zum Projekt:


  • Erforschung von Auswirkungen von intelligenten Systemen, insbesondere generativer KI, für verschiedene Bereiche der Gesellschaft
  • Forschung zu KI-Ethik und Governance, mit besonderem Schwerpunkt darauf, wie Ethik effizient in Organisationen in der Praxis umgesetzt werden kann
  • Untersuchung von Überschneidungen zwischen Techniken des maschinellen Lernens und Erkenntnissen der Kognitionswissenschaft
  • Empirische Analysen des maschinellen Verhaltens und emergenter Fähigkeiten in Sprachmodellen


Details zum Projekt:


  • Die Auswirkungen intelligenter Systeme auf die Art und Weise, wie Informationen bereitgestellt und von unterschiedlichen Personen konsumiert und verarbeitet werden, wobei der Schwerpunkt auf politisch relevanten Informationen liegt
  • Der Zusammenhang zwischen der Homogenität der Informationsumgebung ("Filterblasen", "Echokammern") von Personen und der politischen Meinungsbildung
  • Die Verbreitung von „Fake News“ und „Desinformation“ online und deren Wirkung auf die Meinungsbildung
  • Schaffung von intelligenten Systemen, die die demokratischen Fähigkeiten von Bürger*innen fördern können
  • Digital Phenotyping und Politisches Microtargeting
  • Datenwirtschaft und digitale Geschäftsmodelle


Details zum Projekt:

IRIS3D Seed-Funded Projects

Project Focus

Using thought experiments as a context for creating and exploring a novel artificial intelligence (AI) system that captures dynamics of human cognition in the form of mental models. A representation and prediction system is trained to emulate the basic causal chain-of events occurring when humans engage in thought experiments. Basic operations are cast into simple dynamical rules and objects, defined in a similar way as in cellular automata and
inspired by production rules in symbolic cognitive architectures, using an autoencoder-like architecture for enhanced abstraction. Potential outcomes of thought experiments can thus be “played out”, generated by the physical dynamics, and iteratively refined. These “AI augmented” thought experiments provide a direct means for self-reflection and critique of one’s mental models (i.e., unconscious biases and presumptions), and stimulate a creative process. At the same time, this enables building an AI model consistent with our own understanding. Cross-disciplinary implications are discussed upon evaluating the system from the perspectives of cognitive science, physics of non-equilibrium, complex systems, as well as for AI performative aspects like knowledge transfer.

Project Members

Project Focus

Online political discussions may help to weigh arguments and shape opinions potentially including considerations from all stakeholders. Thereby, discussion platforms may act as intelligent brokers for a fruitful exchange of opinion. In practice, resentful discussions abound and often they disparage specific groups from equal participation. In this research project, we plan to develop methods of natural language processing and network data analysis to identify 
such unfair treatment. Using the Reddit Politosphere dataset as a case study, we will provide specific statistical analyses and evaluation of developed methods. Based on such methods and analyses, we plan to inform discussion platforms about problems and potential means of containment.

Project Members

Project Focus

The construction industry needs to urgently become more productive and sustainable. Automation is a common approach to increase efficiency. But this approach is challenged by a lack of qualified workers in the construction industry. This project at the intersection of architectural computing with social science addresses this challenge with a novel, AI-based method of human-robot collaboration that (1) replaces demands for human physical labor with demands for technical skills and that (2) engages workers by stimulating creativity and ensuring agency. Shifting from physical endurance to professional input and intellectual contributions opens construction to broader demographics that are otherwise excluded and allows them to contribute more meaningfully and with higher-value skills.

The project integrates perspectives from feminist technoscience—a transdisciplinary field offering distinct ways of thinking about societies, technologies, bodies, power, and environments—to develop a HRC method that attracts skilled staff and supports skills and decision-making while considering uncertainties inherent in construction. Specifically, the project uses methods from experimental democracy to ensure a fair and responsible development process for the HRC method that engages a diverse set of potential users

Project Members

Project Focus

The project investigates the potentials and challenges for democratic systems that come with the proliferation of generative AI applications (gAI) within the realm of public spheres and political deliberation. It focuses on three central aspects: First, the epistemic dimension of gAI both as a source of knowledge in political debate as well as its increased potential to further disinformation. Second, the ethical dimension of the quality of training data scraped from public sources and its implications for the representation of social groups and political opinions within these data and thereby also within answers provided by gAI models. And third, the democracy theoretical dimension of gAI applications as “participants” of political discourse and its repercussions for public deliberation and public reason.

With a genuinely interdisciplinary work plan, the project is able to analyze these three dimensions from a philosophical as well as a machine learning perspective and to discover crucial limitations as well as conditions for institutional and technology design to reap possible benefits of the technology. The overarching goal of the project is to develop and submit an interdisciplinary grant proposal (VW, ERC) for a larger project on the topic of “Generative AI and Public Reason”.

Project Members

Project Focus

Online platforms connect individuals from diverse backgrounds across the globe, fostering a sense of global community. However, this vast reach also carries a potential risk: the formation of echo chambers that inadvertently reinforce existing stereotypes and contribute to polarization. This project uses the revision history of the collaboratively edited wikiHow1 platform to investigate the extent to which such a risk can be evidenced by measurable dynamics and how artificial intelligence methods can be used to mitigate polarization. Specifically, we study instructional texts written in a version for women and a version for men and examine how audience-specific changes over time contribute to making articles more polarizing and in how far such changes actually suit the needs and preferences of the corresponding target groups. Finally, we test whether large language models (LLM) can remedy undesired polarization effects by merging articles written for specific audiences into more balanced articles for a general audience. We bring together methods from computational linguistics and experimental psycholinguistics to carry out the project and to measure its success.

Project Members

Project Focus

Feedback enables the maintenance of motivation and the correct self-assessment of learners' individual progress. As individual tutoring by instructors is not always possible due to limited resources, Intelligent Tutoring Systems (ITS) can supplement such instructors to a certain extent. However, ITSs so far only adapt to the status of the learner, but not to the learners' diverse backgrounds (e.g., culture, gender, and socioeconomic status). Furthermore, gamification can be a suitable tool to increase learners' motivation. To investigate the differential impact of adaptive feedback and gamified learning elements on diverse learners in terms of learning outcomes, learner acceptance, and learning motivation, an ITS with these characteristics will be developed in this project. Such an adaptive and gamified ITS aims to address diverse students' needs and thus reduce course heterogeneity, thereby offering new opportunities for inclusive teaching. Therefore, this project forms the basis for future research on the ethically guided usage of ITS in classrooms, cyber-human learning, and the trustworthiness of AI in education.

Project Members

Forschungsprojekte mit Bezug zur kritischen Reflexion intelligenter Systeme

Förderung: Exzellenzpauschale der Deutschen Forschungsgemeinschaft und den Forschungsrat der Universität Stuttgart.

PI: Dr. Curtis Runstedler

Laufzeit: 04/2022 - 12/2025


  • Wie können literarische Erzählungen als kritische Werkzeuge zur Untersuchung von Bedenken und Ideen zu intelligenten Systemen fungieren?

  • Wie werden Roboter und KI in diesen Erzählungen in ihrer Umgebung vermarktet und ausgebeutet?

  • Präsentieren diese Erzählungen hoffnungsvolle Ergebnisse oder Lösungen für die Kommerzialisierung der Roboter- oder KI-Charakteren?

Förderung: Exzellenzpauschale der Deutschen Forschungsgemeinschaft und den Forschungsrat der Universität Stuttgart.

PI: Lukas Erhard

Laufzeit: 04/2022 - 12/2025

Forschung von IRIS-Mitgliedern

Förderung: Volkswagen Stiftung (Förderlinie "Artificial Intelligence - Its Impact on Tomorrow's Society")

Antragstellende (mit Bezug zu IRIS): Prof. Dr. Jonas Kuhn

Laufzeit: 10/2021 - 09/2025

Weitere Informationen: Projektbeschreibung

Institute for Modelling and Simulation of Biomechanical Systems

This research focuses on human physical interaction with the environment using digital human body models.

  • Do these models allow for unbiased and ideology-free decision-making?
  • Do these models enable improved human-centered and barrier-free design of the built environment?

IRIS Members Involved: Prof. Dr. Syn Schmitt

More Information: Research in Computational Biophysics and Biorobotics

Department of Teaching and Learning with Intelligent Systems

The equal professional participation of people with special needs (e.g. people on the autism spectrum or attention deficit disorder) enriches collaboration through diverse perspectives and strengths. However, difficulties in social interaction often lead to the failure of professional life plans despite high cognitive abilities. Innovative technology-supported training measures can take a preventive approach at this point and strengthen interpersonal skills through learning experiences in a protected setting.

IRIS Members Involved: Jun.-Prof. Dr. Maria Wirzberger

More Information: UFO Project

Institute for Natural Language Processing

This research focuses on Natural Language Processing applications to support (and understand) deliberative processes (from political discourse to e-deliberation) and the Interpretability (and cognitive plausibility) of Natural Language Processing models.

IRIS Members Involved: Dr. Gabriella Lapesa

More Information: Powering up E-DELIBeration: towards AI-supported moderation

Forschungsprojekte mit SimTech

Project Description

As new technologies sweep the world, they are poised to bring extensive changes that will affect all aspects of our society and life, as well as see organizations increasingly adopt artificial intelligence (AI) to optimize various aspects of their operations. While AI offers new opportunities, it also presents unintended challenges that societal and organizational leaders must carefully navigate. Numerous predictions have been made about the forthcoming AI revolution, ranging from optimistic ones that predict a science fiction utopia driven by nanotechnology and AI, to pessimistic ones that see AI endangering the very survival of human beings, to pragmatic ones that believe AI technologies can be controlled through effective regulation, and finally the doubting ones stating that the AI will never have human-like capabilities and will never become a threat.

This project aims to develop a deeper understanding of systemic structures that govern dynamics of AI adoption within society and organizations, which will help us identify potential risks and opportunities, as well as propose actionable policies that will work for the betterment of our socio-economic systems. We aim to investigate this topic through conceptual analysis supported by systems thinking, system dynamics modeling and computer simulation, and laboratory experiments.

Project Information

Project Name

Reflecting on societal and organizational impacts of AI

Project Leader

Maria Wirzberger

Project Member

Ivan Dula, PostDoc Researcher

Project Partners

Ksenia Keplinger, Independent Research Group “Organizational Leadership and Diversity,”

Max Planck Institute for Intelligent Systems, Stuttgart, Germany


Ðula I, Berberena T, Keplinger K, Wirzberger M (2023) Hooked on artificial agents: a systems thinking perspective. Frontiers in Behavioral Economics.  2:1223281.

Ðula I, Berberena T, Keplinger K, Wirzberger M (2023) Conceptualizing responsible adoption of artificial agents in the workplace: A systems thinking perspective. In 20th Conference of the Italian Chapter of AIS (Association for Information Systems) (21).

Ðula I, Berberena T, Keplinger K, Wirzberger M (2023) Hooked on artificial agents: A simulation study. In International Conference onData-Integrated Simulation Science (SimTech2023). University of Stuttgart. 


09/2022 - 08/2024


The project is funded by the German Research Foundation within the Cluster of Excellence "Data-Integrated Simulation Science" (EXC 2075).


The transmission of infectious diseases depends on human behavior and their relations. However, current epidemiological models consider social structures only at a highly abstract level. To increase the predictive capability and explanatory power, models of human behavior incorporating social complexity are therefore urgently needed. We address this gap by developing an agent-based approach that utilizes comprehensive micro-level data of complete households. This allows us to create artificial societies that are representative for underlying social structures and contact networks. Based on comprehensive COVID-19 data, we then utilize Bayesian model calibration to estimate unknown parameters and quantify their uncertainty. Conducting various simulation experiments will then allow us to identify super-spreaders and assess the efficiency of interventions. Thus, the project makes not only a substantial contribution to a holistic ”Digital Human Model”, but is also a methodological response to the increasing demand for empirically-calibrated simulation models. However, computational models always bear the risk of incorporating biases. We will tackle this challenge, which is enhanced by potential stigmatization of super-spreaders, by incorporating sensitivity analyses and so pave the way for the development of systematic ”methods of reflection”.


07/2022 – 12/2025

Eingebundene IRIS Mitglieder

The project is funded by the German Research Foundation within the Cluster of Excellence "Data-Integrated Simulation Science" (EXC 2075).

IRIS3D - Research Group Leaders

Kontakt: IRIS-Forscher

Dieses Bild zeigt Curtis Runstedler

Curtis Runstedler


Wissenschaftlicher Mitarbeiter

Dieses Bild zeigt Lukas Erhard

Lukas Erhard


Akademischer Mitarbeiter

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