Conference Announcement

Can Algorithms Calculate Morally?

Exploring the Role of Artificial Intelligence in Moral Decision-making

October 10th & 11th 2022, Munich School of Philosophy, Munich, Germany

Algorithms and machine learning have increasingly gained traction in many societal, economic, and political spheres. For instance, we find algorithmic or automatic decision-making in human resource management, policing, autonomous mobility, nursing, or social work. The leading question of this interdisciplinary conference is whether digital tools can or even should play a significant role in situations, in which decisions are morally complicated and riddled with conflicts.

The aim is to identify and discuss fundamental issues at the intersection of ethics, computer studies and social sciences. We strive to examine how we can develop shared strategies and practices within the contexts in which digital tools can be deployed to tackle moral conflicts. We are inviting scholars from various disciplines to create a platform for exchange on algorithmic decision-making in different areas, such as automated mobility, nursing studies, predictive policing, financial services, social services, migration, public administration. Our research project, KAIMo, will contribute their research on the use of digital tools in child welfare services and institutional social settings. Topics include, but are not limited to:

  • Human-machine relations: how do human beings relate to machine intelligence and algorithmic calculations? Can machines be “better decision-makers”? What does it mean to decide moral questions with the help of A.I.? How do we translate moral questions into code? Are there moral machines?
  • Bias and discrimination in algorithms: the problem of inequality and epistemic injustice in algorithmic risk predictions and screenings. How biased is A.I.? Can we debias processes by digital means?
  • (Ethical) requirements for software engineering: how to design tools in an ethical way? What are the requirements to introduce software in an ethically sensitive environment?
  • Data protection, privacy, and responsibility: how to get adequate, representative, and valid data for moral decisions? How much information do we need? How much privacy do we grant participants? Who is responsible for moral decisions?
  • Participation: What is the role of participation? How should the groups that are affected or that must use algorithms participate in their development?

Preliminary program

Human-machine relations

Doris Aschenbrenner
Assistant Prof. Industrial Design Engineering (Technical University Delf)

Standardization Roadmap AI (DIN/DKE), Working Group Socio-Technical Systems

Carolin Wienrich
Juniorprof. Human-Computer-Media (University of Würzburg)

From Understanding to Decision Making: A Holistic View of Competencies and Determinants in
Human-AI Interactions.

Bias and discrimination in data and algorithms

Virginia Dignum
Prof. Computer Science, Social and Ethical AI (Umeå University & Technical University Delft)

Responsible Artificial Intelligence: what it is and why should we care?

Orwat, Carsten, Dr.
Senior Researcher Technology Assessment and Systems Analysis (KIT)

Risks of Discrimination through the use of Algorithms

AI, child wellfare and vulnerability

Kerstin Schlögl-Flierl
Prof. Moral Theology (University of Augsburg)

Beyond the limits? - AI in decision making concerning child endangerment

Maximilian Kraus
Research Associate (University of Applied Sciences Würzburg-Schweinfurt)

KAIMo - Artificial Intelligence applications in child welfare

Social requirements for software engineering

Laura Sartori
Associate Prof. Political and Social Sciences (Universita di Bologna)

The social implications of algorithms and automated decision systems

Christopher Koska, Dr. des.
Senior Researcher KAIMo (Munich School of Philosophy)

Building digital trust. Opportunities and challenges in ethically aligned design

Data protection, privacy, and responsibility

Rainer Mühlhoff
Prof. Ethics and Social Philosophy of the Digital Society (University of Osnabrück)

Predictive Privacy: New data protection challenges in the age of automated inequality

Tanja Henking
Prof. Criminal Law, Medical Law, Medical Ethics (University for Applied Sciences Würzburg)

Ethical and legal aspects with a focus on decisions in medicine


Doris Allhutter, Dr.
Senior Researcher Science and Technology (Austrian Academy of Sciences. Institute of Technology Assessment)

Co-creating Automated Decision-Making in Welfare