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Research on decisions, models, and data

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Models enable us to comprehend the world, infer beyond the data, and ultimately make better decisions.
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The United Nations report on research by professors Hüseyin Gürkan and Francis de Véricourt

Examining Dissemination of Information on COVID-19
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- United Nations - Academic Impact
Book on AI and Decision Making

Book

Framers
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- by Kenneth Cukier, Viktor Mayer-Schönberger, and Francis de Véricourt
Data

The Economist reports on Prof. Martin Schweinsberg's research

Data don’t lie, but they can lead scientists to opposite conclusions
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- The Economist

The research on decisions, models, and data (DMD) is interdisciplinary research on models, be they mathematical representations, mental models, or other frameworks, to help leaders and their organizations better interpret data, uncover new possibilities, and improve their decision-making. Our approach draws from fields as diverse as data science, analytics, cognitive psychology, sociology, and economics.

The abundance of data and the increasing adoption of intelligent machines raise questions about the future role of human-based decisions in organizations. At the same time, the profound crises the world is experiencing today have highlighted the limits of data-driven predictions and the need to decide even when data are scarce.  

The DMD research is based on the fundamental premise that human decision-makers are most effective when they properly leverage their unique ability to model and represent the world. These models enable inferences beyond the data and reveal new courses of action in a way that machines cannot. The DMD research explores how individuals and organizations can create and apply better models, and how data-driven technologies complement – or hinder – humans’ ability to represent.

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Core areas

Human decisions in the age of artificial intelligence

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Deciding under data scarcity, leading into the unknown

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Governance and responsible analytics

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Disruptive models and innovations

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Projects

No Results Found

Team

Steering committee

  • Francis de Véricourt. Professor of Management Science and President's Chair, ESMT Berlin
  • Gianluca Carnabuci, Professor of Organizational Behavior and Ingrid and Manfred Gentz Chair in Business and Society, ESMT Berlin
  • Henry Sauermann, Professor of Strategy, POK Pühringer PS Chair in Entrepreneurship

 

Faculty members

  • Tamer Boyaci, Professor and Michael Diekmann Chair in Management Science, ESMT Berlin
  • Gianluca Carnabuci, Professor of Organizational Behavior, Ingrid and Manfred Gentz Chair in Business and Society, and Director of Research, ESMT Berlin
  • Francis de Véricourt Professor, Joachim Faber Chair in Business and Technology, and Academic Director of the Institute for Deep Tech Innovation (DEEP), ESMT Berlin
  • Huseyin Gurkan, Assistant Professor of Management Science, ESMT Berlin
  • Henry Sauermann, Professor of Strategy and ESMT Chair in Entrepreneurship, ESMT Berlin
  • Martin Schweinsberg, Assistant Professor of Organizational Behavior, ESMT Berlin

Research associates

  • Ekaterina Gorbunova, ESMT PhD Fellow and Research and Teaching Assistant, ESMT Berlin

Executive Education

  • Nan Guo, Program Director, Executive Education, ESMT Berlin

Schlossplatz 1, 10178 Berlin, Germany