area
Cognitive Science
Understanding judgment, belief formation, group cognition, and individual reasoning under uncertainty.
Principal Fellowship Programme 2026
Future of Forecasting: Collective and Artificial Intelligence
Research event convening fellows and participants working on collective intelligence, forecasting, crowd wisdom, and the evolving role of artificial intelligence in decision-making.
research areas
Interdisciplinary perspectives on forecasting and collective intelligence
The programme brings together scholars working across empirical, computational, social, and humanistic approaches to prediction.
area
Social Science
Studying institutions, social dynamics, public opinion, and collective decision-making.
area
Behavioural Economics
Examining incentives, prediction markets, biases, and mechanisms for improving forecasts.
area
The Humanities
Integrating qualitative forecasting rooted in history, political science, epistemology, democracy, interpretive methods, and AI.
core questions
Can collective and artificial intelligence improve forecasting and decision-making — and if so, how?
The workshop will examine both the promise and the risks of emerging forecasting systems.
question 01
Wisdom of Crowds
Can aggregated judgments outperform individual expertise — and if so, how can crowd wisdom be applied across domains?
question 02
AI and Forecasting
How artificial intelligence can democratize forecasting tools while potentially narrowing the diversity of viewpoints.
question 03
Bayesian Truth Serum
How crowd self-reflection and predictions about others' beliefs can improve opinion aggregation and forecasting methods.
abstract
Programme overview
The proposed research event will convene a small group of permanent and invited researchers working on problems of collective intelligence, forecasting, and artificial intelligence. The event will take place over one week, from September 26 to October 3, and will be structured into three parts: Workshop, Core Group Research, and Public Events / Colloquia. During the latter part of the event week, fellows will present their projects to participants and students through the workshop and Public Events / Colloquia, based on the call for applications.
Together, the fellows and participants will bring expertise across several relevant disciplines, including cognitive science, neuroscience, decision-making research, behavioral economics, and management. The core group will also help shape future initiatives related to the future, long-term decision-making, and the challenges of complexity and uncertainty.
The central focus of the event will be on how collective intelligence — also known as crowd wisdom — can be used to improve forecasting and decision-making. The wisdom-of-crowds phenomenon, in which aggregated judgments often outperform those of individual experts, has become a powerful tool for decision-making across numerous domains. Crowd-based aggregation now underpins multi-billion-dollar prediction markets, market research, product design, political polling, and even fact-checking functions at major technology platforms.
A recent and transformative development is the integration of AI into forecasting. While AI has the potential to democratize access to forecasting tools, it may also reduce diversity of viewpoints if forecasters converge on the same AI-generated information.
Understanding the role of AI in forecasting and decision-making will therefore be one of the event's main themes. Another key topic will be the robustness of algorithmically generated forecasts. Much of the current forecasting literature is highly technical and relies on assumptions that may not hold in real-world contexts. As a counterpoint, qualitative forecasting — rooted in humanistic disciplines such as philosophy, epistemology, democracy studies, political science, and interpretive methods — offers a complementary perspective. The event will devote time to examining how these quantitative and qualitative approaches can be meaningfully integrated.
Finally, the event will provide a setting for advancing a suite of projects that extend the range of applications of the Bayesian Truth Serum. The core idea in this approach is to leverage crowd self-reflection — specifically, by asking individuals to predict the crowd's opinion. This approach parallels prediction markets, in which individuals act only when they believe the current price is inaccurate. Bayesian Truth Serum–style techniques have already been applied to opinion aggregation, market research, and political and social polling. The event will address several open challenges in adapting these methods to forecasting.
maritime applications
Forecasting for maritime futures
The programme connects collective intelligence research with real-world maritime challenges through workshops, colloquia, and industry dialogue in Rijeka and Bremen.
industry focus
From collective judgment to maritime foresight.
The programme explores how forecasting methods, collective intelligence, and AI-assisted decision systems can support strategic thinking under uncertainty within maritime industries.
research application
Bayesian Truth Serum–style techniques and collective forecasting models have already been applied to opinion aggregation, market research, and political and social polling. The programme will investigate how similar approaches may be adapted to maritime forecasting and complex industrial environments.
public events
Public Events / Colloquia in Rijeka and Bremen will bring together researchers, students, and maritime stakeholders through lectures, discussions, and presentations focused on forecasting and decision-making under uncertainty.
keynote lecture
The programme will also feature a keynote lecture dedicated to forecasting, uncertainty, ocean systems, and maritime risk analysis.
permanent fellows
Programme leadership
The permanent fellows will anchor the programme and support the development of future initiatives.
permanent fellow
Dražen Prelec
Economics, Brain and Cognitive Sciences, and Sloan School, MIT – permanent fellow
Dražen Prelec is the Digital Equipment Corp. Leaders for Global Operations Professor of Management and Professor of Management Science and Economics at MIT Sloan. His research focuses on decision-making, behavioral economics, neuroeconomics, and methods for evaluating individual and collective judgment.
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Dražen Prelec's research deals with the psychology and neuroscience of decision-making with the psychology and neuroscience of decision-making, including behavioral economics and neuroeconomics, risky choice, time discounting, self-control, and consumer behavior. He works on both the development of normative decision theory and the exploration of the empirical failures of that theory, using behavioral and fMRI methods.
A current project on "self-signaling" tries to understand the power of non-causal motivation — when individuals favor actions that are diagnostic of good outcomes, even though these actions have little or no causal force. A second "Bayesian Truth Serum" project deals with scoring systems for evaluating individual and collective judgment in knowledge domains where no external truth criterion is available.
He was a Junior Fellow in the Harvard Society of Fellows and has received distinguished research awards, including the John Simon Guggenheim Fellowship. Prelec holds an AB in applied mathematics from Harvard College and a PhD in experimental psychology from Harvard University.
permanent fellow
Danica Mijović-Prelec
MIT Sloan
Danica Mijović-Prelec is a Research Scientist and with Drazen Prelec a Co-founder of the Sloan Neuroeconomics Laboratory at MIT, where her work centers on a paradox at the heart of human judgment: how and why we deceive ourselves.
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Danica Mijović-Prelec is a Research Scientist and with Drazen Prelec a Co-founder of the Sloan Neuroeconomics Laboratory at MIT, where her work centers on a paradox at the heart of human judgment: how and why we deceive ourselves. Her research examines self-deception and the denial of evidence, asking how motivated belief shapes everyday judgment in financial, health, and personal decisions. This inquiry is rooted in her earlier clinical work with neurological patients whose denial of illness can take strikingly vivid form. With Dražen Prelec, she developed a self-signaling model of self-deception, published in Philosophical Transactions of the Royal Society B (2010). At the Neuroeconomics Laboratory, she has supervised extensive student research on empirical tests of Bayesian Truth Serum. She holds a B.A. in Clinical Psychology from the University of Belgrade, a D.E.A. in Lacanian Psychoanalysis from the École Freudienne de Paris and Université de Paris VIII, and a Ph.D. in Clinical Neuropsychology from Boston University. She was a McDonnell-Pew Postdoctoral Fellow in Cognitive Neuroscience at Harvard University, and has held research and visiting positions at Massachusetts General Hospital (Harvard Medical School), Stanford University, and the Institute for Advanced Study in Princeton.
Invited Researchers and Lürssen Fellows
invited researcher
Rava da Silveira
Mathematical Cognitive Science, University of Zurich and University of Basel – visiting fellow
Rava Azeredo da Silveira is a researcher working across theoretical neuroscience, cognition, and quantitative approaches to complex systems.
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Rava Azeredo da Silveira is a professor at the University of Basel, a group leader at the IOB, and Head of Mathematical Cognitive Science at the University of Zurich. After completing a B.S. in physics at the University of Geneva and a Ph.D. in theoretical physics at MIT, he was selected as a Junior Fellow of the Harvard University Society of Fellows. He then moved to Paris as a CNRS Chargé de Recherche, subsequently Directeur de Recherche, at the École Normale Supérieure. In parallel, Silveira held visiting professorships at Princeton University, where he was named Global Scholar, and at the Weizmann Institute of Science.
invited researcher
Steve Fleming
Computational Neuroscience and the Max Planck UCL Centre for Computational Psychiatry, University College London – visiting fellow
Steve Fleming is a researcher working on metacognition, subjective experience, and computational psychiatry.
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Steve Fleming is a researcher working on metacognition, subjective experience, and computational psychiatry. He studied Psychology and Physiology at the University of Oxford before completing his PhD at UCL and postdoctoral studies at New York University. His work aims to understand the mechanisms supporting human subjective experience and metacognition by employing a combination of psychophysics, brain imaging, and computational modelling. He is the author of Know Thyself, a book on the science of metacognition.
invited researcher
Yonatan Loewenstein
The Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem – visiting fellow
Yonatan Loewenstein is a researcher working on neuroscience, learning, decision-making, and computational approaches to cognition.
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Yonatan Loewenstein received a B.Sc. degree in physics and a Ph.D. degree in computational neuroscience from the Hebrew University. After a postdoctoral training at the Massachusetts Institute of Technology he became a faculty member at the Hebrew University, working in the departments of Neurobiology, Cognitive Sciences, and the Edmond and Lily Safra Center for Brain Sciences (ELSC), where he heads the Ph.D. program. Yonatan Loewenstein is also a member of Federmann Center for the Study of Rationality at the Hebrew University.
invited researcher
John McCoy
Wharton School, University of Pennsylvania – visiting fellow
John McCoy is a researcher working at the intersection of cognition, decision-making, and collective intelligence.
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John McCoy is an Assistant Professor of Marketing at the Wharton School. His research deals with the processes underlying human judgment and decision making, and applying our knowledge of such processes to problems in marketing. Methodologically, he uses a combination of behavioral experiments and computational modeling, drawing on ideas and techniques from psychology, economics, marketing, Bayesian statistics, and computer science. Much of his current work focuses on better ways to aggregate judgments from multiple individuals, including in situations where the majority may be wrong and the truth may be unverifiable.
invited researcher
Émile Servan-Schreiber
School of Collective Intelligence, University Mohammed VI Polytechnic – visiting fellow
Émile Servan-Schreiber is a cognitive psychologist and technology entrepreneur working on collective forecasting and the wisdom of crowds.
Read full biography
Prof. Émile Servan-Schreiber is a cognitive psychologist and a technology entrepreneur. Since 2000, he has been running the company Hypermind, which designs online platforms for collective forecasting and prioritization. As a scientist he has participated in several large-scale U.S. government research projects on the wisdom of crowds, and he is a founding member of the School of Collective Intelligence at University Mohammed VI Polytechnic (Morocco). Prior to founding Hypermind, he worked as an artificial intelligence engineer and advised the OECD on its "brain and learning" program. He authored the book Supercollectif (Fayard, 2018).
keynote lecture
Keynote speaker
keynote lecture
Themistoklis P. Sapsis, MIT
William I. Koch Professor of Mechanical and Ocean Engineering; Director of the Center for Ocean Engineering
Themistoklis P. Sapsis is the William I. Koch Professor of Mechanical and Ocean Engineering at MIT and Director of the Center for Ocean Engineering. His research focuses on uncertainty quantification, data-driven forecasting, ocean engineering, and the prediction of complex and extreme events in dynamical systems.
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Dr. Sapsis is the William I. Koch Professor of Mechanical and Ocean Engineering at MIT as well as the Director of the Center for Ocean Engineering. He is also affiliated with the Institute for Data, Systems and Society (IDSS) and the Center for Computational Science and Engineering (CSSE), both within Schwarzman College of Computing. He received a Diploma in Naval Architecture and Marine Engineering from Technical University of Athens, Greece and a Ph.D. in Mechanical and Ocean Engineering from MIT. Before his faculty appointment at MIT he served as Research Scientist at the Courant Institute of Mathematical Sciences at New York University. He has also been a visiting faculty at ETH-Zurich. Prof. Sapsis work lies on the interface of nonlinear dynamical systems, probabilistic modeling and data-driven methods. He has received numerous awards including three Young Investigator Awards (Navy, Army and Air-Force research office), the Alfred P. Sloan Foundation Award, the Verisk AI Faculty Research Award, the MathWorks Faculty Research Innovation Fellowship, and more recently the ASME Lloyd Hamilton Donnell Award and the Bodossaki Award on Basic Sciences: Mathematics.
call for applications
Call for Applications
Future of Forecasting: Collective and Artificial Intelligence Workshop
Researchers and students may apply for participation in the scientific event with permanent and invited researchers.
dates
October 1–2, 2026
Workshop at Terminal, Rijeka.
about the workshop
Future of Forecasting Workshop
The workshop brings together experts across multiple disciplines — cognitive science, social science, behavioural economics, and the humanities — to explore the evolving role of forecasting in the coming age of artificial intelligence.
A central theme is the concept of collective intelligence and wisdom of crowd — the idea that the aggregated judgments of groups can outperform individuals, even the experts. This underpins modern applications such as prediction markets, political forecasting, and large-scale decision systems.
A key topic of the workshop will be the integration of AI into forecasting processes as well as decision-making processes in general. While AI has the potential to democratize forecasting and decision-making tools and enhance predictive accuracy, it also raises important questions about information diversity, bias, and reliability.
Invited speakers and Lürssen Foundation Fellow
Lürssen Foundation Fellows
The workshop will feature distinguished researchers, including:
- Dražen Prelec, Economics, Brain and Cognitive Sciences, and Sloan School, MIT – permanent fellow
- Steve Fleming, Computational Neuroscience and the Max Planck UCL Centre for Computational Psychiatry, University College London – visiting fellow
- Yonatan Loewenstein, The Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem – visiting fellow
- John McCoy, Wharton School, University of Pennsylvania – visiting fellow
- Rava da Silveira, Mathematical Cognitive Science, University of Zurich and University of Basel – visiting fellow
- Émile Servan-Schreiber, School of Collective Intelligence, University Mohammed VI Polytechnic – visiting fellow
The workshop will also feature a keynote by Themistoklis P. Sapsis, MIT — William I. Koch Professor of Mechanical and Ocean Engineering; Director of the Center for Ocean Engineering.
who can apply
Researchers
We invite applications from researchers with an interest in the impact of artificial intelligence on collective and individual intelligence, forecasting, and decision-making.
We particularly welcome contributions from cognitive science, social sciences and humanities, behavioural economics, as well as other relevant interdisciplinary areas.
student session
MA and PhD Students
We invite applications from MA and PhD students for the Espresso workshop session, where they will have the opportunity to deliver short presentations of their own work and receive feedback.
requirements
Application Requirements
All applications should include:
- Title and abstract of the proposed presentation, max. 250 words
- A short CV and a brief statement of interest (max. 300–500 words) outlining your research background and motivation for the Principal Fellowship Programme Workshop
benefits
Selected Participants
All selected participants will have the opportunity to learn from and engage with internationally leading researchers. Selected participants also receive:
- Possible Lürssen Foundation Alumni status and continued engagement in future initiatives
- Continued engagement with the Lürssen Foundation scholarship and fellowship programmes
- Full coverage of the conference fee
Participants are expected to cover their own travel and accommodation costs.
selection process
Selection Process
Participants will be selected by a Selection Committee composed of the Lürssen Foundation Permanent Fellows and University of Rijeka research project members, on the basis of academic merit, research quality, and motivation.
how to apply
Submit your application by June 30, 2026
Applications may be sent to:
andrea.mesanovic@luerssen.depublic programme
Public Events
public events
To be announced.
Details of the public programme will be announced soon.