Bayesian Argumentation via Delphi

Bayesian Reasoning For Better Thinking

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Translation Team UK

Marko Tesic

I am a Ph.D. student in Psychology at the Department of Psychological Sciences, Birkbeck, University of London (principal supervisor: Ulrike Hahn; second supervisor: David Lagnado). Previously, I have received a B.A. degree in Philosophy from the University of Belgrade, Serbia and an M.A. degree in Logic and Philosophy of Science from the Munich Centre for Mathematical Philosophy, Ludwig-Maximilians-Universität, Munich, Germany.

As a part of BARD’s translation team, I am working on probabilistic and causal reasoning. In particular, I am currently interested in how people reason in situations in which two independent causes compete to account for an effect that both could have produced. Experimentally testing how both individuals and groups reason in these kinds of situations should lead to a better understanding of the reasoning processes involved, which in turn could suggests ways to improve people’s reasoning. I also maintain an interest in philosophy of science and argumentation and reasoning, as well as in building and exploring agent-based models of opinion dynamics.

Alice Liefgreen

I completed a BSc Psychology at the University of Bath, which included a 1-year work placement within the clinical forensic psychology team in a prison. Subsequently I completed the MSc Cognitive Neuroscience at UCL and continued working as research assistant within the Memory and Space lab in the year following graduation. I am currently undertaking a PhD supervised by Prof. Lagnado, within the Experimental Psychology department at UCL. Research interests include investigating the psychological processes underlying evidential and causal reasoning, as well as developing a normative framework for optimal information search strategies in a range of contexts, including forensic.

Stephen Dewitt

Stephen Dewitt

Stephen Dewitt is a Research Associate in the Experimental Psychology Department at UCL. He is part of the translation team for the Bayesian ARgumentation via Delphi (BARD) project team and is currently examining the role of prior judgements and prejudice on the incorporation of ambiguous evidence into belief structures. He is also investigating the impact of the surprisal value of evidence on belief updating and the degree to which the incorporation of surprising evidence is undertaken according to normative standards.

Dr Ulrike Hahn

Ulrike Hahn is a co-leader of the Elicitation Team and is based at the Department of Psychological Sciences, Birkbeck, University of London. Ulrike’s research has investigated language and language acquisition, concepts and concept acquisition, and the nature of similarity. Her work presently is focussed on human rationality in judgment, decision-making, and argumentation. Her work utilises both modelling and experimental methods, and she is interested in both descriptive question about how we behave and normative question about how we should behave. She is particularly interested in the role of perceived source reliability on our beliefs, including our beliefs as parts of larger communicative social networks.

Ulrike received her doctorate from the University of Oxford in 1996, has lectured at the psychological departments of Cardiff University and University of Warwick. Since 2012 Ulrike has been a Professor in the Department of Psychological Science at Birkbeck, University of London, where she is also a director of the Centre of Cognition Computation and Modelling.

Ulrike is presently an Associate Editor for Cognitive Psychology and Frontiers in Cognitive Science, a member of the Senior Editorial Board for Topics in Cognitive Science and a Consulting Editor for Cognitive Science and Psychological Review. Ulrike has received the Anneliese Maier Research Award (2014), which is presently funding collaboration with the Munich centre for Mathematical Philosophy. Ulrike was recently awarded fellowships for the Association for Psychological Science (2015) and the German National Academy of Science, Leopoldina (2016), as well as an Honorary Doctorate from Lund University, Sweden (2017).

Prof Martin Neil

Martin Neil is a Professor in Computer Science and Statistics in Queen Mary, University of London and is also a joint founder of Agena. His research interests cover Bayesian modeling and risk quantification in diverse areas. His experience in applying Bayesian methods to real problems has convinced him that intelligent risk assessment and decision analysis requires knowledge and data, not just “Big Data”.

He is interested in intelligent risk assessment and decision analysis using knowledge and data. Typically, this involves analysing and predicting the probabilities of unknown events using Bayesian statistical methods including causal, probabilistic models (Bayesian networks).

In addition to working on theoretical and algorithmic foundations, this work covers a wide range of application domains such as medical analytics, legal reasoning, embedded software, operational risk in finance, systems and design reliability (including software), project risk,commercial risk, decision support, cost benefit analysis, AI and personalization, machine learning, legal argumentation, cyber security and football prediction.

Dr David Lagnado

David Lagnado is Professor of Cognitive and Decision Sciences in the Department of Experimental Psychology at UCL. His research focuses on the psychological processes that underlie learning, reasoning and decision-making. A major theme is the key role played by causal models in cognition. He investigates how people learn causal models from uncertain evidence, and how they use these models for reasoning and attributing responsibility. He also explores the use of Bayesian networks in investigative and forensic contexts, seeking methods to improve people’s reasoning in the face of complex evidence.

Prof Norman Fenton

Norman Fenton is Professor of Risk Information Management at Queen Mary London University and is also a Director of Agena, a company that specialises in risk management for critical systems. Norman, who is a mathematician by training, works on quantitative risk assessment. This typically involves analysing and predicting the probabilities of unknown events using Bayesian statistical methods including especially causal, probabilistic models (Bayesian networks).

Norman’s experience in risk assessment covers a wide range of application domains such as legal reasoning (he has been an expert witness in major criminal and civil cases), medical analytics, vehicle reliability, embedded software, transport systems, financial services, and football prediction.

Norman has a special interest in raising public awareness of the importance of probability theory and Bayesian reasoning in everyday life (including how to present such reasoning in simple lay terms) and he maintains a website dedicated to this and also a blog focusing on probability and the law.

Nicole Cruz De Echeverria Loebell

Nicole is a postdoctoral research fellow, supervised by Ulrike Hahn, within the Elicitation team and is situated at Birkbeck, University of London.

Nicole is completing a PhD thesis which investigates reasoning with uncertain information. In particular, Nicole is investigating when and why people’s reasoning becomes inconsistent, in the sense of departing from the axioms of probability theory, and what factors might lead people to reason in a more consistent way. Nicole aims to investigate these questions through experiments and through Bayesian computational modelling. Nicole is also interested in the extent to which it makes a difference for people whether an inference is inductive or deductive, and in people’s understanding of statements with “if”, “all”, “or”, and “and” (e. g. “if that bird eats flax seeds, then it eats sesame seeds” vs. “all birds that eat flax seeds eat sesame seeds”).

Dr Toby Pilditch

Toby is a Research Associate in the Experimental Psychology department at UCL. He is part of the translation team for the Bayesian ARgumentation via Delphi (BARD) project team, currently working in the domains of evidential, probabilistic, and causal reasoning. He additionally works on topics including communication, belief updating and cognitive biases, exploring the interplay between first and second-hand evidence sources in learning.

Toby also maintains an active interest in building psychologically informed Agent-Based Models, exploring the intersection of cognitive science and dynamic, complex systems. He is an associate member of the Complex Human-Environmental Systems Simulation Laboratory (CoHeSyS) at Oxford University.

Kirsty Phillips

Research Assistant to Ulrike Hahn, situated at Birkbeck, University of London. Recently graduated University College London with a Distinction in Research Methods in Psychology, Msc. Previously worked as an Honorary Assistant Psychologist, NHS, after graduating from Warwick University with a First Class degree in Psychology, BSc (with Honours). Has completed research investigating various fields including phenomenology and content of voice hearing, attitudes towards mental health conditions, and different aspects of attention biases in relation to emotionally valenced stimuli.

The BARD project is funded by IARPA’s CREATE Program