The topic of reducing uncertainty can be somehow considered *the* task of sciences. In a sense, scientific methodology can be understood precisely as the process of reducing epistemic
uncertainty, allowing one to go from the unknown to the justified. In the Platonic vein, justified true belief was obtained by the Socratic method of investigation of analysis, proceeding by selecting one of analytical, definitional choice of the concept. Logically, truth as an objective notion against which languages and systems are defined, was strengthened by the notion of justification from Intuitionistic Logic. And since the XVII century uncertainty was approached in terms of (game-based, but also chance-oriented) problems involving probabilites, with figures of the kind of Cardano, de Fermat, Pascal. Since then, probabilities have become the major methodology to deal with uncertainty. But in the sciences, and in the computational ones as well, uncertainty is a phenomenon that is manifested, analysed and treated in many ways and under different methodological approaches.
The iTRUS workshop and its topic originate from an informal collaboration between the School of Science and Technology at Middlesex University and the Research Group Savoirs, Textes, Langage of the University of Lille3. A first meeting titled “Methods of objectifying uncertainty” was held at the Maison Européenne des sciences de l’homme et de la société (Lille) in June 2014, with a small investigation group that combined an historically-based philosophical approach to biology (Charles Wolfe (University of Ghent, “Chance between holism and reductionism. Tensions in the conceptualisation of life”) and an analysis of uncertainty as determination of auhtorization control in a logical setting (Giuseppe Primiero (Middlesex University), “Proof theories for access control on resources including trust to eliminate uncertainty”). These two apparently very distant topics were the suggestive conceptual setting to consider uncertainty under the axis of both time and science: how did uncertainty-reduction processes changed across different periods and disciplines?
It was decided that this interdisciplinary methodology could have offered more by strenghtening focus. This workshop is the follow-up to the Lille meeting. The programme focuses on methodological differences in reducing uncertainty, in foundational research and applications, with a stronger focus on the computationl science and their history. The programme presents a combination of expertise from Middlesex University and additional speakers from outside, including University of Lille3, the London School of Economics and the University of Cambridge.
Liesbeth de Mol is fellow of the CNRS at Lille3 University and President of the History and Philosophy of Computing Commission of the Division for the History of Science and Technology (ww.hapoc.org). She is an historian of computing and her contribution will set the stage for the day, with an analysis of formalization and calculation techniques in early computing. She will focus on two historical developments and how they deal with problems of uncertainty and unpredictability, viz., formal logic and computational practices and how within one of the first computers they resulted in different practices that have an impact even
Tomas Petricek is a PhD candidate at the Computer Lab at the University of Cambridge. He combines technical research in programming (in particular, functional programming and type systems) with a deep interest in comparing its methodology to the philsophy of science and its paradigms.
Franco Raimondi is reader in Logic and Multiagent Systems at the Department of Computer Science, Middlesex University. His contribution will focus on recent work in combining subjective and objective probabilites in a doxastic logic setting, with applications to avionics and the use of model checking techniques.
Hykel Hosni is a Marie Curie Research Fellow at the London School of Economics, and an expert in logical foundations of reasoning and decision making. He is the monthly editor of the column “What’s hot in Uncertain Reasoning” in the monthly digest The Reasoner (http://www.thereasoner.org/). His talk will investigate the combination of pure and applied methods and techniques to reduce uncertainty, in a number of key examples connecting various disciplines, including Logic, Mathematics, Decision and Economic Theory, Artificial Intelligence and Philosophy.
Florian Kammueller is Senior Lecturer at the Department of Computer Science, Middlesex University. His contribution, based on joint work with Jaap Boender, Marieta Georgieva Ivanova and Giuseppe Primiero, approaches the problem of modeling the human component in technical systems with a view on the difference between the use of model and theory in sociology and computer science and an application to the uncertainty of user identification in modelling insider threats as a Higher Order Logic theory in Isabelle/HOL.
Chris Rooney is a Researcher at the Department of Computer Science, Middlesex University. He will report on problems related to data representation and uncertainty reduction in the VISUAL ANALYTICS FOR SENSE-MAKING IN CRIMINAL INTELLIGENCE ANALYSIS Project (VALCRI), funded under FP7 (http://www.valcri.org/).
Written by Dr. Giuseppe Primiero