INVESTIGATIONS ON COGNITIVE COMPUTATION AND COMPUTATIONAL COGNITION

This Thesis describes our work at the boundary between Computer Science and Cognitive (Neuro)Science. In particular, (1) we have worked on methodological improvements to clustering-based meta-analysis of neuroimaging data, which is a technique that allows to collectively assess, in a quantitative way, activation peaks from several functional imaging studies, in order to extract the most robust results in the cognitive domain of interest. Hierarchical clustering is often used in this context, yet it is prone to the problem of non-uniqueness of the solution: a different permutation of the same input data might result in a different clustering result. In this Thesis, we propose a new version of hierarchical clustering that solves this problem. We also show the results of a meta-analysis, carried out using this algorithm, aimed at identifying specific cerebral circuits involved in single word reading. Moreover, (2) we describe preliminary work on a new connectionist model of single word reading, named the two-component model because it postulates a cascaded information flow from a more cognitive component that computes a distributed internal representation for the input word, to an articulatory component that translates this code into the corresponding sequence of phonemes. Output production is started when the internal code, which evolves in time, reaches a sufficient degree of clarity; this mechanism has been advanced as a possible explanation for behavioral effects consistently reported in the literature on reading, with a specific focus on the so called serial effects. This model is here discussed in its strength and weaknesses. Finally, (3) we have turned to consider how features that are typical of human cognition can inform the design of improved artificial agents; here, we have focused on modelling concepts inspired by emotion theory. A model of emotional interaction between artificial agents, based on probabilistic finite state automata, is presented: in this model, agents have personalities and attitudes that can change through the course of interaction (e.g. by reinforcement learning) to achieve autonomous adaptation to the interaction partner. Markov chain properties are then applied to derive reliable predictions of the outcome of an interaction. Taken together, these works show how the interplay between Cognitive Science and Computer Science can be fruitful, both for advancing our knowledge of the human brain and for designing more and more intelligent artificial systems

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings

Mobile, intelligent and autonomous policing tools and the law

This thesis resolves around problems arising for the existing legal framework from the use of novel software-­‐based policing tools during criminal investigations. The increasing dependence on information and communication technologies and the Internet means that more aspects of people’s lives move online, and crime follows them. This has triggered the development of innovative, autonomous investigative technologies that are increasingly replacing human officers for the policing of the online sphere. While only recently discussions of the legal status of embodied and unembodied robotical devices have gained more widespread attention, discussions of the legal status of autonomous agent technology are not new. They have focussed however in the past on applications in the private domain, enabling contract formation online. No systematic study has so far been carried out that looks at the use of autonomous agent technology when deployed by state actors, to fulfil core state functions. This thesis starts with the hypothesis that the use of automated, intelligent devices to replicate core police functions in the online world will increase in the future. Looking at first emerging technologies, but with an eye towards future deployment of much more capable software tools that fulfil policing functions on the Internet, this thesis looks at the challenges this poses for regulators and software developers. Based on extensive qualitative research interviews with stakeholders from two different jurisdictions (Germany & UK) this thesis finds that these novel policing technologies challenge existing legal frameworks, which are still premised on the parameters of the offline world. It therefore develops an alternative governance model for these policing tools, which enables their law-­‐compliant use and prevents rights violations of suspects. In doing so it draws upon both worlds, the technical and the legal, while also incorporating the empirical research results from the interviews with experts. The first part of this thesis analyses the technical foundations of these software-­‐based policing tools. Here, one of the key findings is that the current governance system focuses on ex-­‐ante authorisation of very specific, individual software tools without developing a systematic classification. This contradicts the principle of sustainable law making. To overcome this piecemeal approach, as a first contribution to existing research this work defines a new class of investigative technologies – mobile, intelligent and autonomous (MIA) policing tools ‐ based on the findings of the technical analysis. Identifying such a natural class of present and future technologies that pose the same type of legal issues should facilitate the sustainable governance of these new policing tools. The second part of this thesis analyses two specific legal issues: cross-­jurisdictional investigations and the evidentiary value of the seized data. These issues were identified as most pressing by the experts interviewed for this work. This analysis reveals that investigative activities of MIA tools are potentially in conflict with international law principles and criminal procedure law. In order to gain legitimacy, these new policing tools need to operate within the parameters of the existing legal framework. This thesis argues that given the unique technical capabilities of MIA tools, the primary approach to achieving this is to assign legal responsibility to these tools. The third part of this thesis develops a novel governance approach to ensure that MIA tools operate within the parameters of the legal framework, and therefore obtain legitimacy and relevance, also with regard to the investigative results. This approach builds on existing research identifying code as a regulatory modality and contributes to the field of legal theory. It constitutes a solution for the governance problems of MIA tools, however, it requires currently lacking collaboration among stakeholders and cross-­disciplinary research

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings

Word Knowledge and Word Usage

Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines

Predictive embodied concepts: an exploration of higher cognition within the predictive processing paradigm

Predictive processing, an increasingly popular paradigm in cognitive sciences, has focused primarily on giving accounts of perception, motor control and a host of psychological phenomena, including consciousness. But higher cognitive processes, like conceptual thought, language, and logic, have received only limited attention to date and PP still stands disconnected from a huge body of research in those areas. In this thesis, I aim to address this gap and I attempt to go some way towards developing and defending a cognitive-computational approach to higher cognition within the predictive processing paradigm. To test its explanatory potential, I apply it to a range of linguistic and conceptual phenomena. I proceed in three steps. First, I lay out an account of concepts and suggest how concepts are represented, how they can be context-sensitively processed, and how the apparent diversity of formats arise. Secondly, I propose how paradigmatic higher cognitive competencies, like language and logical reasoning, could fit into the PP picture. Thirdly, I apply the PP account of concepts and language to a range of linguistic-conceptual phenomena as test cases, namely: metaphor, the semantic paradox (specifically the Liar Paradox) and copredication. Finally, I discuss some challenges and objections to the PP framework as applied to higher cognition and in general

Abstract book : 25th IVR World Congress of Philosophy of Law and Social Philosophy ; law, science, technology ; 15 – 20 August 2011, Frankfurt am Main, Germany

On behalf of myself and my colleagues Professor Dr. Klaus Günther and Professor Dr. Lorenz Schulz, it is my great pleasure to welcome you to the 25th World Congress of the International Association for Philosophy of Law and Social Philosophy (IVR) in Frankfurt am Main. ...Auch im Namen meiner Frankfurter Kollegen Prof. Dr. Klaus Günther und Prof. Dr. Lorenz Schulz möchte ich Sie zu dem 25. Weltkongress der Internationalen Vereinigung für Rechts- und Sozialphilosophie (IVR) in Frankfurt am Main sehr herzlich begrüßen. ..

Plessner's Philosophical Anthropology. Perspectives and Prospects

Helmuth Plessner (1892-1985) was one of the founders of philosophical anthropology, and his book The Stages of the Organic and Man, first published in 1928, has inspired generations of philosophers, biologists, social scientists, and humanities scholars. This volume offers the first substantial introduction to Plessner’s philosophical anthropology in English, not only setting it in context with such familiar figures as Bergson, Cassirer, and Merleau-Ponty, but also showing Plessner’s relevance to contemporary discussions in a wide variety of fields in the humanities and sciences

The paradox of fiction revisited: a cognitive approach to understanding (cinematic) emotion

The following project is intended as a contribution to the inter-disciplinary enterprise of cognitive film theory. Employing a cognitive approach, the project examines our capacity to respond emotionally to audiovisual fictions in general and cinematic fictions in particular. In order to structure and focus the investigation, the project centres on the paradox of fiction: namely, the question of why and how we respond emotionally to fictional characters and events, especially when we are consciously aware of their fictional - i.e., non-existent - status. (It also considers the related paradoxes of representation and empathy.) The main strategy for solving the paradox is to challenge the proposition that (cinematic) emotions require 'existence beliefs'; in tum, this strategy can be divided into 'direct' and 'indirect approaches', as exemplified by the 'seeing' and 'thought theories' respectively. An additional strategy is to revise the Cartesian framework which underlies the paradox as a whole. The first three main chapters explicitly address the direct approach. The process of direct engagement can be divided roughly into a 'seeing stage' and a 'reacting stage'. In light of this, Chapter 2 outlines a modular and computational view of the mind/brain, considering some of the ways in which we 'see' the world and the cinema. In a corresponding fashion, Chapter 3 outlines a multi-level model of the emotion system from a neurobiological perspective, considering some of the ways in which we 'react' to what we see. The function of Chapter 4 is to develop the multi-level model in question by adopting a connectionist and cognitive perspective, thereby tracing both an associative network and a cognitive appraisal route to (cinematic) emotion. The final main chapter - Chapter 5 - explicitly addresses the indirect approach. Given that appeals to 'thought' and 'imagination' are potentially problematic, it re-traces the simulative route to (cinematic) emotion, demonstrating how the multi-level model acts as both a constraint on, and an alternative to, emotional simulation

Chomskyan (R)evolutions

It is not unusual for contemporary linguists to claim that “Modern Linguistics began in 1957” (with the publication of Noam Chomsky’s Syntactic Structures). Some of the essays in Chomskyan (R)evolutions examine the sources, the nature and the extent of the theoretical changes Chomsky introduced in the 1950s. Other contributions explore the key concepts and disciplinary alliances that have evolved considerably over the past sixty years, such as the meanings given for “Universal Grammar”, the relationship of Chomskyan linguistics to other disciplines (Cognitive Science, Psychology, Evolutionary Biology), and the interactions between mainstream Chomskyan linguistics and other linguistic theories active in the late 20th century: Functionalism, Generative Semantics and Relational Grammar. The broad understanding of the recent history of linguistics points the way towards new directions and methods that linguistics can pursue in the future