xxAI - Beyond Explainable AI

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science.https://digitalcommons.unomaha.edu/isqafacbooks/1000/thumbnail.jp

xxAI - Beyond Explainable AI

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science

Politeness in Diplomatic Talk: A Thai Case Study

This research starts from the assumption that there are goal-oriented politeness strategies in diplomatic talk. The case study analyses Thai-foreign diplomatic events during Thailand’s national crisis, the massive demonstrations across the country in the years of 2009-2011, in which the colours of the protesters’ clothing signified divergent political allegiances (so-called “colorized politics”). The research aims are threefold: firstly, to characterise politeness strategies in the Thai-foreign diplomatic talks conducted in English; secondly, to examine the extent to which culture-specific values inform the conversational performance of Thai speakers; and thirdly, to explore potential causes of misunderstandings arising from cross-cultural mismatches which occur during these social interactions. The research data are real-time conversations in courtesy calls and international meetings between foreign diplomatic representatives and the leaders of the Thai state and government agencies. My study is influenced by Brown and evinson’s theory along with intercultural communication theories for analysing the ethnographically observed talk-in-action events and transcribed conversational discourse. The research frames a conclusive argument that the diplomatic speakers use both conventional politeness and unconventional politeness strategies. The latter includes what I term ‘lexical politeness’, ‘interactive politeness’, and ‘intercultural politeness’. The Thai party’s politeness strategies in pursuit of diplomatic goals carry an implication of Thai cultural values, specifically: fun-orientation, interdependence, and non-confrontation. Potential pragmatic failures in Thai cultural-oriented politeness are intimacy and directness. The research reveals the suppositions and entailments of English utterances by non-native speakers (Thais) and develops linguistic politeness strategies from the evidence of the diplomatic conversations

xxAI - Beyond Explainable AI

This is an open access book. Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and understandable for humans. Explainable AI is receiving huge interest in the machine learning and AI research communities, across academia, industry, and government, and there is now an excellent opportunity to push towards successful explainable AI applications. This volume will help the research community to accelerate this process, to promote a more systematic use of explainable AI to improve models in diverse applications, and ultimately to better understand how current explainable AI methods need to be improved and what kind of theory of explainable AI is needed. After overviews of current methods and challenges, the editors include chapters that describe new developments in explainable AI. The contributions are from leading researchers in the field, drawn from both academia and industry, and many of the chapters take a clear interdisciplinary approach to problem-solving. The concepts discussed include explainability, causability, and AI interfaces with humans, and the applications include image processing, natural language, law, fairness, and climate science

Strategy and ritual in institutional encounters: a linguistic ethnography of weekly meetings in the British Embassy in Brussels

This study enters the closed and secluded community of a British embassy. It enters a cultural milieu, a setting where a group of self-identifying people with certain shared beliefs engage in a set of distinctive and mutually intelligible practices and tries to gain a more complete understanding of its norms, values and expectations. In particular, it investigates the role of the weekly gathering of Heads of Section as organizational ritual and symbol of collective experience, conveying cultural norms, interpretations and expectations. The work is essentially anthropologically-informed and inspired, while at the same time guided by a profound interest in and concern for language and communication. Apart from linguistics and anthropology, the study relies on and expands upon existing methods and views in a variety of other independently established disciplines. It draws on the sociological writings of Goffman, the philosophical work of Durkheim and Turner, the political ideas of Marx and Weber and many others

Environment 2.0 : the 9th Biennial Conference on Environmental Psychology, 26-28 September 2011, Eindhoven University of Technology, Eindhoven, The Netherlands

On behalf of the Environmental Psychology Division of the German Association of Psychology, the 9th Biennial International Conference on Environmental Psychology is organized by the Human-Technology Interaction (HTI) group of the School of Innovation Sciences of the Eindhoven University of Technology. The HTI group is internationally acclaimed for perception research, and has become established as a major centre of excellence in human-technology interaction research. Bringing together psychological and engineering expertise, its central mission is investigating and optimizing interactions between people, systems, and environments, in the service of a socially and ecologically sustainable society