The formal sciences, particularly mathematics, have had a profound influence on the development of linguistics. This insightful overview looks at techniques that were introduced in the fields of mathematics, logic and philosophy during the twentieth century, and explores their effect on the work of various linguists. In particular, it discusses the 'foundations crisis' that destabilised mathematics at the start of the twentieth century, the numerous related movements which sought to respond to this crisis, and how they influenced the development of (...) syntactic theory in the 1950s. The book concludes by discussing the resulting major consequences for syntactic theory, and provides a detailed reassessment of Chomsky's early work at the advent of Generative Grammar. Informative and revealing, this book will be invaluable to all those working in formal linguistics, in particular those interested in its history and development. (shrink)

In this paper we explore quarantining as a more ethical method for delimiting the spread of Hate Speech via online social media platforms. Currently, companies like Facebook, Twitter, and Google generally respondreactivelyto such material: offensive messages that have already been posted are reviewed by human moderators if complaints from users are received. The offensive posts are onlysubsequentlyremoved if the complaints are upheld; therefore, they still cause the recipients psychological harm. In addition, this approach has frequently been criticised for delimiting freedom (...) of expression, since it requires the service providers to elaborate and implement censorship regimes. In the last few years, an emerging generation of automatic Hate Speech detection systems has started to offer new strategies for dealing with this particular kind of offensive online material. Anticipating the future efficacy of such systems, the present article advocates an approach to online Hate Speech detection that is analogous to the quarantining of malicious computer software. If a given post is automatically classified as being harmful in a reliable manner, then it can be temporarily quarantined, and the direct recipients can receive an alert, which protects them from the harmful content in the first instance. The quarantining framework is an example of more ethical online safety technology that can be extended to the handling of Hate Speech. Crucially, it provides flexible options for obtaining a more justifiable balance between freedom of expression and appropriate censorship. (shrink)

This article probes the practical ethical implications of AI system design by reconsidering the important topic of bias in the datasets used to train autonomous intelligent systems. The discussion draws on recent work concerning behaviour-guiding technologies, and it adopts a cautious form of technological utopianism by assuming it is potentially beneficial for society at large if AI systems are designed to be comparatively free from the biases that characterise human behaviour. However, the argument presented here critiques the common well-intentioned requirement (...) that, in order to achieve this, all such datasets must be debiased prior to training. By focusing specifically on gender-bias in Neural Machine Translation systems, three automated strategies for the removal of bias are considered – downsampling, upsampling, and counterfactual augmentation – and it is shown that systems trained on datasets debiased using these approaches all achieve general translation performance that is much worse than a baseline system. In addition, most of them also achieve worse performance in relation to metrics that quantify the degree of gender bias in the system outputs. By contrast, it is shown that the technique of domain adaptation can be effectively deployed to debias existing NMT systems after they have been fully trained. This enables them to produce translations that are quantitatively far less biased when analysed using gender-based metrics, but which also achieve state-of-the-art general performance. It is hoped that the discussion presented here will reinvigorate ongoing debates about how and why bias can be most effectively reduced in state-of-the-art AI systems. (shrink)

Dialogue systems, from Virtual Personal Assistants such as Siri, Cortana, and Alexa to state-of-the-art systems such as BlenderBot3 and ChatGPT, are already widely available, used in a variety of applications, and are increasingly part of many people’s lives. However, the task of enabling them to use empathetic language more convincingly is still an emerging research topic. Such systems generally make use of complex neural networks to learn the patterns of typical human language use, and the interactions in which the systems (...) participate are usually mediated either via interactive text-based or speech-based interfaces. In human–human interaction, empathy has been shown to promote prosocial behaviour and improve interaction. In the context of dialogue systems, to advance the understanding of how perceptions of empathy affect interactions, it is necessary to bring greater clarity to how empathy is measured and assessed. Assessing the way dialogue systems create perceptions of empathy brings together a range of technological, psychological, and ethical considerations that merit greater scrutiny than they have received so far. However, there is currently no widely accepted evaluation method for determining the degree of empathy that any given system possesses (or, at least, appears to possess). Currently, different research teams use a variety of automated metrics, alongside different forms of subjective human assessment such as questionnaires, self-assessment measures and narrative engagement scales. This diversity of evaluation practice means that, given two DSs, it is usually impossible to determine which of them conveys the greater degree of empathy in its dialogic exchanges with human users. Acknowledging this problem, the present article provides an overview of how empathy is measured in human–human interactions and considers some of the ways it is currently measured in human–DS interactions. Finally, it introduces a novel third-person analytical framework, called the Empathy Scale for Human–Computer Communication (ESHCC), to support greater uniformity in how perceived empathy is measured during interactions with state-of-the-art DSs. (shrink)

This volume looks at the forms and functions of counterspeech as well as what determines its effectiveness and success from multidisciplinary perspectives. Counterspeech is in line with international human rights and freedom of speech and it can be a much more powerful tool against dangerous and toxic speech than blocking and censorship. In the face of online hate speech and disinformation, counterspeech is a tremendously important and timely topic. The book uniquely brings together expertise from a variety of disciplines. It (...) explores linguistic, ethical and legal aspects of counterspeech, looks at the functions and effectiveness of counterspeech from anthropological, practical and sociological perspectives and addresses the question of how we can use modern technological advances to make counterspeech a more instantaneous and efficient option to respond to harmful language online. The greatest benefit of counterspeech lies in the ability to reach bystanders and prevent them from becoming perpetrators themselves. This volume is an excellent opportunity to spread the word about counterspeech, its potential, importance, and future endeavors. This anthology is a great resource for scholars and students of linguistics, philosophy of language, media and communication studies, digital humanities, natural language processing, international human rights law, anthropology and sociology, and interdisciplinary research methods. It is also a valuable source of information for practitioners and anyone who wants to speak up against harmful speech. (shrink)

Taking Chomsky’s Syntactic Structures as a starting point, this paper explores the use of recursive techniques in contemporary linguistic theory. Specifically, it is shown that there were profound ambiguities surrounding the notion of recursion in the 1950s, and that this was partly due to the fact that influential texts such as Syntactic Structures neglected to define what exactly constituted a recursive device. As a result, uncertainties concerning the role of recursion in linguistic theory have prevailed until the present day, and (...) some of the most common misunderstandings that have appeared in recent discussions are examined at some length. This article shows that debates about such topics are frequently undermined by fundamental misunderstandings concerning core terminology, and the full extent of the prevailing haziness is revealed. An attempt is made, for instance, to distinguish between such things as iterative constructional devices and self-similar syntactic embedding, despite the fact that these are usually both unhelpfully classified as examples of recursion. Consequently, this article effectively constitutes a plea for much greater accuracy and clarity when such important issues are addressed from a linguistic perspective. (shrink)