The chapter aims to inform researchers and speech language pathologists on current definitions, key constructs, tenets, available resources, and challenges in the field, serving to tighten the existing, but overall loose, connection between the study of child bilingual phonological development cross-linguistically and the diagnosis, assessment, and therapy protocols in the context of bilingual children’s speech disorder. The chapter provides an overarching review of apposite literature to date, discussing the evolution of terms and key issues, and their relevance in bridging the gap between psycholinguistics research, theory, and clinical practice for bilingual children’s speech sound disorders nowadays. Ultimately, the chapter utilizes existing knowledge to project the canonical perspective that a universal classification of phonological disorders can be informed only by a single mechanism driving its manifestations across children, albeit one that needs to take into consideration every child’s spot on the spectrum of disorder, and on the global map of linguistic and cultural diversity. Gaps and future directions are integrally sketched.

In this concluding chapter, we discuss future directions in law, policy, and regulations for robots that are expressive, humanoid in appearance, becoming smarter, and that are anthropomorphized by users. Given the wide range of skills shown by this emerging class of robots, legal scholars, legislators, and roboticists are beginning to discuss how law, policy, and regulations should be applied to robots that are becoming more like us in form and behavior. For such robots, we propose that human–robot interaction should be the focus of efforts to regulate increasingly smart, expressive, humanoid, and social robots. Therefore, in the context of human–robot interaction, this chapter summarizes our views on future directions of law and policy for robots that are becoming highly social and intelligent, displaying the ability to detect and express emotions, and controversially, in the view of some commentators, beginning to display a rudimentary level of self-awareness.

This chapter aims to present the potential challenges and opportunities brought forth by the integration of care robots within the home- and healthcare services within the Nordic context, stressing the difference between home and conventional or institutional care. In this chapter, we specifically focus on Social and Assistive Robots. Similarly, the chapter aims to discuss if and to what extent these care robots need to be designed for a diversity of users. The chapter suggests Universal Design and accessibility of robots as a potential approach to achieving the care robots’ characteristics of becoming inclusive. Nevertheless, the chapter argues that an inclusive robot approach is important in order to protect the right to health(care), especially if robots will be integrated as part of the home- and/or healthcare services. The chapter exemplifies the need for universal design and accessible robots, as well as the idea of inclusive care robots through empirical work based on a series of interview sessions. Finally, the chapter concludes that: Social and Assistive robots need to be seen in context if such robots are integrated into home- and healthcare services; and that a universal design approach could offer an ethical design charter, a solution, or a guide for designing robots that cater to diverse populations with various situated abilities, considering rights such as the right to healthcare.

Autonomous robots and Artificial Intelligence (AI) are increasingly involved in the commission of criminal offenses, resulting in questions as to who is accountable for such crimes and how human–machine interactions influence criminal responsibility. This chapter first elaborates upon the conditions of machine responsibility and explains why technical systems cannot be granted personhood under today’s criminal law. It then discusses the challenges that complex human–machine interactions bring in terms of the attribution of criminal responsibility, before outlining options regarding how they might be met. Human–machine interactions should be understood as a form of distributed agency. It is therefore essential to define what a legitimate delegation of agency to a machine is. As this chapter shows, this could lead to a modified understanding of the attribution of action under criminal law, or even new norms specifically designed to address automation. Ensuring accountability under criminal law for robots and AI means holding actors accountable who cede agency to such technologies in bad or unjustified ways.

This chapter examines the conceptualization and measurement of contact phenomena in the context of bilingualism across various languages. The goal of the chapter is to account for various phonetic contact phenomena in sociolinguistic analysis, as well as providing context for elaborating on quantitative methodologies in sociophonetic contact linguistics. More specifically, the chapter provides a detailed account of global phenomena in modern natural speech contexts, as well as an up-to-date examination of quantitative methods in the field of sociolinguistics. The first section provides a background of theoretical concepts important to the understanding of sociophonetic contact in the formation of sound systems. The following sections focus on several key social factors that play a major part in the sociolinguistic approach to bilingual phonetics and phonology, including language dominance and age of acquisition at the segmental and the suprasegmental levels, as well as topics of language attitudes and perception, and typical quantitative methods used in sociolinguistics.

Social norms, often described as the “cement” or “grammar” of society, guide human behavior and infuse it with social meaning. In this chapter, we offer a legal perspective on whether robots should be required to adhere to social norms in the context of human–robot interactions (HRIs). To do so, we examine how the mass introduction of social robots may affect existing norms in different contexts, develop a taxonomy of HRIs as they pertain to social norms, and offer a legal-normative framework of analysis to determine whether and to what extent should robots be legally required to adhere to social norms.

This chapter reviews available information on the phonetics and phonology of indigenous language bilinguals published in the last few decades, focusing on both of the bilinguals’ languages, the interplay between their phonological systems, and the phonetic realizations of the sounds present in their languages. We understand indigenous languages as predominantly minority languages spoken by linguistically distinct and often socially marginalized and vulnerable ethnic groups, autochthonous to a specific region of the world, and found in diglossias with majority international languages resulting from colonization. Indigenous language bilingualism is usually small-scale and involves speaking at least one minority indigenous language and at least one majority international language, thus being a step toward a seemingly inevitable language shift and in some cases an eventual indigenous language disappearance. The dynamic and asymmetrical character of indigenous bilingualism, along with the vast number of language combinations and the speaker community size differences between the members of these language pairs, sets it apart from other types of bilingualism considered in this book.

This chapter focuses on the acquisition of segmental phonology in simultaneous bilingual children, highlighting the factors that help explain variability in the pathways toward the construction of language-specific phonological systems. A review of the literature is offered which groups studies by age of participants, a strategy that captures the dynamic nature of the segmental learning processes. It also reveals differences in the methodological approaches for assessing bilingual children’s phonological learning, from the production of their first words to more mature levels of phonological knowledge. As a general view, segmental acquisition seems to be characterized by differentiated but interconnected systems, including realignments along this extended developmental process. However, more nuanced approaches are needed, especially related to the perception–production connection and input quality factors, to reach a more comprehensive view of the acquisition of segmental phonology in young simultaneous bilinguals.

This chapter explores design guidelines and potential regulatory issues that could be associated with future baby robot interaction. We coin the term “robot natives,” which we define as the first generation of human’s regularly interacting with robots in domestic environments. This term includes babies (0–1 year old) and toddlers (1–3 years old) born in the 2020s. Drawing from the experience of other interactive technologies becoming widely available in the home and the positive and negative impact they have on humans; we propose some insights into the design of future scenarios for baby–robot interaction, aiming to influence future legislation regulating service robots and social robots used with robot natives. Similarly, we aim to inform designers and developers to inhibit robot designs which can negatively affect the long-term interactions for the robot natives. We conclude that a qualitative, multidisciplinary, ethical, human-centered design approach should be beneficial to guide the design and use of robots in the home and around families as this is currently not a common approach in the design of studies in child robot interaction.

Romance between a human and robot will pose many questions for the laws that apply to human–robot interaction and, in particular, family law. Such questions include whether humans and robots can marry and what a subsequent divorce might look like. This chapter considers these issues, organized to track the seasons of romantic relationships, such as cohabitation, engagement, and marriage. Given that marriage is no longer devoid of the possibility of divorce, this chapter also considers issues of property division, alimony, child custody, and child support when a marriage between a human and robot dissolves. Even for skeptics of such a future, given rapid advances in robotics, the applicability of family law to relationships between a human and robot is nonetheless an increasingly relevant thought experiment and intersects with other emerging areas of law, technology, and robotics.

The purpose of this chapter is to contribute to the current discussion on what robot laws might look like once artificial intelligence (AI)-enabled robots become more widespread and integrated within society. The starting point of the discussion is Asimov’s three laws of robotics, and the realization that while Asimov’s laws are norms formulated in human language, the behavior of robots is fundamentally controlled by algorithms, that is, by code. Three conclusions can be drawn from this starting point in the discussion of what laws for robots might look like. One is that laws enacted for humans will be translated into laws for robots, which as discussed here, will be a difficult challenge for legal scholars. The second conclusion is that due to the norms which exist within society, the same rules will be simultaneously present in the natural language version of laws for humans and the code version of laws for robots. And the third conclusion is that the translation of the robots’ actions and outputs back into human language will also be a challenging process. In addition, the chapter also argues that the regulation of a robot’s behavior largely overlaps with the current discourse on providing explainable AI but with the added difficulty of understanding how explaining legal decisions differ from explaining the outputs of AI and AI-enabled robots in general.

In this chapter, we thoroughly describe the L2LP model, its five ingredients to explain speech development from first contact with a language or dialect (initial state) to proficiency comparable to a native speaker of the language or dialect (ultimate attainment), and its empirical, computational, and statistical method. We present recent studies comparing different types of bilinguals (simultaneous and sequential) and explaining their differential levels of ultimate attainment in different learning scenarios. We also show that although the model has the word “perception” in its name, it was designed to also explain phonological development in general, including lexical development, speech production, and orthographic effects. The chapter demonstrates that the L2LP model can be regarded as a comprehensive theoretical, computational, and probabilistic model or framework for explaining how we learn the phonetics and phonology of multiple languages (sequentially or simultaneously) with variable levels of language input throughout the life span.