Recent robotics, AI, and human–robot interaction techniques increasingly improve the capability of social robots. Yet, there seems to be the lack of important capabilities of social robots for their more substantial use. This chapter specifically focus on mobile social robots that would be used for service industry. We introduce some of the technical advancement about the basic social capabilities for mobile social robots, such as how social robots should consider human personal space, approach people, crossing with human pedestrians, and harmonized with crowd of people. Then, we discuss the moral-related issues with social robots, particularly, robot abuse problem. The fact that children treat social robots aggressively and even violently indicates the lack of peer respect for them. Here, we discuss what the future social robots would need to be equipped, and argue for the needs of “moral interaction” capability. Two capabilities, peer respect and peer pressure, are discussed. That is, social robots would need to elicit people to consider them as a kind of moral recipient (peer respect), and elicit people to behave good (peer pressure) in a way similar to “human eyes” would work. We introduce some of recent research works for moral interaction capability. Finally, we discuss the future implications on law and regulations if much more moral interaction capabilities will be equipped for social robots in the future.

Spoken word recognition is an automatic and smooth everyday process for most of us in our first language (L1), but it can be challenging in a second language (L2). Bilinguals’ recognition of spoken L2 words is characterized by L1 interference in how words are phonologically encoded in the mental lexicon, and how they are activated during comprehension. This chapter provides an overview of phonological processing during spoken word recognition in bilinguals, describing how phonological knowledge in L1 impacts the processing of native and non-native speech for various phonological dimensions. The chapter then surveys major experimental findings in L2 phonological perception and lexical access processes, highlighting the connection between the two, and showing that the phonolexical representations created by L2 learners are L1 influenced. This survey is contextualized by an outline of the various “forces” that further shape processing (e.g. orthography, vocabulary size, or lexical factors). Finally, the chapter outlines how L2 phonological processing develops over time, and how learners succeed at optimizing their processing and creating more target-like phonolexical representations.

This chapter discusses the topic of ethics, law, and policy as related to human interaction with robots which are humanoid in appearance, expressive, and AI enabled. The term “robot ethics” (or roboethics) is generally concerned with ethical problems that occur when humans and robots interact in various social contexts. For example, whether robots pose a threat to humans in warfare, the use of robots as caregivers, or the use of robots which make decisions that could impact historically disadvantaged populations. In each case, the focus of the discussion is predominantly on how to design robots that act ethically toward humans (some refer to this issue as “machine ethics”). However, the topic of robot ethics could also refer to the ethical issues associated with human behavior toward robots especially as robots become active members of society. It is this latter and less investigated view of robot ethics that the chapter focuses on, and specifically whether robots that are humanoid in appearance, AI enabled, and expressive will be the subject of discrimination based on the robot’s perceived race, gender, or ethnicity. This is an emerging topic of interest among scholars within law, robotics, and social science and there is evidence to suggest that biases and other negative reactions which may be expressed toward people in social contexts may also be expressed toward robots that are entering society. For these and other reasons presented within the chapter, a discussion of the ethical treatment of robots is an important and timely topic for human–robot interaction.

Computational models allow researchers to formulate explicit theories of language acquisition, and to test these theories against natural language corpora. This chapter puts the problem of bilingual phonetic and phonological acquisition in a computational perspective. The main goal of the chapter is to show how computational modeling can be used to address crucial questions regarding bilingual phonetic and phonological acquisition, which would be difficult to address with other experimental methods. The chapter first provides a general introduction to computational modeling, using a simplified model of phonotactic learning as an example to illustrate the main methodological issues. The chapter then gives an overview of recent studies that have begun to address the computational modeling of bilingual phonetic and phonological acquisition, focusing on phonetic and phonological cues for bilingual input separation, bilingual phonology in computational models of speech comprehension, and computational models of L2 speech perception. The chapter concludes by discussing several key challenges in the development of computational models of bilingual phonetic and phonological acquisition.

This chapter introduces the problem of regulating human–robot interaction (HRI) according to the rule of law in the convergence of the Web of Data, the Internet of Things, and Industry 5.0. It explains some strategies fleshed out in the EU H2020 Project OPTIMAI, a data-driven platform for zero-defect manufacturing (ZDM) to deploy a smart industry ecosystem. The chapter defines the notions of legal governance and smart legal ecosystems as a mindset and as a toolkit to foster and regulate HRI in iterative cycles.

Adults undertaking the endeavor of learning a new language can attest to the difficulty involved with producing the sounds and prosody of the target language. A principal aim of research on adult speech production is to comprehend the mechanisms and processes that differentiate adult bilingual speech development from bilingual speech that develops earlier in life. It is clear that individuals who learn an additional language in adulthood typically encounter some difficulties that early learners do not. In particular, these difficulties arise at the segmental level when acquiring novel sound categories and novel sound contrasts, as well as at the suprasegmental level when learning to produce non-native prosodic structures related to intonation, stress, rhythm, tone, and tempo. The present chapter provides a selective overview of the current state-of-the-art in adult bilingual speech production. Furthermore, this chapter considers theoretical and methodological areas for improvement, as well as avenues for future research.

Recently there has been more attention to the cultural aspects of social robots. This chapter contributes to this effort by offering a philosophical, in particular Wittgensteinian framework for conceptualizing in what sense and how robots are related to culture and by exploring what it would mean to create an “Ubuntu Robot.” In addition, the chapter gestures toward a more culturally diverse and more relational approach to social robotics and emphasizes the role technology can play in addressing the challenges of modernity and in assisting cultural change: It argues that robots can help us to engage in cultural dialogue, reflect on our own culture, and change how we do things. In this way, the chapter contributes to the growing literature on cross-cultural approaches to social robotics.

This chapter examines from a theoretical perspective the role of interface in the formation of trust in HR interaction, notably between humans and humanoid robotic agents. Interfaces are fundamental means of communication that do not only allow interaction between different agents but they also enable them to exchange information on the nature of the context in which the interaction takes place: This can facilitate the formation of a trust relationship between agents, whether they are human or robotic, within a more or less structured context. The chapter concludes with a discussion of the pivotal role of human–robot interfaces as essential means of communication from the analysis displayed in my contribution.

Evidence that listeners attend to and track subphonemic phonetic details is indicated by listeners’ ability to reliably connect subphonemic variation and, often, socio-indexical associations in ways that align with the patterns realized in production. Bilinguals are presented with the task not only of associating within-language variation (e.g., social group X is connected to a particular range of phonetic realizations within language Y) but also of attending to how ethnolects and bilingually accented speech index social categories across languages. Having access to multiple languages also gives bilingual speakers a larger repertoire with which to index language- and community-specific social meaning. This chapter outlines the linguistic structures bilinguals may connect across their languages and then presents a specific exemplar model, noting the opportunities within the model’s structure for bilingual dynamics. The heterogeneity of bilingual individuals and speech communities is necessarily addressed, as this dynamic adds to the complexity and intrigue of studying bilingual populations.

After researching for years the law and ethics of robotic systems in the security sector, that is, defense, law enforcement, and disaster relief, we present a set of eight recommendations bearing on human–robot interaction. These recommendations should guide developers, lawyers, ethicists, and policymakers who navigate a highly technical and dynamic field. Our eight recommendations boil down to the following: In circumstances where technology develops rapidly while normative discussions fail to keep up and uncertainty prevails, we suggest a pragmatic, practical, and dynamic form of applied ethics to those involved with robotics – an ethics that eschews high politics at first, but ultimately produces experience that can be fed back into higher-level normative discussions on robots and technology more generally and thus move them forward.

This chapter reviews the last twenty-five years of L2 prosody research in three sections, word stress, sentence intonation, and rhythm, and presents findings in relation to two underlying themes, form-meaning mapping and additive versus subtractive bilingual contexts. Concerning L2 stress, pioneering research framed perception difficulties either as an L1-to-L2 cue-transfer problem or as a processing deficit linked to learners’ inability to represent contrastive stress in their lexicons. Recent research established the extent and limits of those initial frames. L2 sentence intonation has multiple factors modeling its variation. One of them, social meaning, and in particular accommodation literature revealed the effect of affective factors which in multilingual communities became stronger than that of linguistic and social factors. As regards L2 rhythm, most research uses duration-based measures. Indeed, recent L1 studies started examining pitch-based rhythm measures which are still to be explored in L2. Ending with suggestions for future research that address those biases, this chapter aims at promoting a more inclusive and comprehensive understanding of L2 prosody.

Psycholinguistic theories conceptualize the mind as a set of mechanical processes that map between levels of mental representation. Cognition is seen as a form of computation, emerging from the interaction of these processes. We explore how this conceptualization frames psycholinguistic research questions. We first examine how the idea of “mind as computer” leads psycholinguists to examine two broad types of questions. Some studies focus on the structure of mental representations (e.g., are “similar” speech sounds associated with one vs. two representations across languages?). Others focus on the number and nature of processes underlying behavior (e.g., to what extent do speech perception and speech production rely on distinct vs. shared processes?). We then turn to connectionism, a specific computational framework that has dominated psycholinguistic theories of bilingualism. Connectionism’s conceptualization of processing as spreading activation has driven studies of representation and processing. We conclude by considering how psycholinguistic theories can inform as well as be informed by other perspectives

The interaction between bilingual phonetic systems is dynamic, shaped by both long-term and short-term factors. Short-term factors, the focus of this chapter, refer to immediate changes in the linguistic situation. This chapter discusses two short-term sources of potential phonetic interference: code-switching and bilingual language mode. A growing body of research on the phonetics of code-switching has shown that code-switching may result in phonetic interference between the L1 and the L2, although outcomes may vary across speakers and features. Language mode describes a bilingual’s position along a continuum, from operation in a monolingual mode, in which only one language is active, to bilingual mode with equal activation of both languages. Recent work has demonstrated that language mode may modulate cross-linguistic phonetic interference, with greater interference found during bilingual mode. Finally, this chapter discusses two variables responsible for modulating and constraining phonetic interference in cases of dual language activation that have emerged in the literature – the nature of the phonetic feature and bilingual language dominance.

The use of advanced robots interacting with humans, especially in the health and care sector, will interfere with the personal autonomy and privacy of the users. A person can give permission to such interference by giving their consent. In law, the term “consent” has different connotations dependent on the field of law and jurisdictions. A recurrent topic in robotics research is how consent can be implemented in human–robot interaction (HRI). However, it is not always clear what consent actually means. The terms “informed consent” and “consent” are used interchangeably with an emphasis on informational privacy, whereas the embodiment of robots also intervenes with “physical” privacy. This lack of nuance leads to misconceptions about the role consent can play in HRI. In this chapter, I critically examine the perception and operationalization of consent in HRI and whether consent is an appropriate concept at all. It is crucial for the adaptation of consent to understand the requirements for valid consent, and the implications consent have for deployment of robots, in particular in a health and care setting. I argue that valid consent to the use of AI-driven robots may be hard, if not impossible, to obtain due to the complexity of understanding the intentions and capabilities of the robot. In many instances, consent would not be appropriate in robotics because it would not be possible to have truly informed and free consent beyond a simple “yes” or “no.” This chapter is a critical analysis that builds on the extensive scholarly critique of consent. As the chapter shows, robotics is yet another field where the shortcomings of consent are salient.

This chapter assesses EU Consumer law and Policy in the light of consumers’ increasing interaction with humanoid robots. Amidst the plethora of benefits that humanoid robots can bring to consumers, they can also challenge the application of consumer protection principles. The biggest problems lie in the areas of protection of the weaker party, consumer autonomy, nondiscrimination, and privacy. Consumers may face difficulties ranging from exposure to unfair commercial practices, difficulties in exercising their rights under the Consumer Rights Directive, in claiming damages for AI-related losses under the Product Liability Directive, in exercising the rights – for example, to consent, to be forgotten, to be informed, not to be profiled – under the General Data Protection Regulation, and in avoiding being discriminated by credit scoring systems under the Consumer Credit Directive. The chapter explores the sufficiency of EU legislation to tackle the wide range of challenges and proposes targeted regulatory action. The rationale behind addressing these issues is to strike a balance between consumer protection and innovation in robotics.

When the idea of a robot butler or maid started to spread, Rosie from the Jetsons became a symbol for a vision shared by many roboticists: One day, each household would have a robotic helper that takes care of our chores and keeps us company. However, when we examine the realities of robots produced for the consumer market today (from autonomous cars to social robots), we discover that realizing such a future with robots is not all that rosy for consumers. From a property law perspective, we find that most consumers will only partially own the robots they purchase. The software that gives life, functionality, and character to the robots will likely be owned by the manufacturer, who can take it all away from the purchasers just as easily as they can change subscription fees and user terms and conditions. In this chapter, we draw analogies from the automotive industry and current business trends in the consumer robotics market to underscore seven issues that stem from this precarious ownership dynamic. Reflecting on our collective journey toward “a robot in every home,” we highlight how the status quo is not only unsustainable from an environmental perspective (i.e., generation of electronic waste) but also ineffective in generating a flourishing consumer robotics market. We find that the existing roboethics and AI ethics frameworks do not sufficiently protect consumers from these issues and call on the community to critically examine the complex ethical and societal implications of deploying social robots widely.