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Human opacity is the intrinsic quality of unknowability of human beings with respect to machines. The descriptive relationship between humans and machines, which captures how much information one can gather about the other, can be explicated using an opacity-transparency relationship. This relationship allows us to describe and normatively evaluate a spectrum of opacity where humans and machines may be either opaque or transparent. In this paper, we argue that the advent of Affective Computing (AC) has begun to shift the ideal position of humans on this spectrum towards greater transparency, while much of this technology is shifting towards opacity. We explore the implications of this shift with regard to the affective information of humans and how the threat to human opacity by AC systems has various adverse repercussions, such as infringement of one's autonomy, deception, manipulation, and increased anxiety. There are also distributive consequences that expose vulnerable groups to unjustified burdens and reduce them to mere profiles. We further provide an assessment of current AC technology, which follows the descriptive relationship between humans and machines from the lens of opacity and transparency. Finally, we foresee and address three possible objections to our claims. These are the beneficence of AC systems, their relation to privacy, and their restrictive capacity to capture human affects. Through these arguments, the paper aims to bring attention to the ontological relationship between humans and machines from the perspective of opacity and transparency while emphasizing on the gravity of the ethical concerns raised by their threat to human opacity. [ABSTRACT FROM AUTHOR]

The U.S. National Science Foundation (NSF), together with other federal agencies, launched the National Robotics Initiative (NRI) program in 2011. The aim of the NRI is to accelerate the development and use of collaborative robots (corobots), which work beside or cooperatively with people. To date, the NRI program has involved multiple directorates of the NSF (Computer and Information Science and Engineering; Engineering; Social, Behavioral, and Economic Sciences; and Education and Human Resources) and several other federal research funding agencies [the U.S. Department of Agriculture (USDA), the National Institutes of Health (NIH), the U.S. Department of Energy (DOE), NASA, and the U.S. Department of Defense (DOD)]. As the program prepared to announce its sixth round of awards in the summer of 2017, we took the opportunity to reflect on the impacts of the first five years of NRI funding. [ABSTRACT FROM AUTHOR]

Several prominent criticisms have recently challenged the possibility of algorithmically determining or recognising human affect. This paper ethically evaluates one underexplored avenue for overcoming such deficiencies in categorical affect recognition technologies (ARTs). Specifically, the emerging literature on “situated affectivity” offers valuable guidance on three fronts. First, it conceptually substantiates existing criticism by stressing the contextual dimensions of human affect. Second, in highlighting the breadth of information required for more accurate ARTs, it suggest that they may necessitate penetrating forms of surveillance the ethical literature has already provided good reason to resist. Third, it corroborates postphenomenological insights concerning the socially co-constituting character of technology; and thereby grounds the need for a “situated ethics” sensitive to the ways that ARTs might reconstruct human affectivity (and reinforce existing power hierarchies). The deep worry is that this concern is likely to persist even if concerns over accuracy and surveillance are mitigated. A detailed consideration of this novel ethical concern suggests that the ethically acceptable use of ARTs may only be possible in highly contained settings. Yet doubts over such containment places advocates of ARTs in a “double bind” they need to address. [ABSTRACT FROM AUTHOR]

Video games are one of the richest and most popular forms of human-computer interaction and, hence, their role is critical for our understanding of human behaviour and affect at a large scale. As artificial intelligence (AI) tools are gradually adopted by the game industry a series of ethical concerns arise. Such concerns, however, have so far not been extensively discussed in a video game context. Motivated by the lack of a comprehensive review on the ethics of AI as applied to games, we survey the current state of the art in this area and discuss ethical considerations of these systems from the holistic perspective of the affective loop. Through the components of this loop, we study the ethical challenges that AI faces in video game development. Elicitation highlights the ethical boundaries of artificially induced emotions; sensing showcases the trade-off between privacy and safe gaming spaces; and detection, as utilised during in-game adaptation, poses challenges to transparency and ownership. This paper calls for an open dialogue and action for the games of today and the virtual spaces of the future. By setting an appropriate framework we aim to protect users and to guide developers towards safer and better experiences for their customers. [ABSTRACT FROM AUTHOR]

In recent years, many agent-based models of human groups have implemented a mechanism of emotion contagion, yet empirical validation is lagging behind. The aim of the present paper is to validate an agent-based model of emotion contagion at the level of group emotion, by comparing simulations against the emotional development of real people in small groups. To study the effect of emotion contagion, the participants interacted via a video call, where they were virtually placed in different social environments while they played a quiz. This allowed the exchange of emotion among all, some or none of the participants. The patterns of emotional development in the empirical results supported our hypotheses based on literature of emotion contagion and social norms. Further, the simulations with the complete model resembled many of these patterns. When emotion contagion was disabled in the model, the resemblance decreased. These results give a first indication that emotion contagion occurs in groups that meet via video calls, and can in-part be predicted by the proposed model of emotion contagion. Yet, further study with a larger and more diverse empirical sample is needed, as well as comparisons across contagion mechanisms, to draw stronger conclusions and ultimately justify societal application. [ABSTRACT FROM AUTHOR]

This work presents a longitudinal study of diversity among the Affective Computing research community members. We explore several dimensions of diversity, including gender, geography, institutional types of affiliations and selected combinations of dimensions. We cover the last 10 years of the IEEE Transactions on Affective Computing (TAFFC) journal and the International Conference on Affective Computing and Intelligent Interaction (ACII), the primary sources of publications in Affective Computing. We also present an analysis of diversity among the members of the Association for the Advancement of Affective Computing (AAAC). Our findings reveal a “leaky pipeline” in the field, with a low –albeit slowly increasing over the years– representation of women. They also show that academic institutions clearly dominate publications, ahead of industry and governmental centres. In terms of geography, most publications come from the USA, contributions from Latin America or Africa being almost non-existent. Lastly, we find that diversity in the characteristics of researchers (gender and geographic location) influences diversity in the topics. To conclude, we analyse initiatives that have been undertaken in other AI-related research communities to foster diversity, and recommend a set of initiatives that could be applied to the Affective Computing field to increase diversity in its different facets. The diversity data collected in this work are publicly available, ensuring strict personal data protection and governance rules. [ABSTRACT FROM AUTHOR]

Thanks to the many submissions we have received, we can present this second part of our special issue on "AI-eXplained." In here, we continue our mission to demystify the intricate world of artificial intelligence and make it accessible to a broader audience. As AI continues to evolve and integrate into various aspects of our lives, it becomes increasingly important to bridge the gap between experts and those eager to understand the inner workings of AI systems. Our goal remains unchanged—to present AI concepts in a comprehensible, engaging, and interactive manner, empowering our readers to explore and grasp the enchanting world of AI. [ABSTRACT FROM AUTHOR]

We address the problem of merging probabilistic knowledge in a centralized (nonflat) multiple participant system. Each participant independently reports a known distribution of a common quantity of interest to an extra participant, called the deliberator. The deliberator’s task is the optimal design of a compromise distribution, which seeks to minimize the expected loss imposed on each of the participants. We formulate this task as one of Bayesian decision-making, and solve it using fully probabilistic design. Solutions are currently available for discrete distributions only. In this paper, we provide two novel contributions. First, the deliberator’s unknown distribution is parametric on a continuous support. Second, the scheme adopts a hierarchical model for the deliberator, optimizing the deliberator’s parameter prior. This allows quantification of the deliberator’s uncertainty in their model choice. We formulate conditions under which a conjugate design is achieved, and provide an example where the design is analytically tractable. Extensive simulation-based evidence is reported, pointing to the significantly enhanced performance of our framework over logarithmic pools. [ABSTRACT FROM PUBLISHER]

This article reviews aspects of academic and scientific publishing, primarily in the context of IEEE publications and policies. The intent is to provide a brief tutorial for those new to academic publishing. The material on publication ethics and the IEEE's associated policies should be useful to all, including those experienced with academic publishing. The types of IEEE publications and what they publish are reviewed. The importance of a publication's scope is explained, and publication and author metrics are examined. The steps in the publication process are described in detail, along with the roles of the Editor-in-Chief (EiC), associate editors, reviewers, and authors. Ethical issues and the principles of scholarly publishing are examined, including authorship and the responsibilities of authors, duplicate submission and publication, and plagiarism. [ABSTRACT FROM PUBLISHER]

This study analyzes the value conflict of a paper on fan fiction writing that used online fan fiction novels as a source to extract and filter sexual expressions from text. The boundaries of public and private information are ambiguous because users are not always aware of or have agreed to the fact that their content is to be used openly. The case was complicated by the fact that the use of these data by researchers violated an unconsciously infringed upon right of a vulnerable community with a weak legal position. This paper describes the debate on this topic among researchers from engineering and humanities fields on whether the purpose of the research was ethically acceptable; how the systems can be embedded in ethical values; and what ethical, legal, social, and educational lessons are appropriate for governance of artificial intelligence (AI). Our analysis aimed not only to clarify the abstract concept of privacy but also to make changes to the submission guidelines for authors. We hope that our analysis contributes to the governance of ethical AIs and AI ethics on handling sensitive aspects of online activities. [ABSTRACT FROM AUTHOR]

Ethical understanding aims at morally analyzing and discriminating ethical scenarios described in natural language. By classifying behaviors that occur in ethical scenarios as ethical or unethical, ethical understanding empowers artificial intelligence systems to understand human values so as to discern right from wrong morally. However, most existing ethical understanding methods lack fine-grained analysis and cannot handle the problem that an ethical scenario may contain multiple behaviors with multiple polarities. In this paper, we introduce a novel natural language processing task, behavior-based ethical understanding (BEU), for mining the purpose relation(s) and ethical polarity of a specific behavior from the social news. It contains three subtasks: behavior term extraction (BTE) to extracts behavior terms, purpose relation inference (PRI) to identifies purposive relations among behaviors, and polarity discrimination (PD) to predicts the ethical polarities of behaviors, respectively. To perform this task, we constructed a Chinese BEU dataset, named FG-ETHICS. Besides, we propose a three-stage framework, BEU-BERT, based on the pre-trained language model BERT and deliberately designed downstream models for three subtasks. Experimental results show that the proposed framework achieves the best performance from the BTE and PD tasks, and achieves a promising performance of 75% on the PRI task. [ABSTRACT FROM AUTHOR]

After 20 years of testing a framework for affective user responses to artificial agents and robots, we compiled a full formalization of our findings so to make the agent respond affectively to its user. Silicon Coppélia as we dubbed our system works from the features of the observed other, appraises these in various domains (e.g., ethics and affordances), then compares them to goals and concerns of the agent, to finally reach a response that includes intentions to work with the user as well as a level of being engaged with the user. This ultimately results in an action that adds to or changes the situation both agencies are in. Unlike many other systems, Silicon Coppélia can deal with ambiguous emotions of its user and has ambiguous ‘feelings’ of its own, which makes its decisions quite human-like. In the current paper, we advance a fuzzy-sets approach and show the inner workings of our system through an elaborate example. We present a number of simulation experiments, one of which showed decision behaviors based on biases when agent goals had low priorities. Silicon Coppélia is open to scrutiny and experimentation by way of an open-source implementation in Ptolemy. [ABSTRACT FROM AUTHOR]

Codes of ethics provide a critical foundation for an organization to define the tenets that best reflect their values. These codes provide a touchstone for employees to follow that establishes trust between an organization and their customers and key stakeholders. The rapid acceleration of autonomous and intelligent systems (A/IS) has created an imperative for technologists to complement these codes with new methodologies focused on the widespread implementation of ethical considerations in all levels of design and manufacture. This paper describes IEEE’s work in this arena, including the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, the IEEE TechEthics program, the IEEE P7000 Standards Series focused on A/IS issues, Digital Inclusion through Trust and Agency, and the ongoing work of the IEEE Society on Social Implications of Technology. This paper also includes a table of approximately 50 activities within the IEEE related to ethics. [ABSTRACT FROM AUTHOR]

This paper surveys reasons for and against pursuing the field of machine ethics, understood as research aiming to build “ethical machines.” We clarify the nature of this goal, why it is worth pursuing, and the risks involved in its pursuit. First, we survey and clarify some of the philosophical issues surrounding the concept of an “ethical machine” and the aims of machine ethics. Second, we argue that while there are good prima facie reasons for pursuing machine ethics, including the potential to improve the ethical alignment of both humans and machines, there are also potential risks that must be considered. Third, we survey these potential risks and point to where research should be devoted to clarifying and managing potential risks. We conclude by making some recommendations about the questions that future work could address. [ABSTRACT FROM AUTHOR]

This book comprises a selection of papers presented at the IPET 2008 symposium that took place at the Royal Academy of Engineering in London in November 2008 and at the following workshop at the Colorado School of Mines. It is the second volume in a series that emanated from a workshop on Philosophy in Engineering that took place at the University of Delft in October 2007 and that began a continuing series of workshops named by the acronym IPET followed by the year of the workshop. Prior to that, there had been three significant publications that had illustrated the value of pursuing the relationship between philosophy and engineering, and engineering education. The success of this 2007 University of Delft workshop led to IPET 2008 being held at the Royal Academy of Engineering in London. While the focus of both volumes is on engineering, necessarily many of the papers have implications for engineering education. It would be surprising if the three individuals invited to review this book were able to agree upon a conclusion. They did indeed have different views; this seems to be because their views differed of who was likely to read this book. A reader may infer the editors? intentions from the questions put to Mitcham, but it is harder to infer the intended audience. One of the reviewers takes the view that a collection of papers of the calibre presented will attract a like-minded set of readers, and so responded to the questions put to Mitcham with that group in mind. Another thought the book would be suited to engineering educators more generally, and as a result was effusive in its praise. The fundamental questions that need to be answered are ?What value do these papers have for engineering educators?? and ?What value do they have for their students?? While the editors have not focused on engineering and technological literacy, a number of chapters are of considerable importance to those who promote study in these areas. The chapters on peace engineering and the use of robotics in warfare are examples of this. Of the series of papers on the philosophy of technology adoption over the last two decades, some are summarized in Ch. 23 by Houkes and Pols. This chapter focuses on the designer?user system in terms of what the authors' call Rational Acceptance Technology (RAT), one aspect of which is control. They point out that in designing artefacts, designers hand over a measure of control to the users. RAT requires that the user has partial responsibility for failure. For instance, guarantees and insurance for domestic electrical goods are careful to note improper use as an exclusion from the guarantee. From the reviewers' perspective, the answer to the first of the questions put to Mitcham is that this volume contributes to the establishment of a philosophy of engineering. It now requires an authority to provide a synthesis of the numerous articles that have been published in this area with that in mind. A good starting point would be for the organizers of these and similar workshops to call for some focused review papers, to which the reviewers and readers of this book can look forward to with great anticipation. [ABSTRACT FROM PUBLISHER]

In current wireless communication systems, there is a rapid development of location based services, which will play an essential role in the future 5G networks. One key feature in providing the service is the mobile crowdsourcing in which a central cloud node denoted as the principal collects location based data from a large group of users. In this paper, we investigate the problem of how to provide continuous incentives based on user’s performances to encourage users’ participation in the crowdsourcing, which can be referred to the moral hazard problem in the contract theory. We not only propose the one-dimensional performance-reward related contract, but also extend this basic model into the multi-dimensional contract. First, an incentive contract which rewards users by evaluating their performances from multiple dimensions is proposed. Then, the utility maximization problem of the principal in both one-dimension and multi-dimension are formulated. Furthermore, we detailed the analysis of the multi-dimensional contract to allocate incentives. Finally, we use the numerical results to analyze the optimal reward package, and compare the principal’s utility under the different incentive mechanisms. Results demonstrate that by using the proposed incentive mechanism, the principal successfully maximizes the utilities, and the users obtain continuous incentives to participate in the crowdsourcing activity. [ABSTRACT FROM AUTHOR]

This article is an extension of a work in progress paper originally presented at the conference FiE 2020, Frontiers in Education by (Schirichian et al., 2020), as a result of Schirichian’s master’s in science dissertation. It studies the relations between academic performance, protection factors, life at university, and personal characteristics to understand how they influence students’ academic success in undergraduate engineering programs in Brazil. In this challenging environment, several students overcome these issues and graduate, which indicates that some protection structures allow students to face challenging situations and be successful in their studies. Current research studied the relationships between academic performance, self-efficacy, causal attributions, personal characteristics, and life at university, with a group of 30 students. Models were studied by combining the different variables and aspects evaluated in the research, and the findings show relationship between academic performance and: 1) self-efficacy, causal attributions, and personal characteristics (such as leisure activities, living with their parents, or college accommodations) and those who attended private schools during basic education; 2 protection factors self-efficacy and causal attributions with advancing in the program and the time of enrolment in the university; and 3) the dimensions initiation and persistence, success/internality and failure/internality, indicating that those who perceive themselves as playing a major role in their academic journey tend to have better outcomes. Further results show the influence of social inequalities, particularly for those students who declared themselves brown and who conducted their basic education in public schools (which are generally of lower quality than private ones in Brazil). [ABSTRACT FROM AUTHOR]

In this paper we provide a proof of principle of a new method for addressing the ethics of autonomous vehicles (AVs), the Data-Theories Method, in which vehicle crash data is combined with philosophical ethical theory to provide a guide to action for AV algorithm design. We use this method to model three scenarios in which an AV is exposed to risk on the road, and determine possible actions for the AV. We then examine how different philosophical perspectives on agent partiality, or the degree to which one can act in one’s own self-interest, might address each scenario. This method shows why modelling the ethics of AVs using data is essential. First, AVs may sometimes have options that human drivers do not, and designing AVs to mimic the most ethical human driver would not ensure that they do the right thing. Second, while ethical theories can often disagree about what should be done, disagreement can be reduced and compromises found with a more complete understanding of the AV’s choices and their consequences. Finally, framing problems around thought experiments may elicit preferences that are divergent with what individuals might prefer once they are provided with information about the real risks for a scenario. Our method provides a principled and empirical approach to productively address these problems and offers guidance on AV algorithm design. [ABSTRACT FROM AUTHOR]

Ethical decision-making during inevitable crashes, especially when humans involved, has become a big and sensitive roadblock for future mass adoption of autonomous vehicles. Towards addressing this challenge, this paper proposes a predictive control framework for ethical decision-making in autonomous driving using rational ethics. For flexibly implementing of ethical rules, the Lexicographic Optimization-based model predictive controller (LO-MPC) has been designed, in which obstacles and constraints are prioritized. Simulation environment is set up in PreScan, with different edge cases. The results show that the proposed LO-MPC approach has the capability to deal with the ethical decision-making during inevitable crashes by avoiding the obstacles with the assumed priority orders compared with traditional decision-making algorithm. [ABSTRACT FROM AUTHOR]

Mass availability of self-driving cars is ante portas and independent of their sophistication, unavoidable fatal accidents will occur where the car will have to take life and death decisions. However, there is a knowledge gap, since the impact, that the ethical frameworks (used in the car's decision-making process) have on the overall acceptance of self-driving cars, is not well investigated. This paper addresses the key question: In the scope of unavoidable accidents, what is the effect of different ethical frameworks governing self-driving car decision-making, on their acceptance? This quantitative positivist research investigates the link of selected ethical frameworks, i.e., utilitarianism, deontology, relativism, absolutism (monism), and pluralism, to the acceptance of self-driving cars. It is hypothesized that they have an impact on the acceptance of the self-driving cars, and a model linking them to it is proposed and assessed. All five selected ethical frameworks investigated are found to have an effect on self-driving car acceptance, which implies actions for several involved stakeholders as these may be a deciding factor for the success or failure of the self-driving car market introduction. [ABSTRACT FROM AUTHOR]

A system operator asks a group of sensors toexert costly effort to collect accurate measurements of a value of interest over time. At each time, each sensor is asked to report its observation to the operator, and is suitably compensated for the costly effort it exerts. Since both the effort and the observation are private information for the sensor, a naive payment scheme which compensates the sensor based only on its self-reported values of the effort and the measurements will lead to both shirking and falsification of outcomes by the sensor. In this paper, we design an appropriate compensation scheme to incentivize the sensors to both exert costly effort and then reveal the resulting observation truthfully. To this end, we formulate the problem as a repeated game and propose a compensation scheme that employs stochastic verification by the operator coupled with an algorithm to assign a reputation to each sensor. By including the history of the behavior exerted by the sensor in determining present payments, we show that the operator can incentivize higher effort as well as more frequent truthtelling by the sensors. [ABSTRACT FROM AUTHOR]

During the 1980s, many software developers and enthusiasts reacted to software's unclear status within the U.S. copyright law by pursuing technical, rather than legislative fixes. This paper applies forensic methods to recover records of conflict between commercial software developers and the enthusiasts who sought to "crack" commercial programs' copy protection. [ABSTRACT FROM AUTHOR]

Adopting speech as their mode of interaction, speech-enabled conversational agent (CA) systems hold the potential to enable more natural and engaging self-report experiences than traditional media (e.g., pen and paper, web, or smartphone systems). Our recent research concerns the potential design and use of CAs to support mental health and wellbeing. In this article, we present findings from a study during which 22 individuals with affective disorders (e.g., depression, bipolar disorder) used either a speech-enabled CA or web app to self-report their emotional wellbeing. Analysis of users' experiences and engagement with the system for daily self-report suggests that despite many technical limitations, users rated self-reporting via CA as a significantly novel and attractive experience yielding similar rates of engagement to a traditional web-based method. [ABSTRACT FROM AUTHOR]

Stunning advances in machine learning are heralding a new era in sensing, interpreting, simulating and stimulating human emotion. In the human sciences, research is increasingly highlighting the explanatory power of emotions, feelings, and other affective processes to predict how we think and behave. This is beginning to translate into an explosion of applications that can improve human wellbeing including methods to reduce stress and improve emotion regulation skills, techniques to support healthier social media use, pain monitoring in neonates, and decision-support tools that recognize emotional bias. [ABSTRACT FROM AUTHOR]

This paper explores the design process of robotics and autonomous systems using a co-design approach, applied ethics, and values-driven methods. Specifically, the approach seeks to move beyond traditional risk assessment toward a greater consideration of end-user exposure. The goal of the ethics-based co-design approach is to identify end-user and stakeholder values that guide the minimization of end-user vulnerability associated with the employment of autonomous systems. This design process is also used to identify positive consequences that probably increase human wellbeing as opposed to simply avoiding harm. We argue that biomedical autonomous systems design, during the preclinical phase, should bring together diverse stakeholders that would not traditionally be involved in design. We also argue that embedding ethical considerations in the engineering design process should bring together a diverse range of stakeholders to more accurately appreciate possible end-user implications of a design. With complex systems design, such as biotechnologies, greater awareness is necessary of the ethical implications of designed autonomy to end-user exposure. [ABSTRACT FROM AUTHOR]

Non-discrimination is a recognized objective in algorithmic decision making. In this paper, we introduce a novel probabilistic formulation of data pre-processing for reducing discrimination. We propose a convex optimization for learning a data transformation with three goals: controlling group discrimination, limiting distortion in individual data samples, and preserving utility. Several theoretical properties are established, including conditions for convexity, a characterization of the impact of limited sample size on discrimination and utility guarantees, and a connection between discrimination and estimation. Two instances of the proposed optimization are applied to datasets, including one on real-world criminal recidivism. Results show that discrimination can be greatly reduced at a small cost in classification accuracy and with precise control of individual distortion. [ABSTRACT FROM AUTHOR]

Cyber insurance is a viable method for cyber risk transfer. However, it has been shown that depending on the features of the underlying environment, it may or may not improve the state of network security. In this paper, we consider a single profit-maximizing insurer (principal) with voluntarily participating insureds/clients (agents). We are particularly interested in two distinct features of cybersecurity and their impact on the contract design problem. The first is the interdependent nature of cybersecurity, whereby one entity’s state of security depends not only on its own investment and effort, but also the efforts of others’ in the same eco-system (i.e., externalities). The second is the fact that recent advances in Internet measurement combined with machine learning techniques now allow us to perform accurate quantitative assessments of security posture at a firm level. This can be used as a tool to perform an initial security audit, or pre-screening, of a prospective client to better enable premium discrimination and the design of customized policies. We show that security interdependency leads to a “profit opportunity” for the insurer, created by the inefficient effort levels exerted by interdependent agents who do not account for the risk externalities when insurance is not available; this is in addition to risk transfer that an insurer typically profits from. Security pre-screening then allows the insurer to take advantage of this additional profit opportunity by designing the appropriate contracts which incentivize agents to increase their effort levels, allowing the insurer to “sell commitment” to interdependent agents, in addition to insuring their risks. We identify conditions under which this type of contract leads to not only increased profit for the principal, but also an improved state of network security. [ABSTRACT FROM PUBLISHER]

Tremors are a common movement disorder that affects a person’s life adversely. With various drawbacks of current treatment methods, there is a need for a mechanical solution. The authors present a soft orthosis based on layer jamming for the suppression of hand tremors. A vacuum supplied to the layer jamming elements which contain a stack of layers attached to the glove leads to increased stiffness in the glove, suppressing the tremor. The behavior of the tremor in a cohort of patients in Sri Lanka was studied and showed that the tremor’s mean frequency was 5.05 ± 2.03 Hz. An existing analytical model was modified and verified experimentally to select the layer jamming element. An element with sandpaper (320 grade) and tracing paper was chosen based on the high stiffness provided at a lower weight (total weight of the glove = 30g). Experimental results show minimal variation in stiffness for vacuum pressures between 10–50 kPa (abs.). The performance evaluation on a test rig was used to verify the efficacy of the glove and showed optimal placement on the palmar side with a mean tremor amplitude reduction of 78.32%. Clinical trials conducted on 11 recruited tremor patients showed a mean frequency power reduction of 41.74 ± 12.11%, 41.99 ± 14.82%, and 24.71 ± 12.18% in the index and middle fingers and in grasping, respectively with a maximum power reduction of 59.15%. The soft, low weight orthosis shows a high tremor suppression in both the test rig and clinical experiments. [ABSTRACT FROM AUTHOR]

Secret sharing schemes allow a dealer to distribute a secret piece of information among several parties such that only qualified subsets of parties can reconstruct the secret. The collection of qualified subsets is called an access structure. The best known example is the k -threshold access structure, where the qualified subsets are those of size at least k . When k=2 and there are n parties, there are schemes for sharing an \ell bits, and this is tight even for secrets of 1 b. In these schemes, the number of parties n must be given in advance to the dealer. In this paper, we consider the case where the set of parties is not known in advance and could potentially be infinite. Our goal is to give the {t} {^{\mathrm{ th}}} party arriving the smallest possible share as a function of t$ . Our main result is such a scheme for the k$ -threshold access structure and 1-bit secrets where the share size of party t$ is . For k=2$ we observe an equivalence to prefix codes and present matching upper and lower bounds of the form \log t + \log \log t + \log \log \log t + O(1)$ . Finally, we show that for any access structure there exists such a secret sharing scheme with shares of size . [ABSTRACT FROM AUTHOR]

Clark Glymour argued in 2004 that "despite a lack of public fanfare, there is mounting evidence that we are in the midst of ... a revolution - premised on the automation of scientific discovery" [1]. This paper highlights some of the philosophical and sociological dimensions that have been found empirically in work conducted with robot scientists - that is, with autonomous robotic systems for scientific discovery. Robot scientists do not supply definite answers to the discussed questions, but rather provide "proofs of concept" for various ideas. For example, it is not that robot scientists solve the realist/antirealist philosophical debate, but that when working with robot scientists one has to make a philosophical choice - in this case, to assume a realist view of science. There are still few systems for autonomous scientific discovery in existence, and it is too early to generalize and propose new theories. However, being "in the midst of ... a revolution" it is important for the research community to re-examine views pertinent to scientific discovery. This paper highlights how experience with robot scientists could inform discussions in other disciplines, from philosophy of science to computer creativity research. [ABSTRACT FROM PUBLISHER]

Chapters 12, "Presentations", is one of the few chapters in this book clearly devoted to scientific spoken communication, the other being Chapter 14. Hanganu-Bresch and Flaherty begin with the most common types: original research papers (Chapter 8) and review articles (Chapter 9). In Chapter 1, "Cultivating good writing habits", Hanganu-Bresch and Flaherty recommend a list of practical writing habits (e.g., find and use writing models, incorporate writing in every stage of writing). [Extracted from the article]

In cognitive radio networks (CRNs), spectrum trading is an efficient way for secondary users (SUs) to achieve dynamic spectrum access and to bring economic benefits for the primary users (PUs). Existing methods require full payment from SU, which blocked many potential “buyers,” and thus limited the PU’s expected income. To better improve PUs’ revenue from spectrum trading in a CRN, we introduce a financing contract, which is similar to a sealed non-cash auction that allows SU to do financing. Unlike previous mechanism designs in CRN, the financing contract allows the SU to only pay part of the total amount when the contract is signed, known as the down payment. Then, after the spectrum is released and utilized, the SU pays the rest of payment, known as the installment payment, from the revenue generated by utilizing the spectrum. The way the financing contract carries out and the sealed non-cash auction works similarly. Thus, contract theory is employed here as the mathematical framework to solve the non-cash auction problem and form mutually beneficial relationships between PUs and SUs. As the PU may not have the full acknowledgment of the SU’s transmission status, the problems of adverse selection and moral hazard arise in the two scenarios, respectively. Therefore, a joint adverse selection and moral hazard model is considered here. In particular, we present three situations when either or both adverse selection and moral hazard are present during the trading. Furthermore, both discrete and continuous models are provided in this paper. Through simulations, we show that the adverse selection and moral hazard cases serve as the upper and lower bounds of the general case where both problems are present. [ABSTRACT FROM PUBLISHER]

The use of social robots has been proposed for the delivery of therapy to autistic children. The aim of such projects, of which the DREAM project is an example, is to replace therapists by robots, operating in sensory environments that enable them to detect and respond to feedback from the child. This article considers the ethical concerns of autonomy, community, transparency, identity, value, and empathy to evaluate the ethics of such deployment of robots. In doing so it provides a response to the Richardson et al. article in IEEE Technology and Society Magazine, Mar. 2018 [20]. This article concludes that deployment of robots to control the behavior of autistic children is ethically suspect and should be questioned. The use of robots with children should be evaluated on the basis of the purpose of and process by which such robots are deployed, rather than on the basis of the technology itself. Particularly important is the roboticist's empathy with the user of the robot, and gaining an understanding of the individual child. The paper suggests how an understanding of the autistic child might lead to sensitive deployment of a robot to help the child manage social environments through supporting the child's regulation of emotions. [ABSTRACT FROM AUTHOR]

Sensing falsification is a key security threat in cooperative spectrum sensing in cognitive radio networks. Intelligent malicious users (IMUs) adjust their malicious behaviors according to their objectives and the network’s defense schemes. Without long-term collection of information on users’ reputation, the existing schemes fail to thwart such malicious behaviors. In this paper, we construct a joint spectrum sensing and access framework to thwart the malicious behaviors of both rational and irrational IMUs. Lack of reputation information makes the malicious behavior resistance degrade performance since the honest users may be misjudged as IMUs. Based on the moral hazard principal-agent model, we design an incentive compatible mechanism to provide a moderate punishment to IMUs. Our findings show that neither spectrum sensing nor spectrum access alone can prevent malicious behaviors without any information on users’ reputation. According to the different properties of malicious behavior resistance by spectrum sensing and spectrum access, we employ joint spectrum sensing and access to optimally prevent the IMUs sensing falsification. The proposed malicious behavior resistance mechanism is shown to achieve almost the same performance as the ideal case with truthful sensing. [ABSTRACT FROM PUBLISHER]

The capacity to link records associated with the same individual across data sets is a key challenge for data-driven research. The challenge is exacerbated by the potential inclusion of both genomic and clinical data in data sets that may span multiple legal jurisdictions, and by the need to enable re-identification in limited circumstances. Privacy-Preserving Record Linkage (PPRL) methods address these challenges. In 2016, the Interdisciplinary Committee of the International Rare Diseases Research Consortium (IRDiRC) launched a task team to explore approaches to PPRL. The task team is a collaboration with the Global Alliance for Genomics and Health (GA4GH) Regulatory and Ethics and Data Security Work Streams, and aims to prepare policy and technology standards to enable highly reliable linking of records associated with the same individual without disclosing their identity except under conditions in which the use of the data has led to information of importance to the individual's safety or health, and applicable law allows or requires the return of results. The PPRL Task Force has examined the ethico-legal requirements, constraints, and implications of PPRL, and has applied this knowledge to the exploration of technology methods and approaches to PPRL. This paper reports and justifies the findings and recommendations thus far. [ABSTRACT FROM AUTHOR]

In this paper, a case-supported principle-based behavior paradigm is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake. We believe that this is the case since we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Such principles not only help ensure ethical behavior of complex and dynamic systems but also can serve as a basis for justification of this behavior. The requirements, methods, implementation, and evaluation components of the paradigm are detailed as well as its instantiation in both a simulated and real robot functioning in the domain of eldercare. [ABSTRACT FROM AUTHOR]

Background: This paper offers a hybrid, place-based ethic drawn from multiple perspectives as a way to reinvigorate ethical thought for technical communicators. Literature review: Aldo Leopold's land ethic asks us to consider actions beyond our immediate surroundings. Martin Buber's dialogic ethics complement a land ethic and interrogate interpersonal communication. Anticipatory technology ethics recommends the integration of ethical discussions and decisions during the design phase of new technologies. Together, these three approaches inform a place-based ethic for technical communicators. Research questions: 1. How might we meaningfully merge the many ways that technical communicators from varying backgrounds approach ethics into a useful ethical model that considers human interaction, technological innovation, and physical place? 2. How might such a merged model, what we call a place-based ethic, affect technical communication design? Methods: We analyze cases including documents from radical environmental defense groups, a restyling of certain federal court rules from legalese into plainer language, the creation of mortgage documents suitable for consumers and industry professionals, and the action-research design phase of a locative mobile application about public art. Results and conclusion: The cases provide concrete examples of the components of a place-based ethic, and we conclude that designing with a place-based ethic includes actively acknowledging the value of the environment, seeking areas for dialogue among involved parties and celebrating dialogue where it occurs, seeking shared spaces, clearly stating anticipated outcomes, and usability testing for potential ethical issues. [ABSTRACT FROM AUTHOR]

This paper presents the results of our research into cooperation in Government Extended Enterprises, a type of system of systems. The effort proposed and evaluated a novel theory that these decisions are the result of the interaction of four canonical forces—Sympathy, Trust, Fear, and Greed. A computational simulation involving the Stag Hunt game examined information sharing decisions in a series of key decision points in three large case studies. For the five hypotheses tested, exploratory data analysis and nonparametric statistical testing show strong support for three of the hypotheses (cooperation is positively correlated with actors’ levels of Sympathy and Trust and negatively correlated with actors’ levels of Fear) and moderate support for the fourth (cooperation is negatively correlated with actors’ levels of Greed). Indications are that the fifth hypothesis (cooperation is correlated with history of behavior) is not needed to explain observed behavior. Multiple correspondence analysis showed significant interactions both among pairs of forces and when a force is paired with decision making strategies. These results can form the basis for: 1) analysis of additional case studies; 2) development of an agent-based simulation; and 3) creation of training programs for current and future organizational leaders. [ABSTRACT FROM AUTHOR]

Hybrid zero dynamics (HZD) has emerged as a popular framework for dynamic walking but has significant implementation difficulties when applied to the high degrees of freedom humanoids. The primary impediment is the process of gait design—it is difficult for optimizers to converge on a viable set of virtual constraints defining a gait. This paper presents a methodology that allows for fast and reliable generation of dynamic robotic walking gaits through the HZD framework, even in the presence of underactuation. Specifically, we describe an optimization formulation that builds upon the novel combination of HZD and direct collocation methods. Furthermore, achieving a scalable implementation required developing a defect-variable substitution formulation to simplify expressions, which ultimately allows us to generate compact analytic Jacobians of the constraints. We experimentally validate our methodology on an underactuated humanoid, DURUS, a spring-legged machine designed to facilitate energy-economical walking. We show that the optimization approach, in concert with the HZD framework, yields dynamic and stable walking gaits in hardware with a total electrical cost of transport of 1.33. [ABSTRACT FROM PUBLISHER]

The development of social robots for children with autism has been a growth field for the past 15 years. This article reviews studies in robots and autism as a neurodevelopmental disorder that impacts socialcommunication development, and the ways social robots could help children with autism develop social skills. Drawing on ethics research from the EU-funded Development of Robot-Enhanced Therapy for Children with Autism (DREAM) project (framework 7), this paper explores how ethics evolves and developed in this European project. [ABSTRACT FROM PUBLISHER]

Ethical issues remain a significant concern for future large-scale deployment of autonomous vehicles. Although machine ethics have been developed for a few decades, ethical decision making in autonomous driving imposes more complex and emerging challenges to which some dedicated efforts from academia, policymakers, and automakers have been devoted in the past few years. This paper reviews the efforts and progress associated with the various aspects of ethical challenges in autonomous vehicles. Based on the critical review, it is clear that a consistent solution for ethical challenges does not currently exist and recommendations are provided, to potentially encourage the involving players to collaborate to tackle the remaining challenges. [ABSTRACT FROM AUTHOR]

Welcome to this March 2024 Special Issue on Advancing Sustainable Development Goals with AI This issue features research on how AI and data technologies can be used to advance the United Nations (UN) sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

Argument mining is defined as the task of automatically identifying and extracting argumentative components (e.g., premises, claims, etc.) and detecting the existing relations among them (i.e., support, attack, rephrase, no relation). One of the main issues when approaching this problem is the lack of data, and the size of the publicly available corpora. In this work, we use the recently annotated US2016 debate corpus. US2016 is the largest existing argument annotated corpus, which allows exploring the benefits of the most recent advances in natural language processing in a complex domain like argument (relation) mining. We present an exhaustive analysis of the behavior of transformer-based models (i.e., BERT, XLNET, RoBERTa, DistilBERT, and ALBERT) when predicting argument relations. Finally, we evaluate the models in five different domains, with the objective of finding the less domain-dependent model. We obtain a macro F1-score of 0.70 with the US2016 evaluation corpus, and a macro F1-score of 0.61 with the Moral Maze cross-domain corpus. [ABSTRACT FROM AUTHOR]

In the last few years, most of the public universities in the Kingdom of Saudi Arabia (KSA) have adopted electronic learning (e-learning) as an evolutionary educational platform both by choice and by demand. Despite its many advantages, it has increased the ethical and moral challenges faced in the form of the violations of academic integrity that exist in traditional education. Universities all over the world are struggling to overcome these issues. Keeping this in mind, the purpose of this paper is to investigate and priorities the factors of violating academic integrity within Saudi Arabian universities. Based on the previously published literature and using Delphi - based discussions with e-Learning experts, this paper has identified twelve major factors which were related to e-Learning environment, Awareness on Academic Integrity, and e-Learning guiding principles. Analytic Hierarchy Process (AHP) was used to prioritize these factors. It was concluded that inappropriate guidelines provided to students was the most contributing factor while Shortage of feedbacks was least contributing factor among all the identified factors.

One of the greatest compliments I've ever received came from a gentleman who approached me after I had delivered a paper in Vancouver, British Columbia. He said: "You're from the future, aren't you?" He was responding to the manner in which I had considered logical entailments of how future episodes may play out. Although I was trained as a philosopher of science, the majority of my work for the last two decades has been interdisciplinary and collaborative with other fields in the social and physical sciences. As a pioneer in my field - sometimes referred to as experimental philosophy - I often employ the use of thought experiments or "what if?" scenarios to imagine possible future worlds. Thought experiments have been around for thousands of years; from Plato's allegory of the cave (Figure 1), to Rene Descartes' malin genie (Figure 2), to Hilary Putnam's brains in vats (Figure 3). [ABSTRACT FROM AUTHOR]

From the 1970s onward, we started to dream of the leisure society in which, thanks to technological progress and consequent increase in productivity, working hours would be minimized and we would all live in abundance. We all could devote our time almost exclusively to personal relationships, contact with nature, sciences, the arts, playful activities, and so on. Today, this utopia seems more unattainable than it did then. Since the 21st century, we have seen inequalities increasingly accentuated: of the increase in wealth in the United States between 2006 and 2018, adjusted for inflation and population growth, more than 87% went to the richest 10% of the population, and the poorest 50% lost wealth. Following the crisis of 2008, social inequalities, rights violations, planetary degradation, and the climate emergency worsened and increased (see). In 2019, the world’s 2153 billionaires had more wealth than 4.6 billion people. The World Bank estimates that COVID-19 will push up to 150 million people into extreme poverty. [ABSTRACT FROM AUTHOR]