Providing effective feedback to patients in a rehabilitation training program is essential. As technologies are being developed to support patient training, they need to be able to provide the users with feedback on their performance. As there are various aspects on which feedback can be given, it is important to ensure that users are not overwhelmed by too much information given too frequently by the assistive technology. We created a rule-based set of guidelines for the desired hierarchy, timing, and content (...) of feedback to be used when stroke patients train with an upper-limb exercise platform which we developed. The feedback applies to both success on task completion and to the execution of compensatory movements, and is based on input collected from clinicians in a previous study. We recruited 11 stroke patients 1–72 months from injury onset. Ten participants completed the training; each trained with the rehabilitation platform in two configurations: with motor feedback and with no motor feedback. The two conditions were identical, except for the feedback content provided: in both conditions they received feedback on task success; in the MF condition they also received feedback on making undesired compensatory movements during the task. Participants preferred the configuration that provided feedback on both task success and quality of movement. This pilot experiment demonstrates the feasibility of a system providing both task-success and movement-quality feedback to patients based on a decision tree which we developed. (shrink)

IntroductionCognition generally declines gradually over time due to progressive degeneration of the brain, leading to dementia and eventual loss of independent functions. The rate of regression varies among the six cognitive domains. Current modality of cognitive assessment using neuropsychological paper-and-pencil screening tools for cognitive impairment such as the Montreal Cognitive Assessment has limitations and is influenced by age. Virtual reality is considered as a potential alternative tool to assess cognition. A novel, fully immersive automated VR system has been developed to (...) assess the six cognitive domains. As cognition is associated with age, VR performance is postulated to vary with age using this system.AimsThis is a feasibility study to evaluate the VR performance of cognitively healthy adults aged between 35 and 74 years old, based on the performance score and completion time using the CAVIRE system.MethodsConducted in a public primary care clinic in Singapore, 25 multi-ethnic Asian adults were recruited in each of the four age groups in years: 35–44; 45–54; 55–64, and 65–74. The eligibility criteria included a MoCA score of 26 or higher to reflect normal cognition and understanding English instructions. They completed common daily activities ranging from brushing teething to shopping, across 13 VR segments. Their performances scores and completion time were automatically computed by the CAVIRE system. These VR performance indices were compared across the four age groups using one-way ANOVA, F-test of the hypothesis, followed by pair-wise comparisons in the event of a significant F-test.ResultsOne participant dropped out from Group 1. The demographic characteristics of 99 participants were similar across the 4 age groups. Overall, younger participants in Groups 1 and 2 attained higher VR performance scores and shorter completion time, compared to those in Groups 3 and 4, in all six cognitive domains.ConclusionThe CAVIRE VR performance scores and completion time significantly differ between the younger and older Asian participants with normal cognition. Enhancements to the system are needed to establish the age-group specific normal performance indices. (shrink)

Why do organizations conduct job interviews? The traditional view of interviewing holds that interviews are conducted, despite their steep costs, to predict a candidate’s future performance and fit. This view faces a twofold threat: the behavioral and algorithmic threats. Specifically, an overwhelming body of behavioral research suggests that we are bad at predicting performance and fit; furthermore, algorithms are already better than us at making these predictions in various domains. If the traditional view captures the whole story, then interviews seem (...) to be a costly, archaic human resources procedure sustained by managerial overconfidence. However, building on T. M. Scanlon’s work, we offer the value of choice theory of interviewing and argue that interviews can be vindicated once we recognize that they generate commonly overlooked kinds of noninstrumental value. On our view, interviews should thus not be entirely replaced by algorithms, however sophisticated algorithms ultimately become at predicting performance and fit. (shrink)

In this paper, we study the effects of using an algorithm-based risk assessment instrument (RAI) to support the prediction of risk of violent recidivism upon release. The instrument we used is a machine learning version of RiskCanvi used by the Justice Department of Catalonia, Spain. It was hypothesized that people can improve their performance on defining the risk of recidivism when assisted with a RAI. Also, that professionals can perform better than non-experts on the domain. Participants had to predict whether (...) a person who has been released from prison will commit a new crime leading to re-incarceration, within the next two years. This user study is done with (1) general participants from diverse backgrounds recruited through a crowdsourcing platform, (2) targeted participants who are students and practitioners of data science, criminology, or social work and professionals who work with RisCanvi. We also run focus groups with participants of the targeted study, including people who use RisCanvi in a professional capacity, to interpret the quantitative results. Among other findings, we observe that algorithmic support systematically leads to more accurate predictions from all participants, but that statistically significant gains are only seen in the performance of targeted participants with respect to that of crowdsourced participants. Among other comments, professional participants indicate that they would not foresee using a fully-automated system in criminal risk assessment, but do consider it valuable for training, standardization, and to fine-tune or double-check their predictions on particularly difficult cases. We found that the revised prediction by using a RAI increases the performance of all groups, while professionals show a better performance in general. And, a RAI can be considered for extending professional capacities and skills along their careers. (shrink)

Recent advances in medical and information technologies, the availability of new types of medical data, the requirement of increasing numbers of study participants, as well as difficulties in recruitment and retention, all present serious problems for traditional models of specific and informed consent to medical research. However, these advances also enable novel ways to securely share and analyse data. This paper introduces one of these advances—blockchain technologies—and argues that they can be used to share medical data in a secure and (...) auditable fashion. In addition, some aspects of consent and data collection, as well as data access management and analysis, can be automated using blockchain-based smart contracts. This paper demonstrates how blockchain technologies can be used to further all three of the bioethical principles underlying consent requirements: the autonomy of patients, by giving them much greater control over their data; beneficence, by greatly facilitating medical research efficiency and by reducing biases and opportunities for errors; and justice, by enabling patients with rare or under-researched conditions to pseudonymously aggregate their data for analysis. Finally, we coin and describe the novel concept of prosent, by which we mean the blockchain-enabled ability of all stakeholders in the research process to pseudonymously and proactively consent to data release or exchange under specific conditions, such as trial completion. (shrink)

This article examines the transformation of the labor market under the influence of informatization of society. It is noted that in the conditions of globalization and informatization of the nowadays a post-industrial society has been formed, in which information is a determining factor of production. New opportunities and challenges of the labor market in the conditions of information society development are analyzed. The informatization of society changes the conditions, nature and forms of work. Extensive digitalization, the use of cloud technologies (...) and artificial intelligence systems are displacing traditional forms of employment towards teleworking, which makes workers more mobile and able to optimize working hours. It is established that the spread of technology increases the efficiency of the recruitment and searching job processes. Informatization of society contributes to the creation of a digital labor market, which forms the demand and supply of information and computer technology workers. In the context of informatization of society, the labor market is characterized by an imbalance between supply and demand of labor due to structural changes in the economy. Among the challenges of the labor market are rising unemployment in the raw materials industries, robotics and automation of routine manual labor. The digitalization of the economy leads to the need to adjust government regulation of business and provide social guarantees for employees. It is noted that the informatization of society provides more benefits to the labor market than obstacles. Solving the problems it raises, promotes progress and economic development. (shrink)

Digital technologies are radically transforming our work environments and demand for skills, with certain jobs being automated away and others demanding mastery of new digital techniques. This global challenge of rapidly changing skill requirements due to task automation overwhelms workers. The digital skill gap widens further as technological and social transformation outpaces national education systems and precise skill requirements for mastering emerging technologies, such as Artificial Intelligence, remain opaque. Online labour platforms could help us to understand this grand challenge (...) of reskilling en masse. Online labour platforms build a globally integrated market that mediates between millions of buyers and sellers of remotely deliverable cognitive work. This commentary argues that, over the last decade, online labour platforms have become the ‘laboratories’ of skill rebundling; the combination of skills from different occupational domains. Online labour platform data allows us to establish a new taxonomy on the individual complementarity of skills. For policy makers, education providers and recruiters, a continuous analysis of complementary reskilling trajectories enables automated, individual and far-sighted suggestions on the value of learning a new skill in a future of technological disruption. (shrink)

Cardiovascular disease is a major complication of type 2 diabetes mellitus. In addition to traditional risk factors, psychological determinants play an important role in CVD risk. This study applied Deep Neural Network to develop a CVD risk prediction model and explored the bio-psycho-social contributors to the CVD risk among patients with T2DM. From 2017 to 2020, 834 patients with T2DM were recruited from the Department of Endocrinology, Affiliated Hospital of Harbin Medical University, China. In this cross-sectional study, the patients' bio-psycho-social (...) information was collected through clinical examinations and questionnaires. The dataset was randomly split into a 75% train set and a 25% test set. DNN was implemented at the best performance on the train set and applied on the test set. The receiver operating characteristic curve analysis was used to evaluate the model performance. Of participants, 272 were diagnosed with CVD. The developed ensemble model for CVD risk achieved an area under curve score of 0.91, accuracy of 87.50%, sensitivity of 88.06%, and specificity of 87.23%. Among patients with T2DM, the top five predictors in the CVD risk model were body mass index, anxiety, depression, total cholesterol, and systolic blood pressure. In summary, machine learning models can provide an automated identification mechanism for patients at CVD risk. Integrated treatment measures should be taken in health management, including clinical care, mental health improvement, and health behavior promotion. (shrink)

Rapid advances in AI-based automation have led to a number of existential and economic concerns. In particular, as automating technologies develop enhanced competency they seem to threaten the values associated with meaningful work. In this article, we focus on one such value: the value of achievement. We argue that achievement is a key part of what makes work meaningful and that advances in AI and automation give rise to a number achievement gaps in the workplace. This could limit (...) people’s ability to participate in meaningful forms of work. Achievement gaps are interesting, in part, because they are the inverse of the (negative) responsibility gaps already widely discussed in the literature on AI ethics. Having described and explained the problem of achievement gaps, the article concludes by identifying four possible policy responses to the problem. (shrink)

Automated influence is one of the most pervasive applications of artificial intelligence in our day-to-day lives, yet a thoroughgoing account of its associated individual and societal harms is lacking. By far the most widespread, compelling, and intuitive account of the harms associated with automated influence follows what I call the control argument. This argument suggests that users are persuaded, manipulated, and influenced by automated influence in a way that they have little or no control over. Based on evidence about the (...) effectiveness of targeted advertising as well as empirical results about the nature of attentional control, I provide reasons to reject this argument. In turn, I use C. Thi Nguyen’s theory of value collapse to develop a new account of the harmfulness of automated influence. (shrink)

Theorems in automated theorem proving are usually proved by formal logical proofs. However, there is a subset of problems which humans can prove by the use of geometric operations on diagrams, so called diagrammatic proofs. Insight is often more clearly perceived in these proofs than in the corresponding algebraic proofs; they capture an intuitive notion of truthfulness that humans find easy to see and understand. We are investigating and automating such diagrammatic reasoning about mathematical theorems. Concrete, rather than general diagrams (...) are used to prove particular concrete instances of the universally quantified theorem. The diagrammatic proof is captured by the use of geometric operations on the diagram. These operations are the inference steps of the proof. An abstracted schematic proof of the universally quantified theorem is induced from these proof instances. The constructive -rule provides the mathematical basis for this step from schematic proofs to theoremhood. In this way we avoid the difficulty of treating a general case in a diagram. One method of confirming that the abstraction of the schematic proof from the proof instances is sound is proving the correctness of schematic proofs in the meta-theory of diagrams. These ideas have been implemented in the system, called Diamond, which is presented here. (shrink)

In this paper, we discuss the ethics of automated driving. More specifically, we discuss responsible human-robot coordination within mixed traffic: i.e. traffic involving both automated cars and conventional human-driven cars. We do three main things. First, we explain key differences in robotic and human agency and expectation-forming mechanisms that are likely to give rise to compatibility-problems in mixed traffic, which may lead to crashes and accidents. Second, we identify three possible solution-strategies for achieving better human-robot coordination within mixed traffic. Third, (...) we identify important ethical challenges raised by each of these three possible strategies for achieving optimized human-robot cordination in this domain. Among other things, we argue that we should not just explore ways of making robotic driving more like human driving. Rather, we ought also to take seriously potential ways of making human driving more like robotic driving. Nor should we assume that complete automation is always the ideal to aim for; in some traffic-situations, the best results may be achieved through human-robot collaboration. Ultimately, our main aim in this paper is to argue that the new field of the ethics of automated driving needs take seriously the ethics of mixed traffic and responsible human-robot coordination. (shrink)

Artificial intelligence-based (AI) technologies such as machine learning (ML) systems are playing an increasingly relevant role in medicine and healthcare, bringing about novel ethical and epistemological issues that need to be timely addressed. Even though ethical questions connected to epistemic concerns have been at the center of the debate, it is going unnoticed how epistemic forms of injustice can be ML-induced, specifically in healthcare. I analyze the shortcomings of an ML system currently deployed in the USA to predict patients’ likelihood (...) of opioid addiction and misuse (PDMP algorithmic platforms). Drawing on this analysis, I aim to show that the wrong inflicted on epistemic agents involved in and affected by these systems’ decision-making processes can be captured through the lenses of Miranda Fricker’s account of hermeneutical injustice. I further argue that ML-induced hermeneutical injustice is particularly harmful due to what I define as an automated hermeneutical appropriation from the side of the ML system. The latter occurs if the ML system establishes meanings and shared hermeneutical resources without allowing for human oversight, impairing understanding and communication practices among stakeholders involved in medical decision-making. Furthermore and very much crucially, an automated hermeneutical appropriation can be recognized if physicians are strongly limited in their possibilities to safeguard patients from ML-induced hermeneutical injustice. Overall, my paper should expand the analysis of ethical issues raised by ML systems that are to be considered epistemic in nature, thus contributing to bridging the gap between these two dimensions in the ongoing debate. (shrink)

The article explores the problem of preferable technological changes in the context of work. To this end, it addresses the ‘why’ (motives and values) and the ‘how’ (organizational forms) of automation from a normative perspective. Concerning the ‘why,’ automation processes are currently mostly driven by values of economic efficiency. Yet, since automation processes are part of the basic structure of society, as is the division of labor, considerations of justice apply to them. As for the ‘how,’ the (...) article suggests ‘fair hybrid cooperation’ as an alternative ideal to guide automation priorities. It is achieved when the division of labor between humans and machines does not hinder, and preferably enables, workers’ experience of certain primary qualities in their work activity. By analogy with Rawls’ primary goods, these are qualities that it is necessary for every worker to experience in order to pursue their life plans: security, self-direction, self-development, dignity, and recognition. According to this criterion, the tasks to automate first are those hindering these contributive primary qualities. This provides us with a normative vocabulary and a standard to orient automation decisions but also to assess existing organizational forms and envisage alternative cooperative imaginaries. To illustrate how the ideal may play out in the real world, the article concludes with a ‘fair hybrid cooperation test’ and a nurse bots case for meaningful work. (shrink)

This work provides proof-search algorithms and automated counter-model extraction for a class of STIT logics. With this, we answer an open problem concerning syntactic decision procedures and cut-free calculi for STIT logics. A new class of cut-free complete labelled sequent calculi G3LdmL^m_n, for multi-agent STIT with at most n-many choices, is introduced. We refine the calculi G3LdmL^m_n through the use of propagation rules and demonstrate the admissibility of their structural rules, resulting in auxiliary calculi Ldm^m_nL. In the single-agent case, we (...) show that the refined calculi Ldm^m_nL derive theorems within a restricted class of (forestlike) sequents, allowing us to provide proof-search algorithms that decide single-agent STIT logics. We prove that the proof-search algorithms are correct and terminate. (shrink)

How should automated vehicles react in emergency circumstances? Most research projects and scientific literature deal with this question from a moral perspective. In particular, it is customary to treat emergencies involving AVs as instances of moral dilemmas and to use the trolley problem as a framework to address such alleged dilemmas. Some critics have pointed out some shortcomings of this strategy and have urged to focus on mundane traffic situations instead of trolley cases involving AVs. Besides, these authors rightly point (...) out the political nature of the most interesting debates involving AVs. However, in our view, they do not offer an adequate account of the distinction between ethics and politics and still see their proposals as contributions to the ethics of AVs. We argue that many of the interesting questions about how AVs should behave, both in emergency and other situations, are of political, and not moral, nature. This view is based on a conception of politics and political normativity that we have developed elsewhere and that we call “political minimalism.” Additionally, we show that this proposed perspective has significant consequences for the design, management, and regulation of transport systems. (shrink)

Robots are widely expected—and pushed—to transform open-field agriculture, but these visions remain wedded to optimizing monocultural farming systems. Meanwhile there is little pull for automation from ecology-based, diversified farming realms. Noting this gap, we here explore the potential for robots to foster an agroecological approach to crop production. The research was situated in The Netherlands within the case of _pixel cropping_, a nascent farming method in which multiple food and service crops are planted together in diverse assemblages employing agroecological (...) practices such as intercropping and biological pest control. Around this case we engaged with a variety of specialists in discussion groups, workshops, and design challenges to explore the potential of field robots to meet the multifaceted demands of highly diverse agroecological cropping systems. This generated a spectrum of imaginations for how automated tools might—or might not—be appropriately used, ranging from fully automated visions, to collaborative scenarios, to fully analogue prototypes. We found that automating agroecological cropping systems requires finding ways to imbue the ethos of agroecology into designed tools, thereby seeking to overcome tensions between production aims and other forms of social and ecological care. We conclude that a rethinking of automation is necessary for agroecological contexts: not as a blueprint for replacing humans, but making room for analogue and hybrid forms of agricultural work. These findings highlight a need for design processes which include a diversity of actors, involve iterative design cycles, and incorporate feedback between designers, practitioners, tools, and cropping systems. (shrink)

Perhaps due to the numerous community and company benefits associated with corporate volunteer programs, an increasing number of national and international firms are adopting such programs. A major issue in organizing corporate volunteer programs concerns the strategies that are most effective for recruiting employee participation. The results of this study suggest that the most effective strategies for initiating participation in volunteer programs may not be the same as the strategies that are most effective in terms of maximizing the number (...) of volunteer hours contributed by employees. More importantly, the results suggest that the most effective recruitment strategies depend on the age of the employee. The results were discussed in terms of matching the recruitment strategies with the characteristics of the potential volunteers and the nature of the volunteer project. (shrink)

In their proof-of-concept, Meier and colleagues describe the purpose and programming decisions underpinning Medical Ethics Advisor, an automated decision support system used t...

A great deal of theorizing has emerged about the economic ramifications of increased automation. However, significantly less attention has been paid to the potential effects of AI-driven occupational replacement on less measurable metrics—in particular, what it feels like to be replaced. In politics, we see examples of nation-states and extremist groups invoking the concept of replacement as a motivator for political action, unrest, and, at times, violence. In the realm of workplace automation, and in particular, in the case (...) of AI-driven workplace automation, the replacement of human labor with artificial labor is an explicit goal. In this paper, we suggest that, given the effects that the experience of a sense of replacement has in political contexts and the potential for that sense of replacement to motivate unrest and violence, we should be concerned about the widely predicted replacement of workers over the coming decades beyond the potential economic challenges which may arise. (shrink)

Automation can bring the risk of technological unemployment, as employees are replaced by machines that can carry out the same or similar work at a fraction of the cost. Some believe that the appropriate response is to tax automation. In this paper, I explore the justifiability of view, maintaining that we can embrace automation so long as we compensate those employees whose livelihoods are destroyed by this process by creating new opportunities for employment. My contribution in this (...) paper is important not only because I develop a theoretical framework that we can use to resolve this urgent policy dispute—a dispute that has been discussed extensively by labour economists, tax lawyers, and policymakers, but largely neglected by political philosophers—but also because my analysis sheds lights on a wider range of controversies relating to the moral and political importance of unemployment. (shrink)

This chapter contains sections titled: The Cutting Edge Automated Reasoning, Principles and Elements Significant Successes Myths, Mechanization, and Mystique.

A recent wave of academic and popular publications say that utopia is within reach: Automation will progress to such an extent and include so many high-skill tasks that much human work will soon become superfluous. The gains from this highly automated economy, authors suggest, could be used to fund a universal basic income (UBI). Today's employees would live off the robots' products and spend their days on intrinsically valuable pursuits. I argue that this prediction is unlikely to come true. (...) Historical precedent speaks against it, but the main problem is that the prediction fundamentally misunderstands how capitalism works—its incentives to increase or decrease production, its principles of income allocation, and the underlying conception of merit. (shrink)

Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based on Prolog, and in (...) bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model vague concepts following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) a representative use case, the criteria for the admission of students in the “Comunidad de Madrid”. (shrink)

The use of advanced AI and data-driven automation in the public sector poses several organisational, practical, and ethical challenges. One that is easy to underestimate is automation bias, which, in turn, has underappreciated legal consequences. Automation bias is an attitude in which the operator of an autonomous system will defer to its outputs to the point where the operator overlooks or ignores evidence that the system is failing. The legal problem arises when statutory office-holders (or their employees) (...) either fetter their discretion to in-house algorithms or improperly delegate their discretion to third-party software developers—something automation bias may facilitate. A synthesis of previous research suggests an easy way to mitigate the risks of automation bias and its potential legal ramifications is for those responsible for procurement decisions to adhere to a simple checklist that ensures that the pitfalls of automation are avoided as much as possible. (shrink)

This article discusses Fin de Copenhague, a Situationist book experiment from 1957 by Asger Jorn and Guy Debord. By way of a contextualizing archival study with special attention to Jorn’s contemporaneous book project Pour la forme, the article demonstrates that the Russian avant-garde book was a key influence if also a point of critical departure. On this reading, Fin de Copenhague marks a turn away from the unbridled technological optimism of the historical avant-garde. In its material implications and aesthetic choices, (...) Fin de Copenhague draws attention to crucial changes in the capitalist mode of production and challenges the then nascent discourse about “full automation.”. (shrink)

The intention of this paper is to point to the dilemma humanity may face in light of AI advancements. The dilemma is whether to create a world with less evil or maintain the human status of moral agents. This dilemma may arise as a consequence of using automated decision-making systems for high-stakes decisions. The use of automated decision-making bears the risk of eliminating human moral agency and autonomy and reducing humans to mere moral patients. On the other hand, it also (...) has the potential to bring tremendous benefits to humanity by decreasing human-induced harm in the world. After presenting how this dilemma may arise, I explore general avenues for addressing it. I will argue that we do not have to solve this dilemma in an all-or-nothing fashion and that a more nuanced approach may be suitable. However, the main point I want to highlight is that we need to have a principled way of addressing this dilemma, which is currently missing. (shrink)

Automation, artificial intelligence, and biotechnology have become topics of increasing interest in both academia as well as in popular media. The goal of this article is to establish which issues are the most pressing, and what are the underlying causes of the rise of robots. I demonstrate that fears of automation are well supported by current trends of automation as well as the inherent tendency within a capitalist system to automate at the expense of workers and working (...) wages. Additionally, I point to what appears to be a potential evolutionary divide between what Yuval Noah Harari calls the “god” class and the “useless” class. Finally, I discuss how the new role of information as the world’s most valued commodity can either exacerbate this coming divide or liberate society. I present the case that in order to diminish the negative effects we must move beyond the present capitalist economic system, towards one in which economic democracy and the free flow of information thrives. (shrink)

The automated parsing of 130,213 news articles about the 2012 US presidential elections produces a network formed by the key political actors and issues, which were linked by relations of support and opposition. The nodes are formed by noun phrases and links by verbs, directly expressing the action of one node upon the other. This network is studied by applying insights from several theories and techniques, and by combining existing tools in an innovative way, including: graph partitioning, centrality, assortativity, hierarchy (...) and structural balance. The analysis yields various patterns. First, we observe that the fundamental split between the Republican and Democrat camps can be easily detected by network partitioning, which provides a strong validation check of the approach adopted, as well as a sound way to assign actors and topics to one of the two camps. Second, we identify the most central nodes of the political camps. We also learnt that Clinton played a more central role than Biden in the Democrat camp; the overall campaign was much focused on economy and rights; the Republican Party is the most divisive subject in the campaign, and is portrayed more negatively than the Democrats; and, overall, the media reported positive statements more frequently for the Democrats than the Republicans. This is the first study in which political positions are automatically extracted and derived from a very large corpus of online news, generating a network that goes well beyond traditional word-association networks by means of richer linguistic analysis of texts. (shrink)

Automated classification of legal documents has been the subject of extensive research in recent years. However, this is still a challenging task for long documents, since it is difficult for a model to identify the most relevant information for classification. In this paper, we propose a two-stage supervised learning approach for the classification of petitions, a type of legal document that requests a court order. The proposed approach is based on a word-level encoder–decoder Seq2Seq deep neural network, such as a (...) Bidirectional Long Short-Term Memory (BiLSTM) or a Bidirectional Encoder Representations from Transformers (BERT) model, and a document-level Support Vector Machine classifier. To address the challenges posed by the lengthy legal documents, the approach introduces a human-in-the-loop approach, whose task is to localize and tag relevant segments of text in the word-level training part, which dramatically reduces the dimension of the document classifier input vector. We performed experiments to validate our approach using a real-world dataset comprised of 270 intermediate petitions, which were carefully annotated by specialists from the 15th civil unit of the State of Alagoas, Brazil. Our results revealed that both BiLSTM and BERT-Convolutional Neural Networks variants achieved an accuracy of up to 95.49%, and also outperformed baseline classifiers based on the Term Frequency–Inverse Document Frequency test vectorizer. The proposed approach is currently being utilized to automate the aforementioned justice unit, thereby increasing its efficiency in handling repetitive tasks. (shrink)

This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.

Automating Humanity is the shocking and eye-opening new manifesto from international award-winning designer Joe Toscano that unravels and lays bare the power agendas of the world's greatest tech titans in plain language, and delivers a fair warning to policymakers, civilians, and industry professionals alike: we need a strategy for the future, and we need it now. Automating Humanity is an insider's perspective on everything Big Tech doesn't want the public to know--or think about--from the addictions installed on a global scale (...) to the profits being driven by fake news and disinformation, to the way they're manipulating the world for profit and using our data to train systems that will automate jobs at an explosive, unprecedented scale. Toscano provides a critique of modern regulation, including parts of the new European Union's General Data Proctection Regulation (GDPR) suggesting how we can create proactive, adaptable regulation that satisfies both the needs of consumer safety and commercial success in the international economy. The content touches on everything from technology, economics, and public policy to psychology, history, and ethics, and is written in a way that is accessible to everyone from the average reader to the technical expert. (shrink)

This chapter examines the role of shopfloor knowledge in the operation of advanced manufacturing systems. Design trends towards full automation are contrasted with those toward hybrid, human-centred systems with particular emphasis on job design and the development and reproduction of knowledge. The chapter concludes with a short discussion of the problems inherent in hybrid design.

Migrant nurses form an increasing proportion of the nursing workforce, with the United Kingdom (UK) being the third most popular destination for overseas nurses in the world. The migrant nurse workforce is highly susceptible to policy changes at the macro or professional level of the donor and recipient countries. Freedom of information requests were issued to 19 National Health Service [NHS] Trusts in England to determine their involvement in overseas nurse recruitment activity from 1998 onwards. These indicate a notable shift (...) away from active European Union (EU) recruitment and towards overseas countries particularly the Philippines and India. Reasons given were as follows: diminishing returns from EU sources, high attrition among EU nurses and the introduction of English language tests for EU nurses in July 2016. This led to Trusts revisiting their recruitment strategies by increasing more direct/less resource‐intensive methods and expanding their focus outside of the EU. Trusts frequently utilised private recruitment companies for their recruitment drives, including consulting and influencing the Trusts’ workforce strategies. Policy adjustments have numerous influences on the composition of the overseas nursing workforce. While the NHS continues its efforts in expanding its international nursing workforce, this should not be at the expense of ethical and sustainable recruitment practices, which may be compromised indirectly as a result. (shrink)

According to a recent survey by the HR Research Institute, as the presence of artificial intelligence (AI) becomes increasingly common in the workplace, HR professionals are worried that the use of recruitment algorithms will lead to a “dehumanization” of the hiring process. Our main goals in this paper are threefold: i) to bring attention to this neglected issue, ii) to clarify what exactly this concern about dehumanization might amount to, and iii) to sketch an argument for why dehumanizing the hiring (...) process is ethically suspect. After distinguishing the use of the term “dehumanization” in this context (i.e., removing the human presence) from its more common meaning in the interdisciplinary field of dehumanization studies (i.e., conceiving of other humans as subhuman), we argue that the use of hiring algorithms may negatively impact the employee-employer relationship. We argue that there are good independent reasons to accept a substantive employee-employer relationship, as well as an applicant-employer relationship, both of which are consistent with a stakeholder theory of corporate obligations. We further argue that dehumanizing the hiring process may negatively impact these relationships because of the difference between the values of human recruiters and the values embedded in recruitment algorithms. Drawing on Nguyen’s (2021) critique of how Twitter “gamifies communication”, we argue that replacing human recruiters with algorithms imports artificial values into the hiring process. We close by briefly considering some ways to potentially mitigate the problems posed by recruitment algorithms, along with the possibility that some difficult trade-offs will need to be made. (shrink)

Single units that are not related to the desired task can become related to the task by conditioning their firing rates. We theorized that, during conditioning of firing rates to a tone, (a) unrelated single units would be recruited to the task; (b) the recruitment would depend on the phase of the task; (c) tones of different frequencies would produce different patterns of single unit recruitment. In our mute locked-in participant, we conditioned single units using tones of different frequencies emitted (...) from a tone generator. The conditioning task had three phases: Listen to the tone for 20 s, then silently sing the tone for 10 s, with a prior control period of resting for 10 s. Twenty single units were recorded simultaneously while feedback of one of the twenty single units was made audible to the mute locked-in participant. The results indicate that (a) some of the non-audible single units were recruited during conditioning, (b) some were recruited differentially depending on the phase of the paradigm (listen, rest, or silent sing), and (c) single unit firing patterns were specific for different tone frequencies such that the tone could be recognized from the pattern of single unit firings. These data are important when conditioning single unit firings in brain-computer interfacing tasks because they provide evidence that increased numbers of previously unrelated single units can be incorporated into the task. This incorporation expands the bandwidth of the recorded single unit population and thus enhances the brain-computer interface. This is the first report of conditioning of single unit firings in a human participant with a brain to computer implant. (shrink)

In this article we introduce a logical structure for normative reasoning, called Normative Detachment Structure with Ideal Conditions, that can be used to represent the content of certain legal texts in a normalized way. The structure exploits the deductive properties of a system of bimodal logic able to distinguish between ideal and actual normative statements, as well as a novel formalization of conditional normative statements able to capture interesting cases of contrary-to-duty reasoning and to avoid deontic paradoxes. Furthermore, we illustrate (...) how the theoretical framework proposed can be mechanized to get an automated procedure of query-answering on an example of legal text. (shrink)

Many ethicists writing about automated systems attribute agency to these systems. Not only that; they seemingly attribute an autonomous or independent form of agency to these machines. This leads some ethicists to worry about responsibility-gaps and retribution-gaps in cases where automated systems harm or kill human beings. In this paper, I consider what sorts of agency it makes sense to attribute to most current forms of automated systems, in particular automated cars and military robots. I argue that whereas it indeed (...) makes sense to attribute different forms of fairly sophisticated agency to these machines, we ought not to regard them as acting on their own, independently of any human beings. Rather, the right way to understand the agency exercised by these machines is in terms of human–robot collaborations, where the humans involved initiate, supervise, and manage the agency of their robotic collaborators. This means, I argue, that there is much less room for justified worries about responsibility-gaps and retribution-gaps than many ethicists think. (shrink)

Algorithmic decision making is used in an increasing number of fields. Letting automated processes take decisions raises the question of their accountability. In the field of computational journalism, the algorithmic accountability framework proposed by Diakopoulos formalizes this challenge by considering algorithms as objects of human creation, with the goal of revealing the intent embedded into their implementation. A consequence of this definition is that ensuring accountability essentially boils down to a transparency question: given the appropriate reverse-engineering tools, it should be (...) feasible to extract design criteria and to identify intentional biases. General limitations of this transparency ideal have been discussed by Ananny and Crawford :973–989, 2018). We further focus on its technical limitations. We show that even if reverse-engineering concludes that the criteria embedded into an algorithm correspond to its publicized intent, it may be that adversarial behaviors make the algorithm deviate from its expected operation. We illustrate this issue with an automated news recommendation system, and show how the classification algorithms used in such systems can be fooled with hard-to-notice modifications of the articles to classify. We therefore suggest that robustness against adversarial behaviors should be taken into account in the definition of algorithmic accountability, to better capture the risks inherent to algorithmic decision making. We finally discuss the various challenges that this new technical limitation raises for journalism practice. (shrink)

Automated influence, delivered by digital targeting technologies such as targeted advertising, digital nudges, and recommender systems, has attracted significant interest from both empirical researchers, on one hand, and critical scholars and policymakers on the other. In this paper, we argue for closer integration of these efforts. Critical scholars and policymakers, who focus primarily on the social, ethical, and political effects of these technologies, need empirical evidence to substantiate and motivate their concerns. However, existing empirical research investigating the effectiveness of these (...) technologies (or lack thereof), neglects other morally relevant effects—which can be felt regardless of whether or not the technologies "work" in the sense of fulfilling the promises of their designers. Drawing from the ethics and policy literature, we enumerate a range of questions begging for empirical analysis—the outline of a research agenda bridging these fields—and issue a call to action for more empirical research that takes these urgent ethics and policy questions as their starting point. (shrink)

Our computational metaphysics group describes its use of automated reasoning tools to study Leibniz’s theory of concepts. We start with a reconstruction of Leibniz’s theory within the theory of abstract objects (henceforth ‘object theory’). Leibniz’s theory of concepts, under this reconstruction, has a non-modal algebra of concepts, a concept-containment theory of truth, and a modal metaphysics of complete individual concepts. We show how the object-theoretic reconstruction of these components of Leibniz’s theory can be represented for investigation by means of automated (...) theorem provers and finite model builders. The fundamental theorem of Leibniz’s theory is derived using these tools. (shrink)

Recruitment and Reproduction: The Careers and Carriers of Digital Photography and Floorball The claim that social practices have a relatively durable existence in space and time, and that their persistence depends upon their recurrent reproduction through necessarily localised performances is theoretically plausible, but what of the detail? How do the careers of practices and those who "carry" them actually intersect? In this paper we have two related ambitions. One is to show how selected practices are concurrently shaped by the ebb (...) and flow of recruits and defectors and by what it is that cohorts of practitioners actually do. The second is to learn more about the relation between recruitment and reproduction by comparing the ways in which these processes play out in different situations. In taking these two ambitions forward through a discussion of digital and film photography and of floorball (a team game in which players use plastic sticks to hit a small ball into a goal) we explore ways of concretely examining processes that are implied in Giddens' theory of structuration (1984) and in Bourdieu's concept of habitus (1984). This exercise generates insights into the internal dynamics of practice and the methodological challenges of pinning them down. (shrink)

Artificial intelligence (AI) technology poses possible threats to existing jobs. These threats extend not just to the number of jobs available but also to their quality. In the future, so some predict, workers could face fewer and potentially worse jobs, at least if society does not embrace reforms that manage the coming AI revolution. This paper uses the example of Daron Acemoglu and Simon Johnson’s recent book—_Power and Progress_ (2023)—to illustrate some of the dilemmas and options for managing the future (...) of work under AI. Acemoglu and Johnson, while warning of the potential negative effects of an AI-driven automation, argue that AI can be used for positive ends. In particular, they argue for its uses in creating more ‘good jobs’. This outcome will depend on democratising AI technology. This paper is critical of the approach taken by Acemoglu and Johnson—specifically, it misses the possibility for using AI to lighten work (i.e., to reduce its duration and improve its quality). This paper stresses the potential benefits of automation as a mechanism for lightening work. Its key arguments aim to advance critical debates focused on creating a future in which AI works for people not just for profits. (shrink)

The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation. We have confirmed Adam's conclusions through manual experiments. To describe Adam's research, we have developed an ontology and logical language. The resulting formalization involves over (...) 10,000 different research units in a nested treelike structure, 10 levels deep, that relates the 6.6 million biomass measurements to their logical description. This formalization describes how a machine contributed to scientific knowledge. (shrink)

Reflectance spectroscopy is a standard tool for studying the mineral composition of rock and soil samples and for remote sensing of terrestrial and extraterrestrial surfaces. We describe research on automated methods of mineral identification from reflectance spectra and give evidence that a simple algorithm, adapted from a well-known search procedure for Bayes nets, identifies the most frequently occurring classes of carbonates with reliability equal to or greater than that of human experts. We compare the reliability of the procedure to the (...) reliability of several other automated methods adapted to the same purpose. Evidence is given that the procedure can be applied to some other mineral classes as well. Since the procedure is fast with low memory requirements, it is suitable for on- board scientific analysis by orbiters or surface rovers. (shrink)

Prior research indicates that managers’ dark personality traits increase their tendency to engage in disruptive and unethical organizational behaviors including accounting earnings management. Other research suggests that the prevalence of dark personalities in management may represent an accidental byproduct of selecting managers with accompanying desirable attributes that fit the stereotype of a “strong leader.” Our paper posits that organizations may hire some managers who have dark personality traits because their willingness to push ethical boundaries aligns with organizational objectives, particularly in (...) the accounting context where ethical considerations are especially important. Using several validation studies and experiments, we find that experienced executives and recruiting professionals favor hiring a candidate with dark personality traits into an accounting management position over an otherwise better-qualified candidate when the hiring organization faces pressure to manage earnings. Our results help to illuminate why individuals with dark personality traits may effectively compete for high-level accounting positions. (shrink)

Companies increasingly deploy artificial intelligence technologies in their personnel recruiting and selection process to streamline it, making it faster and more efficient. AI applications can be found in various stages of recruiting, such as writing job ads, screening of applicant resumes, and analyzing video interviews via face recognition software. As these new technologies significantly impact people’s lives and careers but often trigger ethical concerns, the ethicality of these AI applications needs to be comprehensively understood. However, given the novelty (...) of AI applications in recruiting practice, the subject is still an emerging topic in academic literature. To inform and strengthen the foundation for future research, this paper systematically reviews the extant literature on the ethicality of AI-enabled recruiting to date. We identify 51 articles dealing with the topic, which we synthesize by mapping the ethical opportunities, risks, and ambiguities, as well as the proposed ways to mitigate ethical risks in practice. Based on this review, we identify gaps in the extant literature and point out moral questions that call for deeper exploration in future research. (shrink)

The paper explores some normative challenges concerning the integration of Machine Learning (ML) algorithms into anticorruption in public institutions. The challenges emerge from the tensions between an approach treating ML algorithms as allies to an exclusively legalistic conception of anticorruption and an approach seeing them within an institutional ethics of office accountability. We explore two main challenges. One concerns the variable opacity of some ML algorithms, which may affect public officeholders’ capacity to account for institutional processes relying upon ML techniques. (...) The other pinpoints the risk that automating certain institutional processes may weaken officeholders’ direct engagement to take forward-looking responsibility for the working of their institution. We discuss why both challenges matter to see how ML algorithms may enhance (and not hinder) institutional answerability practices. (shrink)

Despite numerous ethical examinations of automated vehicles, philosophers have neglected to address how these technologies will affect vulnerable people. To account for this lacuna, researchers must analyze how driverless cars could hinder or help social justice. In addition to thinking through these aspects, scholars must also pay attention to the extensive moral dimensions of automated vehicles, including how they will affect the public, nonhumans, future generations, and culturally significant artifacts. If planners and engineers undertake this task, then they will have (...) to prioritize their efforts to avoid additional harm. The author shows how employing an approach called a “complex moral assessment” can help professionals implement these technologies into existing mobility systems in a just and moral fashion. (shrink)