Artificial Intelligence (AI) has the potential to influence people’s lives in various ways as it is increasingly integrated into important decision-making processes in key areas of society. While AI offers opportunities, it is also associated with risks. These risks have sparked debates about how AI should be regulated, whether through government regulation or industry self-regulation. AI-related risk perceptions can be shaped by national cultures, especially the cultural dimension of uncertainty avoidance. This raises the question of whether people in countries (...) with higher levels of uncertainty avoidance might have different preferences regarding AI regulation than those with lower levels of uncertainty avoidance. Therefore, using Hofstede’s uncertainty avoidance scale and data from ten European countries (N = 7.855), this study investigates the relationships between uncertainty avoidance, people’s AI risk perceptions, and their regulatory preferences. The findings show that people in countries with higher levels of uncertainty avoidance are more likely to perceive AI risks in terms of a lack of accountability and responsibility. While people’s perceived AI risk of a lack of accountability exclusively drives their preferences for government regulation of AI, the perceived AI risk of a lack of responsibility can foster people’s requests for government regulation and/or industry self-regulation. This study contributes to a better understanding of which mechanisms shape people’s preferences for AI regulation. (shrink)

Several proposals for moral enhancement would use AI to augment (auxiliary enhancement) or even supplant (exhaustive enhancement) human moral reasoning or judgment. Exhaustive enhancement proposals conceive AI as some self-contained oracle whose superiority to our own moral abilities is manifest in its ability to reliably deliver the ‘right’ answers to all our moral problems. We think this is a mistaken way to frame the project, as it presumes that we already know many things that we are still in the (...) process of working out, and reflecting on this fact reveals challenges even for auxiliary proposals that eschew the oracular approach. We argue there is nonetheless a substantial role that ‘AI mentors’ could play in our moral education and training. Expanding on the idea of an AI Socratic Interlocutor, we propose a modular system of multiple AI interlocutors with their own distinct points of view reflecting their training in a diversity of concrete wisdom traditions. This approach minimizes any risk of moral disengagement, while the existence of multiple modules from a diversity of traditions ensures pluralism is preserved. We conclude with reflections on how all this relates to the broader notion of moral transcendence implicated in the project of AI moral enhancement, contending it is precisely the whole concrete socio-technical system of moral engagement that we need to model if we are to pursue moral enhancement. (shrink)

This textbook presents an overview of the critically important ethical and legal issues that arise in the computing field and provides a professional perspective from software engineering. The author gained exposure to these aspects of computing while working as a software engineer at Motorola in Ireland, where he coordinated the patent programme and worked with several software suppliers. Topics and features: Presents a broad overview of ethics and the law Includes key learning topics, summaries, and review questions in each (...) chapter, together with a useful glossary Discusses the professional responsibility of computer professionals Explores ethics in various civilisations and religious traditions Discusses ethical software engineering and ethical outsourcing Considers what is fair and ethical in data science Describes ethical challenges that arise in social media and the AI field Reviews intellectual property including patents, copyright and trademarks This practical and easy-to-follow textbook/reference is ideal for computer science students seeking to understand legal and ethical aspects of computing. The text also serves as a concise self-study primer for software engineers and software managers. (shrink)

This study investigates the relationship between the usage of artificial intelligence (AI), specifically AI-based personalized recommendations (AI-PR), and its impact on consumers’ green product awareness (GPA) during online shopping. Recognizing that AI’s influence alone may not significantly affect green buying behaviours, we introduce emotional intelligence (EI) as a moderator to better understand human impact when using AI. The research framework is built upon the Interactive Recommendation Agents and the SOBC framework. A self-administered survey was conducted with 403 respondents, (...) and the data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that AI and AI-PR positively impact GPA, with partial mediation observed among the variables. Furthermore, emotional intelligence positively moderates the relationship between perceived AI usage and GPA. Specifically, individuals with higher emotional intelligence exhibit a stronger positive association between AI usage and GPA. Conversely, emotional intelligence negatively moderates the relationship between AI-based personalized recommendations and GPA, indicating that higher EI weakens the relationship between AI-PR and GPA, while lower EI strengthens it. The implications of this study are significant for marketers and retailers aiming to utilize AI-based personalized recommendations to encourage green behaviour and contribute to a sustainable future. These insights can help them understand the complex dynamics between AI, emotional intelligence, green product awareness, and behavioural intentions. (shrink)

The purpose of this paper is to show an application of variety engineering in the social realm. It focuses on reducing environmental complexity by catalysing self-organizing processes. This catalysis is based on the use of Sen and Nussbaum’s capabilities approach. By doing this an organization may improve the quality of the relations with their clients by transforming environmental agents into new suppliers. This approach opens a new dimension of social responsibility for organizations. A particular case is presented in (...) which a regional university in Colombia faces the challenge of attending low-income students coming from small municipalities. They designed a strategy to offer low-cost housing and a daily balanced meal without using the university's own resources. Instead, they managed to involve some agents of the community by developing their capabilities. This kind of variety engineering shows the possibility of new forms of social responsibility in universities by incorporating the capabilities approach into their managerial practices. This is something that is currently under study in other universities. (shrink)

Artificial intelligence (AI) and machine learning (ML) are becoming increasingly significant areas of research for scholars in science and technology studies (STS) and media studies. In March 2020, Waymo, Google/Alphabet’s autonomous vehicle project, introduced the ‘Open Dataset Virtual Challenge’, an annual competition leveraging their Waymo Open Dataset. This freely accessible dataset comprises annotated autonomous vehicle data from their own Waymo vehicles. Yearly, Waymo has continued to host iterations of this challenge, inviting teams of computer scientists to tackle evolving machine learning (...) and vision problems using Google's data and tools. This article analyses these challenges, situating them within the context of the ‘Grand Challenges’ of artificial intelligence (AI), which aimed to foster accountable and commercially viable advancements in the late 1980s. Through two exploratory workshops, we adopted a ‘technographic’ approach to examine the pivotal role of challenges in the development and political economy of AI. Serving as an organising principle for the AI innovation ecosystem, the challenge connects companies and external collaborators, driving advancements in specific machine vision domains. By exploring six key themes—interface methods, incrementalism, metrics, AI vernacular, applied domains, and competitive advantages—the article illustrates the role of these challenges in shaping AI research and development. By unpacking the dynamic interaction between data, computation, and labour, these challenges serve as catalysts propelling advancements towards self-driving technologies. The study reveals how challenges have historically and presently shaped the evolving landscape of self-driving and AI technologies. (shrink)

Increasingly complex working environments of school principals inevitably led them to face moral dilemmas in daily life. The aim of this research is to reveal which kinds of moral dilemmas principals fall into mostly, how principals follow the road to making decisions in the moral dilemmas, and if the nature of management affects the decision-making process of their moral dilemmas or not. For data collection process snowball sampling was used. Semi-structured interviews and vignettes which were designed by researchers were used (...) for data collection. According to results, principals in Turkey have experienced moral dilemmas based on self-interests instead of ethic of critique which is experienced by Canadian principals. Moreover, taking into consideration the decision-making process, although principals in Canada follow the same procedure as the Turkish principals, they have two extra steps: “considering the students’ benefit” and “considering teachers’ and parents’ needs.” Lastly, it is seen that the Turkish and Canadian principals’ natures which affect the moral dilemma decision-making process are totally different. The possible reasons for these differences and suggestions were discussed within this context. (shrink)

Although Artificial Intelligence (AI) and Machine Learning (ML) are attracting a lot of scientific and engineering attention nowadays, nothing up to now has been achieved to reach the level of building machines that possess human-like intelligence. Though, the engineering community continuously claims that several engineering problems are solved using AI or ML. Here, it is argued that engineers are not being able to build intelligent machines, implying that the systems claimed to have AI/ML belong to different (...) engineering domains. The base of the syllogism is the existence of four main obstacles on which extensive elucidation is performed. In addition, attempt to clear out the developed confusion, mis-use and ab-use of the phrases “Artificial Intelligence” and “Machine Learning” by scientists and engineers is carried out. Furthermore, mathematical, and philosophical approaches are also mentioned that strengthen the argument against AI implementability as part of the whole syllogism. Finally, an alternative approach (not being unique) is suggested and discussed for performing research on AI and ML by the engineers. It is based on complexity theory and non-linear adaptive systems and provides the benefit of eliminating the before mentioned pragmatic and philosophical obstacles that engineers are facing and ignoring, without creating confusion on this scientific endeavor. (shrink)

Because they are key components of aircraft, improving the safety, reliability and economy of engines is crucial. To ensure flight safety and reduce the cost of maintenance during aircraft engine operation, a prognostics and health management system that focuses on fault diagnosis, health assessment, and life prediction is introduced to solve the problems. Predicting the remaining useful life is the most important information for making decisions about aircraft engine operation and maintenance, and it relies largely on the selection of performance (...) degradation features. The choice of such features is highly significant, but there are some weaknesses in the current algorithm for RUL prediction, notably, the inability to obtain tendencies from the data. Especially with aircraft engines, extracting useful degradation features from multisensor data with complex correlations is a key technical problem that has hindered the implementation of degradation assessment. To solve these problems, deep learning has been proposed in recent years to exploit multiple layers of nonlinear information processing for unsupervised self-learning of features. This paper presents a deep learning approach to predict the RUL of an aircraft engine based on a stacked sparse autoencoder and logistic regression. The stacked sparse autoencoder is used to automatically extract performance degradation features from multiple sensors on the aircraft engine and to fuse multiple features through multilayer self-learning. Logistic regression is used to predict the remaining useful life. However, the hyperparameters of the deep learning, which significantly impact the feature extraction and prediction performance, are determined based on expert experience in most cases. The grid search method is introduced in this paper to optimize the hyperparameters of the proposed aircraft engine RUL prediction model. An application of this method of predicting the RUL of an aircraft engine with a benchmark dataset is employed to demonstrate the effectiveness of the proposed approach. (shrink)

Recent events have highlighted large-scale systemic racial disparities in U.S. criminal justice based on race and other demographic characteristics. Although criminological datasets are used to study and document the extent of such disparities, they often lack key information, including arrestees’ racial identification. As AI technologies are increasingly used by criminal justice agencies to make predictions about outcomes in bail, policing, and other decision-making, a growing literature suggests that the current implementation of these systems may perpetuate racial inequalities. In this paper, (...) we argue that AI technologies should be investigated to understand how they recognize racial categories and whether they can be harnessed to fill missing race data. By bridging this gap, we can work towards better understanding racial inequalities in a wide range of contexts, most notably criminal justice. Using a multidisciplinary perspective, we rethink the design and methodology used in facial processing technology (FPT) based on supervised deep learning model (DLM) image classification. By modifying standard FPT pipelines to tackle multiple sources of DLM bias, we propose an experimental methodology based on ethical AI principles to generate binary (Black and White) racial categories using mugshots. We go beyond simply reporting DLM accuracies and address fundamental issues such as generalizability and interpretability by using a “self-auditing” approach. First, we evaluate the inference performances of 42 fine-tuned DLMs using unseen test images from the same dataset but subject to varying data augmentations. Next, to interpret and validate our methodological approach, we apply gradient-based saliency maps to assess the consistency of facial region relevance and attribution. Finally, drawing upon insights from three areas (computer science, sociology, and law), we investigate the efficacy of our DLM-based method as a tool for detecting racial inequalities in criminal justice. (shrink)

The COVID-19 pandemic has triggered panic-buying behavior around the globe. As a result, many essential supplies were consistently out-of-stock at common point-of-sale locations. Even though most retailers were aware of this problem, they were caught off guard and are still lacking the technical capabilities to address this issue. The primary objective of this paper is to develop a framework that can systematically alleviate this issue by leveraging AI models and techniques. We exploit both internal and external data sources and show (...) that using external data enhances the predictability and interpretability of our model. Our data-driven framework can help retailers detect demand anomalies as they occur, allowing them to react strategically. We collaborate with a large retailer and apply our models to three categories of products using a dataset with more than 15 million observations. We first show that our proposed anomaly detection model can successfully detect anomalies related to panic buying. We then present a prescriptive analytics simulation tool that can help retailers improve essential product distribution in uncertain times. Using data from the March 2020 panic-buying wave, we show that our prescriptive tool can help retailers increase access to essential products by 56.74%. (shrink)

In this study, we analyse the public perception of military AI in Estonia, a techno-optimistic country with high support for science and technology. This study involved quantitative survey data from 2021 on the public’s attitudes towards AI-based technology in general, and AI in developing and using weaponised unmanned ground systems (UGS) in particular. UGS are a technology that has been tested in militaries in recent years with the expectation of increasing effectiveness and saving manpower in dangerous military tasks. However, (...) developing weaponised systems often raises questions about their safety and accountability. While there have been public debates about the possible outcomes of AI-based civilian technologies like self-driving cars, equivalent discussions have not been held about military technologies. A discourse on potentially sensitive technologies can diminish biased representations and the distribution of worst-case scenarios. The results of this study reveal that an overall positive attitude towards AI-driven technologies is related to a positive perception of military AI systems. However, trustworthiness and human control are the main aspects that are expected from military technologies. (shrink)

In this paper, we demonstrate how the language and reasonings that academics, developers, consumers, marketers, and journalists deploy to accept or reject AI as authentic intelligence has far-reaching bearing on how we understand our human intelligence and condition. The discourse on AI is part of what we call the “authenticity negotiation process” through which AI’s “intelligence” is given a particular meaning and value. This has implications for scientific theory, research directions, ethical guidelines, design principles, funding, media attention, and the way (...) people relate to and act upon AI. It also has great impact on humanity’s self-image and the way we negotiate what it means to be human, existentially, culturally, politically, and legally. We use a discourse analysis of academic papers, AI education programs, and online discussions to demonstrate how AI itself, as well as the products, services, and decisions delivered by AI systems are negotiated as authentic or inauthentic intelligence. In this negotiation process, AI stakeholders indirectly define and essentialize what being human(like) means. The main argument we will develop is that this process of indirectly defining and essentializing humans results in an elimination of the space for humans to be indeterminate. By eliminating this space and, hence, denying indeterminacy, the existential condition of the human being is jeopardized. Rather than re-creating humanity in AI, the AI discourse is re-defining what it means to be human and how humanity is valued and should be treated. (shrink)

In the 1990’s, Robotics began to design a new robot aimed at industries (primarily automotive) that worked and interacted with humans outside the cage, thereby replacing traditional _robots_ for some specific duties. This _robot_ is therefore called _co-bot_ (_collaborative_ and _robot)._ Also in the 1990’s, Robotics designed the _social robot_ (for which we propose the neologism _so-bot),_ aimed at assisting humans and keeping them company. The sociality of the _sobots_ lies in their ability to follow the rules of human social (...) life, make decisions independently, and respect the roles assigned to them. Scientific literature usually keeps the terms _collaborative_ and _social robot_ distinct as if they indicated different and separate concepts. We question this separation and affirm that to collaborate (from the Latin _cum-laboro_) means to interact with someone while respecting their nature. Collaboration is that particular form of sociality that relates to work activity. From this it follows that the _cobot_ is essentially social and that _cobots_ and _sobots_ belong to the same category that we call _co-s-bots_ (_collaborative social robots_). In other words, _cobots_ and _sobots_ are two types of _cosbots,_ as the flea and the elephant are two types of animals. The difference between _cobot_ and _sobot_ is given by the development of AI. Both are _potentially_ social, that is, _potentially_ capable of interacting and making decisions independently; but while the _cobot_ is social in potency, the _sobot_ is social ‘in act’. With Aristotelian terminology we can therefore say that the _cobot_ is a _sobot_ in power, while the _sobot_ is a _cobot_ in act. We call this new concept ‘_cobot ontology_’. Such an ontology makes it possible to classify _cobots_ according to the degree of development of AI, just as living beings are classified according to the level of intelligence developed.To teach the _cosbot_ to interact with humans, engineers use some results of neuroscientific research such as mirror neurons and the _embodied Mind_. The use of these models should encourage machine self-learning. Self-learning means autonomy, and autonomy needs strong AI development. It is becoming increasingly clear that autonomy is the condition of the sociality of the _sobot_. The article thus concludes that the relationship between _cobot_ and _sobot_ is the identification of a more general _robot_-_automaton_ (_rabota_-_automatos_) relationship which, in the writer’s opinion, is the essential basis and driving force behind the entire history of Robotics. (shrink)

Meeting 5G high bandwidth rates, ultra-low latencies, and high reliabilities requires of network infrastructures that automatically increase/decrease the resources based on their customers’ demand. An autonomous and dynamic management of a 5G network infrastructure represents a challenge, as any solution must account for the radio access network, data plane traffic, wavelength allocation, network slicing, and network functions’ orchestration. Furthermore, federation among administrative domains (ADs) must be considered in the network management. Given the increased dynamicity of 5G networks, artificial intelligence/machine learning (...) (AI/ML) solutions are strong candidates able to learn, and take quick provisioning decisions upon fast changes in network conditions. Therefore, this chapter presents an analysis of the state-of-the-art solutions for 5G networks’ management, where AI/ML solutions are discussed and compared with traditional methods. Additionally, the chapter provides a technology overview of both standards, and existing solutions regarding the 5G network management, and directions toward the integration of AI/ML in 5G networks. (shrink)

In recent years, ethical questions related to the development of artificial intelligence are being increasingly discussed. However, there has not been enough corresponding increase in the research and development associated with AI technology that incorporates with ethical discussion. We therefore implemented an organic and dynamic tool for use with knowledge base of AI ethics for engineers to promote engineers’ practice of ethical AI design to realize further social values. Here, “organic” means that the tool deals with complex relationships among different (...) AI ethics. “Dynamic” means that the tool dynamically adopts new issues and helps engineers think in their own contexts. Data in the knowledge base of the tool is standardized based on the ethical design theory that consists of an extension of the hierarchical representation of artifacts to understand ethical considerations from the perspective of engineering, and a description method to express the design ideas. In addition, we apply the dynamic knowledge management model called knowledge liquidization and crystallization. To discuss the effects, we introduce three cases: a case for the clarification of differences in the structures among AI ethics and design ideas, a case for the presentation of semantic distance among them, and a case for the recommendation of the scenario paths that allow engineers to seamlessly use AI ethics in their own contexts. We discuss the effectiveness of the tool. We also show the probability that engineers can reconstruct AI ethics as a more practical one with professional ethicists. (shrink)

As automated technologies, particularly artificial intelligence (AI) and automated decision-making (ADM), become integral to social life, there is growing concern about their ethical implications. While issues of accountability, transparency, and fairness dominate discussions on “ethical” AI, little attention has been given to how socially disadvantaged groups most impacted by ADM systems form ethical judgments about them. Drawing on insights from relational ethics, this study uses dialogue groups with disabled people to explore how people distinguish between ‘more just’ or ‘less just’ (...) uses of technology, and the contextual, situational, and relational factors that shape these judgments. For the dialogue group participants in our study, ethical reasoning was most strongly influenced by concerns about how ADM systems affect self-determination, caring relationships and identity recognition, and about the political–economic drivers of automation. The article contributes to AI ethics by empirically demonstrating that justice and ethics depend on the social relationships valued in different contexts and what is at stake, both personally and politically, in decisions aided by automation. (shrink)

We motivate the desire for self-driving and explain its potential and limitations, and explore the need for—and potential implementation of—morals, ethics, and other value systems as complementary “capabilities” to the Deep Technologies behind self-driving. We consider how the incorporation of such systems may drive or slow adoption of high automation within vehicles. First, we explore the role for morals, ethics, and other value systems in self-driving through a representative hypothetical dilemma faced by a self-driving car. Through (...) the lens of engineering, we explain in simple terms common moral and ethical frameworks including utilitarianism, deontology, and virtue ethics before characterizing their relationship to the fundamental algorithms enabling self-driving. The concepts of behavior cloning, state-based modeling, and reinforcement learning are introduced, with some algorithms being more suitable for the implementation of value systems than others. We touch upon the contemporary cross-disciplinary landscape of morals and ethics in self-driving systems from a joint philosophical and technical perspective, and close with considerations for practitioners and the public, particularly as individuals may not appreciate the nuance and complexity of using imperfect information to navigate diverse scenarios and tough-to-quantify value systems, while “typical” software development reduces complex problems to black and white decision-making. (shrink)

Biological pacemakers can be achieved by various gene‐based and cell‐based approaches. Embryonic stem cells (ESCs)‐derived pacemaker cells might be the most promising way to form biological pacemakers, but there are challenges as to how to control the differentiation of ESCs and to overcome the neoplasia, proarrhythmia, or immunogenicity resulting from the use of ESCs. As a potential approach to solve these difficult problems, tissue‐engineering techniques may provide a precise control on the different cell components of multicellular aggregates and the (...) forming of a construct with‐defined architectures and functional properties. The combined interactions between ESC‐derived pacemaker cells, supporting cells, and matrices may completely reproduce pacemaker properties and result in a steady functional unit to induce rhythmic electrical and contractile activities. As ESCs have a high capability for self‐renewal, proliferation, and potential differentiation, we hypothesize that ESCs can be used as a source of pacemaker cells for tissue‐engineering applications and the ambitious goal of biological cardiac pacemakers may ultimately be achieved with ESCs via tissue‐engineering technology. -/- . (shrink)

Some engineering educators recognize the necessity and challenges of teaching students moral sensitivity. As recently pointed out by some scholars, along with moral sensitivity, promoting “self-knowledge” is significantly lacking in engineering curricula. We suggest that the “ethics autobiography” employed in some health and psychological science programs can serve as a useful tool for helping engineering students develop moral sensitivity and self-reflective competencies. First, this paper briefly discusses some unique potential strengths of introducing ethics autobiography as (...) a tool for moral pedagogy to engineering education. Second, this paper provides five specific examples on how to implement ethics autobiography in the classroom. Among the five examples, two are directly related to engineering education and the other three can easily be adapted to meet the needs of engineering education. Finally, this paper concludes with some discussion of the implications of ethics autobiography for engineering ethics education reform and the limitations and ethical considerations of using autobiography in moral pedagogy. (shrink)

This paper investigates how human interactions with AI-powered chatbots may offend human dignity. Current chatbots, driven by large language models (LLMs), mimic human linguistic behaviour but lack the moral and rational capacities essential for genuine interpersonal respect. Human beings are prone to anthropomorphise chatbots—indeed, chatbots appear to be deliberately designed to elicit that response. As a result, human beings’ behaviour toward chatbots often resembles behaviours typical of interaction between moral agents. Drawing on a second-personal, relational account of dignity, we argue (...) that interacting with chatbots in this way is incompatible with the dignity of users. We show that, since second-personal respect is premised on reciprocal recognition of second-personal moral authority, behaving towards chatbots in ways that convey second-personal respect is bound to misfire in morally problematic ways, given the lack of reciprocity. Consequently, such chatbot interactions amount to subtle but significant violations of self-respect—the respect we are dutybound to show for our own dignity. We illustrate this by discussing four actual chatbot use cases (information retrieval, customer service, advising, and companionship), and propound that the increasing societal pressure to engage in such interactions with chatbots poses a hitherto underappreciated threat to human dignity. (shrink)

This paper focuses on the potential of “equitech”—AI technology that improves equity. Recently, interventions have been developed to reduce the harm of implicit bias, the automatic form of stereotype or prejudice that contributes to injustice. However, these interventions—some of which are assisted by AI-related technology—have significant limitations, including unintended negative consequences and general inefficacy. To overcome these limitations, we propose a two-dimensional framework to assess current AI-assisted interventions and explore promising new ones. We begin by using the case of (...) human resource recruitment as a focal point to show that existing approaches have exploited only a subset of the available solution space. We then demonstrate how our framework facilitates the discovery of new approaches. The first dimension of this framework helps us systematically consider the analytic information, intervention implementation, and modes of human-machine interaction made available by advancements in AI-related technology. The second dimension enables the identification and incorporation of insights from recent research on implicit bias intervention. We argue that a design strategy that combines complementary interventions can further enhance the effectiveness of interventions by targeting the various interacting cognitive systems that underlie implicit bias. We end with a discussion of how our cognitive interventions framework can have positive downstream effects for structural problems. (shrink)

Conceptual engineering is the method (or methods) via which we can assess and improve our concepts. Can conceptual engineering be usefully employed within analytic theology? Given that analytic theology and analytic philosophy effectively share the same philosophical toolkit then if conceptual engineering works well in philosophy then it ought to work well in analytic theology too. This will be our working hypothesis. To make good on this hypothesis, we first address two challenges. The first challenge makes conceptual (...) engineering look to be too inclusive; the second challenge makes it look to be too revolutionary (for analytic theology). To address these challenges, we propose a refined characterisation of conceptual engineering. We then turn to consider a number of case studies where analytic theology and conceptual engineering may fruitfully cooperate. These are: theological disagreements, inter-faith dialogue, meaning change, celibacy, AI, the name of God, and conceptual genealogy. (shrink)

There is a deluge of AI-assisted decision-making systems, where our data serve as proxy to our actions, suggested by AI. The closer we investigate our data (raw input, or their learned representations, or the suggested actions), we begin to discover “bugs”. Outside of their test, controlled environments, AI systems may encounter situations investigated primarily by those in other disciplines, but experts in those fields are typically excluded from the design process and are only invited to attest to the ethical features (...) of the resulting system or to comment on demonstrations of intelligence and aspects of craftmanship after the fact. This communicative impasse must be overcome. Our idea is that philosophical and engineering considerations interact and can be fruitfully combined in the AI design process from the very beginning. We embody this idea in the role of a philosopher engineer. We discuss the role of philosopher engineers in the three main design stages of an AI system: deployment management (what is the system’s intended use, in what environment?); objective setting (what should the system be trained to do, and how?); and training (what model should be used, and why?). We then exemplify the need for philosopher engineers with an illustrative example, investigating how the future decisions of an AI-based hiring system can be fairer than those contained in the biased input data on which it is trained; and we briefly sketch the kind of interdisciplinary education that we envision will help to bring about better AI. (shrink)

The present paper explores the realm of indexicals, with a focus on self-locating thoughts, assessing their role in agency. Philosophers have actively discussed the problem of indexicals since the groundbreaking work of David Kaplan and John Perry, and the ongoing debate continues to this day. The paper also discusses an externalist perspective on thought-content while aiming to illustrate the essential role of indexicals in self-locating thoughts, encompassing those found within the self-locating representations of robots. The paper describes (...) a scenario in which Perry the robot, as it is named, becomes disoriented. The robot’s established objective is to navigate through the surroundings while indispensably engaging in self-location. In addition, the paper discusses Paul Teller’s example of robots autonomously following instructions based on third-person representations. Teller’s aim is to present an instance of genuine action devoid of the use of indexicals. In opposition to Teller’s viewpoint, the paper puts forth a form of internalism, termed robot-internalism, asserting that indexical thoughts are internal to individuals, whether human or robot, arguing that indexicals are necessary for the agency of both humans and robots. (shrink)

The literature on self-driving cars and ethics continues to grow. Yet much of it focuses on ethical complexities emerging from an individual vehicle. That is an important but insufficient step towards determining how the technology will impact human lives and society more generally. What must complement ongoing discussions is a broader, system level of analysis that engages with the interactions and effects that these cars will have on one another and on the socio-technical systems in which they are embedded. (...) To bring the conversation of self-driving cars to the system level, we make use of two traffic scenarios which highlight some of the complexities that designers, policymakers, and others should consider related to the technology. We then describe three approaches that could be used to address such complexities and their associated shortcomings. We conclude by bringing attention to the “Moral Responsibility for Computing Artifacts: The Rules”, a framework that can provide insight into how to approach ethical issues related to self-driving cars. (shrink)

Should we be worried that the concept of trust is increasingly used when we assess non-human agents and artefacts, say robots and AI systems? Whilst some authors have developed explanations of the concept of trust with a view to accounting for trust in AI systems and other non-agents, others have rejected the idea that we should extend trust in this way. The article advances this debate by bringing insights from conceptual engineering to bear on this issue. After setting up (...) a target concept of trust in terms of four functional desiderata (trust-reliance distinction, explanatory strength, tracking affective responses, and accounting for distrust), I analyze how agential vs. non-agential accounts can satisfy these. A final section investigates how ‘non-ideal’ circumstances—that is, circumstances where the manifest and operative concept use diverge amongst concept users—affect our choice about which rendering of trust is to be preferred. I suggest that some prominent arguments against extending the language of trust to non-agents are not decisive and reflect on an important oversight in the current debate, namely a failure to address how narrower, agent-centred accounts curtail our ability to distrust non-agents. (shrink)

Ultrasonic excitation has been widely used in the detection of microcracks on metal surfaces, but there are problems such as poor excitation effect of ultrasonic pulse, long time to reach the best excitation, and difficult to find microcracks. In this paper, an adaptive ultrasonic pulse excitation device and infrared thermal imaging technology have been combined, as well as their control method, to solve the problem. The adaptive ultrasonic pulse excitation device adds intelligent modules to realize automatic adjustment of detection parameters, (...) which can quickly obtain reliable excitation; the multidegree-of-freedom base realizes the three-dimensional direction change of the ultrasonic gun to adapt to different excitation occasions. When the appropriate ultrasonic excitation makes microcracks in the resonance state, the microcracks can be frictionated, which produce heat rise with the temperature. Then, the microcrack defect can be detected by the infrared thermal instrument through the different surface temperatures with imaging recognition method. Our detection experiments of the titanium alloy plates and the aluminum alloy profiles of marine engineering show that the method can get reliable detection parameters in a short time and measure the crack length effectively. It can be used in many aspects such as crack detection in mechanical structures or complex equipment operating conditions and industrial production processes. (shrink)

Engineers make decisions with global impacts and empathy can motivate ethical reasoning and behavior that is sensitive to the needs and perspectives of stakeholders across the globe. Microethics and macroethics offer two frames of reference for engineering ethics education, but different dimensions of empathy play distinct roles in micro- and macroethics. Microethics emphasizes individual responsibility and interpersonal relationships whereas macroethics emphasizes societal obligations and impacts. While empathy can support ethical reasoning and behavior for each, in this paper I argue (...) that affective empathy plays a primary (but not exclusive) role in microethics whereas cognitive empathy plays a primary role in macroethics. Gilligan’s and Kohlberg’s theories of moral development are used to further depict how affective empathy aligns with care (depicted as an interpersonal phenomenon) and how cognitive empathy aligns with justice (depicted as a systems-focused phenomenon), thus positioning these ethical principles as playing primary (but again, not exclusive) roles in micro- and macro-ethics, respectively. Building on these ideas, this study generates a framework that describes and visualizes how empathy manifests across six frames of reference, each of which are increasingly macro-ethical in nature: self, team, operators, participants, bystanders, and future generations. The paper describes how proxy stakeholders can be identified, developed, and leveraged to empathize with stakeholder groups. Taken together, the manuscript seeks to clarify the role of empathy in engineering ethics and can enable engineering students to better empathize with the range of stakeholders impacted by engineering decisions, ranging from one’s self to stakeholders across the globe. The intrapersonal understandings and motivations that students generate by empathizing across six frames of reference can facilitate ethical reasoning processes and behaviors that are more inclusive and comprehensive. (shrink)

This paper aims to engineer the concept of biomimetic design for its application in agricultural technology as an innovation strategy to sustain non-human species’ adaptation to today’s rapid environmental changes. By questioning the alleged intrinsic morality of biomimicry, a formulation of it is sought that goes beyond the sharp distinction between nature as inspiration and the human field of application of biomimetic technologies. After reviewing the main literature on Responsible Innovation, we support Vincent Blok’s “eco-centric” perspective on biomimicry, which considers (...) the human and natural worlds as indistinguishable parts of a shared Earth. We propose this approach as a complement to the “evomimetic” critique, which warns biomimetic research against the limits of adaptationism. By merging these two reframing of the biomimicry concept, we thus pave the way for a new understanding of the use of human-inspired technology (such as artificial intelligence) to help the “evolution” of domesticated species into (semi)autonomous natural-technological hybrids. In particular, the examples we consider concern the potential of AI-enabled robotic bases in technological beekeeping. (shrink)

As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

The growing capabilities of artificial intelligence (AI) word processing models have demonstrated exceptional potential to impact language related tasks and functions. Their fast pace of adoption and probable effect has also given rise to controversy within certain fields. Models, such as GPT-3, are a particular concern for professionals engaged in writing, particularly as their engagement with these technologies is limited due to lack of ability to control their output. Most efforts to maximize and control output rely on a process known (...) as prompt engineering, the construction and modification of the inputted prompt with expectation for certain outputted or desired text. Consequently, prompt engineering has emerged as an important consideration for research and practice. Previous conceptions of prompt engineering have largely focused on technical and logistic modifications to the back-end processing, remaining inaccessible and, still, limited for most users. In this paper, we look to the technical communication field and its methods of text generation—the rhetorical situation—to conceptualize prompt engineering in a more comprehensible way for its users by considering the context and rhetoric. We introduce a framework, consisting of a formula, to prompt engineering, which demands all components of the rhetorical situation be present in the inputted prompt. We present discussions on the future of AI writing models and their use in both professional and educational settings. Ultimately, this discussion and its findings aim to provide a means of integrating agency and writer-centric methods to AI writing tools to advance a more human-in-the-loop approach. As the use of generative AI and especially NLP-based technologies become common across societal functions, the use of prompt engineering will play a crucial role not just in adoption of the technology, but also its productive and responsible use. (shrink)

Among the myriad of technical approaches and abstract guidelines proposed to the topic of AI bias, there has been an urgent call to translate the principle of fairness into the operational AI reality with the involvement of social sciences specialists to analyse the context of specific types of bias, since there is not a generalizable solution. This article offers an interdisciplinary contribution to the topic of AI and societal bias, in particular against the poor, providing a conceptual framework of the (...) issue and a tailor-made model from which meaningful data are obtained using Natural Language Processing word vectors in pretrained Google Word2Vec, Twitter and Wikipedia GloVe word embeddings. The results of the study offer the first set of data that evidences the existence of bias against the poor and suggest that Google Word2vec shows a higher degree of bias when the terms are related to beliefs, whereas bias is higher in Twitter GloVe when the terms express behaviour. This article contributes to the body of work on bias, both from and AI and a social sciences perspective, by providing evidence of a transversal aggravating factor for historical types of discrimination. The evidence of bias against the poor also has important consequences in terms of human development, since it often leads to discrimination, which constitutes an obstacle for the effectiveness of poverty reduction policies. (shrink)

Social robotics entertains a particular relationship with anthropomorphism, which it neither sees as a cognitive error, nor as a sign of immaturity. Rather it considers that this common human tendency, which is hypothesized to have evolved because it favored cooperation among early humans, can be used today to facilitate social interactions between humans and a new type of cooperative and interactive agents - social robots. This approach leads social robotics to focus research on the engineering of robots that activate (...) anthropomorphic projections in users. The objective is to give robots "social presence" and "social behaviors" that are sufficiently credible for human users to engage in comfortable and potentially long-lasting relations with these machines. This choice of ’applied anthropomorphism’ as a research methodology exposes the artifacts produced by social robotics to ethical condemnation: social robots are judged to be a "cheating" technology, as they generate in users the illusion of reciprocal social and affective relations. This article takes position in this debate, not only developing a series of arguments relevant to philosophy of mind, cognitive sciences, and robotic AI, but also asking what social robotics can teach us about anthropomorphism. On this basis, we propose a theoretical perspective that characterizes anthropomorphism as a basic mechanism of interaction, and rebuts the ethical reflections that a priori condemns "anthropomorphism-based" social robots. To address the relevant ethical issues, we promote a critical experimentally based ethical approach to social robotics, "synthetic ethics," which aims at allowing humans to use social robots for two main goals: self-knowledge and moral growth. (shrink)

This institutional self-study investigated the use of text-matching software to prevent plagiarism by students in a Canadian university that did not have an institutional license for TMS at the time of the study. Assignments from a graduate-level engineering course were analyzed using iThenticate®. During the initial phase of the study, similarity scores from the first student assignments were collected to determine a baseline level of textual similarity. Students were then offered an educational intervention workshop on academic integrity. (...) Another set of similarity scores from consenting participants’ second assignments were then collected, and a statistically significant assignment effect was found between the similarity scores of the two assignments. The results of this study indicate that TMS, when used in conjunction with educational interventions about academic integrity, can be useful to students and educators to prevent and identify academic misconduct. This study adds to the growing body of empirical research about academic integrity in Canadian higher education and, in particular, in engineering fields. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Toleration and Justice in the Laozi:Engaging with Tao Jiang's Origins of Moral-Political Philosophy in Early ChinaAi Yuan (bio)IntroductionThis review article engages with Tao Jiang's ground-breaking monograph on the Origins of Moral-Political Philosophy in Early China with particular focus on the articulation of toleration and justice in the Laozi (otherwise called the Daodejing).1 Jiang discusses a naturalistic turn and the re-alignment of values in the Laozi, resulting in a naturalization (...) of justice (impartiality) by rejecting artificial humaneness and rigid hierarchical moral-political structures. In this Laozian just world, there is no room for human intervention and rigid top-down enforcement of values, thus leaving justice to naturalized Heaven or Dao as the ultimate source of the cosmos.Based on Jiang's interpretative context, I show that there is a twofold justification for the "paradoxical" and "elusive"2 value of political toleration.3 A negative expression of toleration focuses on non-interference with choices, and non-enforcement of values toward those whom one reasonably disagrees with and regards as morally wrong. Such an attitude of toleration results in practical advantages such as avoiding entrenchment in bloodshed, abandonment, and deprivation.A positive expression of toleration operating in the Laozian ideal world requires equal protection of people as capable knowers, including those to whom we object. Such protection includes their ways of expression and an unbiased recognition of them as equally capable knowers so that they are heard without bias and prejudice. Such a kind of toleration is revealed as a constituent component of justice since it enables equal contribution toward the shaping of society without discrimination. In other words, toleration is seen as naturalized justice in a Laozian world within which no one is "being wronged with the capacity as a knower"—a kind of epistemic justice articulated by Miranda Fricker (Fricker 2007).4 [End Page 466]This article discusses how Jiang's political reconstruction of Laozian philosophy contains the seeds for a discussion of toleration, a value associated with distributive justice and against epistemic injustice. First, it introduces Jiang's arguments on a naturalization of justice and impartiality as Heavenly attributes in the Laozi. Second, it articulates the value of tolerance in the Laozi. Finally, I compare Laozian toleration with Confucian toleration using youwei- wuwei metaethical criticism.Moral-Political Philosophy in the LaoziJiang's interpretative framework about the origins of distributive justice in the Laozi starts with a discussion of the cosmogonic-mystical worldviews that signal "a new understanding of the nature of the cosmos, as well as a broad reorientation in the Heaven-human relationship in the mid-Warring States period" (p. 192). Differing from the interests in the origins of human culture or civilization in the Ru and Mo traditions, Jiang agrees with Franklin Perkins and identifies a "cosmogonic turn" in the late fourth century b.c. that reveals a demotion of anthropomorphic Heaven. By paring Heaven with earth and accordingly decentering human beings in the intellectual discourse, the Laozi directs equal values to the ten thousand things, with humans as just one among them (Perkins 2016, quoted in Jiang 2021, p. 196).5 Laozi's philosophy thus stands out by rejecting Heaven as caring for human affairs while taking Dao as the ultimate origin of the cosmos, as claimed in chapter 5 of the received text: "Heaven and earth are not humane; they treat ten-thousand things in the world as straw dogs; the sage is not humane; he treats people as straw dogs" (p. 199).With Jiang's reading of a naturalistic heaven, we see a re-alignment between cosmos and the human since sage-rulers follow the Heaven-Dao. The Laozian Dao is "self-so-ing" (ziran 自然), "accommodating" (rong 容), and "impartial" (gong 公), and thus marks a sharp contrast to Confucian familial bias resulting in "actively intervening in human affairs on behalf of the (certain) humans by appointing them to carry out its mission" (p. 200). With the sage emulating the ultimate Dao, the Laozi replaces the Confucian anthropocentric Heaven, which focuses on partiality (qin 親) and humaneness (ren 仁).This Laozian understanding of the cosmos also grounds its philosophical departure from Mohism despite both having a political... (shrink)

Artificial Intelligence (AI) seems to be impacting all industry sectors, while becoming a motor for innovation. The diffusion of AI from the civilian sector to the defense sector, and AI’s dual-use potential has drawn attention from security and ethics scholars. With the publication of the ethical guideline Trustworthy AI by the European Union (EU), normative questions on the application of AI have been further evaluated. In order to draw conclusions on Trustworthy AI as a point of reference for responsible research (...) and development (R&D), we approach the diffusion of AI across both civilian and military spheres in the EU. We capture the extent of technological diffusion and derive European and German patent citation networks. Both networks indicate a low degree of diffusion of AI between civilian and defense sectors. A qualitative investigation of project descriptions of a research institute’s work in both civilian and military fields shows that military AI applications stress accuracy or robustness, while civilian AI reflects a focus on human-centric values. Our work represents a first approach by linking processes of technology diffusion with normative evaluations of R&D. (shrink)

Instead of seeing technology as outside ourselves, it is argued that it is an innate human function and the main driving force in human evolution. Opportunistic ‘thing using’, long before stone tools appeared, was the likeliest cause of bipedalism. It also forced brain development and the emergence of creativity. The neural basis for this creative technical activity later provided the brain functions on which language could develop. This simple unifying hypothesis has interesting implications for the way that we see (...) technology in history, and for determinist theories of the future. It also bears on the way engineers are trained, and more important, the human faculties which need to be fostered in children. (shrink)

In what follows, I shall focus on what may be defined as the engineering of hu- mans from a philosophical perspective. More precisely, I shall reflect upon the way in which our language increasingly changes when we define our relationship with emerging technologies, specifically human digital twins, which, as our tech- nological replica, can serve as privileged standpoints to try to understand the meaning of the shift from using distinguishable words to define humans and technologies (for instance, when (...) we happen to talk about our health in terms of self-perception) to using indistinguishable words to define humans and technol- ogies (for instance, when we happen to talk about our health in terms of human digital twins’ diagnoses and prognoses). The change of our language shows a kind of optimisation that is taken to the extreme, starting with the optimisation of human bodies’ performances: the more engineered humans are (in that they identify their purpose not with feeling good, for instance, but with preforming in faster and more profitable ways), the better they are (in that they measure themselves not against typically human values, such as feeling good, for in- stance, but against typically engineering values, such as efficiency). But a re- markable paradox emerges, whose meaning shall be the core of my philosophical reflection: the more humans work on optimising themselves, the more they (par- adoxically) work on moving optimisation from themselves, i.e. their capabilities as autonomous humans (starting with self-perception), to technologies, i.e. ways of engineering, specifically automating, themselves. (shrink)

Artificial intelligence, the "science and engineering of intelligent machines", still has yet to create even a simple "Advice Taker" [McCarthy, 1959]. We have previously argued [Waser, 2011] that this is because researchers are focused on problem-solving or the rigorous analysis of intelligence (or arguments about consciousness) rather than the creation of a "self" that can "learn" to be intelligent. Therefore, following expert advice on the nature of self [Llinas, 2001; Hofstadter, 2007; Damasio, 2010], we embarked upon an (...) effort to design and implement a self-understanding, self-improving loop as the totality of a (seed) AI. As part of that, we decided to follow up on Richard Dawkins' [1976] speculation that "perhaps consciousness arises when the brain's simulation of the world becomes so complete that it must include a model of itself" by defining a number of axioms and following them through to their logical conclusions. The results combined with an enactive approach yielded many surprising and useful implications for further understanding consciousness, self, and "free-will" that continue to pave the way towards the creation of safe/moral autopoiesis. (shrink)

The increasing use of Artificial Intelligence for making decisions in public affairs has sparked a lively debate on the benefits and potential harms of self-learning technologies, ranging from the hopes of fully informed and objectively taken decisions to fear for the destruction of mankind. To prevent the negative outcomes and to achieve accountable systems, many have argued that we need to open up the “black box” of AI decision-making and make it more transparent. Whereas this debate has primarily focused (...) on how transparency can secure high-quality, fair, and reliable decisions, far less attention has been devoted to the role of transparency when it comes to how the general public come to perceive AI decision-making as legitimate and worthy of acceptance. Since relying on coercion is not only normatively problematic but also costly and highly inefficient, perceived legitimacy is fundamental to the democratic system. This paper discusses how transparency in and about AI decision-making can affect the public’s perception of the legitimacy of decisions and decision-makers and produce a framework for analyzing these questions. We argue that a limited form of transparency that focuses on providing justifications for decisions has the potential to provide sufficient ground for perceived legitimacy without producing the harms full transparency would bring. (shrink)

The use of genetic engineering is increasingly discussed for nature conservation. At the same time, recent animal ethics approaches debate whether humans should genetically engineer wild animals to improve their welfare. This paper examines if obligations towards wild sentient animals require humans to genetically engineering wild animals, while arguing that there is no moral need to do so. The focus is on arguments from animal ethics, but they are linked to conservation ethics, highlighting the often neglected overlap between (...) the two fields. The paper emphasizes that a) the benefits of genetic engineering are overestimated and at the same time harms from its development and use underestimated, b) the assumption that genetic engineering is an appropriate ‘last resort’ tool is wrong, c) many arguments in favor of genetic engineering are based on an inadequate understanding of ecology and biotechnological processes, and d) the debate downplays the importance of self-determination for wild animals. (shrink)

Time and technology permeate the fabric of teamwork across a variety of settings to affect outcomes which have a wide range of consequences. However, there is a limited understanding about the interplay between these factors for teams, especially as applied to artificial intelligence (AI) technology. With the increasing integration of AI into human teams, we need to understand how environmental factors such as time scarcity interact with AI technology to affect team behaviors. To address this gap in the literature, we (...) investigated the interaction between the availability of intelligent technology and time scarcity in teams. Drawing from the theoretical perspective of computers are social actors and extant research on the use of heuristics and human–AI interaction, this study uses behavioral data from 56 teams who participated in a between-subjects 2 (intelligent assistant available × control/no intelligent assistant) × 2 (time scarcity × control/no time scarcity) lab experiment. Results show that teams working under time scarcity used the intelligent assistant more often and underperformed on a creative task compared to teams without the temporal constraints. Further, teams who had an intelligent assistant available to them had fewer interactions between members compared to teams who did not have the technology. Implications for research and applications are discussed. (shrink)

Correspondence held in the collections of cultural institutions is an important resource for researchers, including historians, biographers, and social scientists. Email has been the dominant form of correspondence for the last 30 years and email archives are now being acquired by cultural institutions as a valuable resource for their collections. There are challenges in collecting, preserving and providing access to email archives, as with all born-digital materials, but also challenges in using email archives as a researcher. One tool that (...) can help researchers use an email archive is visualisation. Visualisation has been applied to email for a long period of time but there has been little research into the visualisation needs of researchers using email archives. The preliminary outcomes of a research project investigating the needs of researchers suggests that visualisations will be useful to the researcher, who is always under the pressure of limited time, to work efficiently with the email archive. Artificial intelligence (AI) can play a role in preparing the email archive for visualisation. However, the research outcomes suggest that visualisations will be viewed cautiously by researchers who want time with the actual email archive to develop their research and they are unlikely to trust visualisations alone. The use of AI in the production of visualisations has the potential to add further barriers to researchers’ level of trust. (shrink)

The Fourth Industrial Revolution (4IR) and accompanying Fourth Order technologies (FOTs) sit at the confluence of epistemé and techné knowledge identified in classical Greek philosophy. The former is interpreted as scientific knowledge and discoveries, and the latter is its practical application in the form of “new” technologies and manufacturing processes. This helps explain both 4IR and FOT where 4IR is characterised by the science of digitisation and computerisation, and FOT by machines combining artificial intelligence (AI) and advanced machine learning (AML), (...) both key components in FOT functionality. Through the use of codification and algorithms, scientists and engineers are trying to imitate human thought and behaviour in ways devoid of human virtue and relationality, vital ingredients in the “lived” experience. Classical Aristotelian virtue theory is agent-based, but recognises the importance of the “lived experience”, both individual (self) and in terms of their relationality in the wider community (other). Phronesis, or practical wisdom, is a critical tool in Aristotelian virtue theory as it is theorised to assist the individual in their “lived” human experiences in the acquisition of both intellectual virtues (rational) and moral virtues (emotional), leading to a state of eudaimonia, or ultimate well-being for the individual (self) and eventually wider society (other). Aristotelian virtue theory understands that human life is not always calculable, measurable, or rational, but it has a corresponding and arguably deeper and more profound meaning and influence through the relative and moral brought about through the “lived” human experience and its iteration. (shrink)

This participatory study, conducted in an introductory psychology class, recounts self-reflections of 22 undergraduate students and their instructor engaging in an GenAI-mediated storyboard generation process. It relies on Gordon Pask’s conversation theory, structuring out the nature of interactions between students, instructor, and GenAI, and then uses a qualitative narrative to describe these conversational feedback loops constituting the creation of draft and final storyboards. Results suggest students engaged in cyclical feedback driven processes to master their creations, used elements of photography (...) related to the relationships between objects in frame, image processing, and cultural objects/themes to generate narratives. Issues were faced with generating text on images, and the consistency and style of generated frames as they interacted with GenAI tools. This study provides guidelines to university teaching professionals to design effective activities mediated by text-to-image GenAI. (shrink)

Machine ethics and robot rights are quickly becoming hot topics in artificial intelligence and robotics communities. We will argue that attempts to attribute moral agency and assign rights to all intelligent machines are misguided, whether applied to infrahuman or superhuman AIs, as are proposals to limit the negative effects of AIs by constraining their behavior. As an alternative, we propose a new science of safety engineering for intelligent artificial agents based on maximizing for what humans value. In particular, we (...) challenge the scientific community to develop intelligent systems that have human-friendly values that they provably retain, even under recursive self-improvement. (shrink)

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis to (...) show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to _collective_ and _individual use_. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of ‘speeding up—to keep up’ with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered. (shrink)

The progressive dissemination of artificial intelligence (AI) systems in work settings raises numerous questions and concerns regarding their consequences, whether positive or negative, on work activities and organizations. This paper presents an empirical study that was designed to identify and analyze these consequences in radiology. This study focuses on two AI systems: a voice recognition dictation system for radiological reports and a system for detecting fractures on X-rays images. Based on a qualitative analysis of field observations of work activities and (...) interviews with radiologists, emergency physicians, and medical secretaries, our findings help to provide a nuanced view on how AI may affect work in this sector. In contrast to the speculative discourse where AI is seen as a “positive” technology or as “threat” for workers, this study shows, on the one hand, how these kinds of AI systems help or may help these workers in their activities, and, on the other hand, how these systems raise problematic issues regarding their consequences not only for physicians but also for other workers such as medical assistants. (shrink)