The use of artificial intelligence in healthcare contexts is highly controversial for the (bio)ethical conundrums it creates. One of the main problems arising from its implementation is the lack of transparency of machine learning algorithms, which is thought to impede the patient’s autonomous choice regarding their medical decisions. If the patient is unable to clearly understand why and how an AI algorithm reached certain medical decision, their autonomy is being hovered. However, there are alternatives to prevent the negative impact of (...) AI opacity in shared (healthcare professional–patient) decision-making processes, and benefit from the high accuracy of such systems. Despite these ethical issues, this paper advocates for its usage and also defends the positive role that it could have in enhancing patients’ autonomy. I advocate for a system where the implementation of AI is only partial, and humans will remain in control of oversighting algorithm interpretation of medical images and patients’ data. (shrink)

In this paper, we delve into the significant impact of recent advancements in Artificial Intelligence (AI) on the future landscape of work. We discuss the looming possibility of mass unemployment triggered by AI and the societal repercussions of this transition. Despite the challenges this shift presents, we argue that it also unveils opportunities to mitigate social inequalities, combat global poverty, and empower individuals to follow their passions. Amidst this discussion, we also touch upon the existential question of the purpose of (...) human life in a world where machines predominantly perform work. Additionally, we explore the contentious issue of the moral status and rights of AI entities, contemplating the scenario where machines evolve to become sapient and sentient. The paper concludes with a call to action, emphasizing the necessity to acknowledge these potential outcomes and proactively seek solutions, as part of an inevitable journey through the evolution of human society shared with intelligent machines. (shrink)

Recent developments in artificial intelligence based on neural nets—deep learning and large language models which together I refer to as NEWAI—have resulted in startling improvements in language handling and the potential to keep up with changing human knowledge by learning from the internet. Nevertheless, examples such as ChatGPT, which is a ‘large language model’, have proved to have no moral compass: they answer queries with fabrications with the same fluency as they provide facts. I try to explain why this is, (...) basing the argument on the sociology of knowledge, particularly social studies of science, notably ‘studies of expertise and experience’ and the ‘fractal model’ of society. Learning from the internet is not the same as socialisation: NEWAI has no primary socialisation such as provides the foundations of human moral understanding. Instead, large language models are retrospectively socialised by human intervention in an attempt to align them with societally accepted ethics. Perhaps, as technology advances, large language models could come to understand speech and recognise objects sufficiently well to acquire the equivalent of primary socialisation. In the meantime, we must be vigilant about who is socialising them and be aware of the danger of their socialising us to align with them rather than vice-versa, an eventuality that would lead to the further erosion of the distinction between the true and the false giving further support to populism and fascism. (shrink)

This paper investigates the transformative influence of generative AI on the arts, connecting it with Walter Benjamin's insights regarding the aura of art in the mechanical reproduction era. It scrutinizes how generative AI not only redefines art's traditional aura but also introduces a dynamic interplay between technological liberation and dependency. The analysis extends to the democratization of artistic expression and its broader societal impacts, highlighting a shift in art creation, perception, and interpretation in the digital age. This research encapsulates the (...) evolving nature of authenticity, creativity, and human–machine collaboration, marking a significant paradigm shift in art's conception and its role in society. (shrink)

In this paper I articulate the question of whether machines can have emotions. I then reject a common argument against why they cannot have emotions based on the lack of a capacity for feelings. The goal of this paper is not to decisively show that machines can have emotions, but to decisively show that the naïve argument for the conclusion that they cannot needs to be critically examined. I argue that machines that have artificial general intelligence can have emotions based (...) on having the capacity to make judgments that are essential and constitutive of certain emotions, such as anger. I argue against the view that phenomenological or physiological profiles are essential to anger on the basis of emotion regulation. I consider a long list of objections to the position that machines can have emotions. (shrink)

National Artificial Intelligence (AI) strategies articulate imaginaries of the integration of AI into society and envision the governing of AI research, development and applications accordingly. To integrate these central aspects of national AI strategies under one coherent perspective, this paper presented an analysis of Germany’s strategy ‘AI made in Germany’ through the conceptual lens of ordoliberal political rationality. The first part of the paper analyses how the guiding vision of a human-centric AI not only adheres to ethical and legal principles (...) consistent with Germany’s liberal democratic constitutional system but also addresses the risks and promises inherent to the ordoliberal problematization of freedom. Second, it is scrutinized how the strategy cultivates the fear of not achieving technological sovereignty in the AI sector. Thereby, it frames the global AI race as a race of competing (national) approaches to governing AI and articulates an ordoliberal approach to governing AI (the ‘third way’), according to which government has to operate between the twin dangers of governing too much and not governing enough. Third, the paper analyses how this ordoliberal proportionality of governing structures Germany’s Science Technology & Innovation Policy. It is shown that the corresponding risk-based approach of regulating AI constitutes a security apparatus as it produces an assessment of fears: weighting the fear of the failure to innovate with the fear of the ramifications of innovation. Finally, two lines of critical engagement based on this analysis are conducted. (shrink)

It is increasingly recognized that as artificial intelligence becomes more powerful and pervasive in society and creates risks and ethical issues that cross borders, a global approach is needed for the governance of these risks. But why, exactly, do we need this and what does that mean? In this Open Forum paper, author argues for global governance of AI for moral reasons but also outlines the governance challenges that this project raises.

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)

Much has been written about the need for trustworthy artificial intelligence (AI), but the underlying meaning of trust and trustworthiness can vary or be used in confusing ways. It is not always clear whether individuals are speaking of a technology’s trustworthiness, a developer’s trustworthiness, or simply of gaining the trust of users by any means. In sociotechnical circles, trustworthiness is often used as a proxy for ‘the good’, illustrating the moral heights to which technologies and developers ought to aspire, at (...) times with a multitude of diverse requirements; or at other times, no specification at all. In philosophical circles, there is doubt that the concept of trust should be applied at all to technologies rather than their human creators. Nevertheless, people continue to intuitively reason about trust in technologies in their everyday language. This qualitative study employed an empirical ethics methodology to address how developers and users define and construct requirements for trust throughout development and use, through a series of interviews. We found that different accounts of trust (rational, affective, credentialist, norms based, relational) served as the basis for individual granting of trust in technologies and operators. Ultimately, the most significant requirement for user trust and assessment of trustworthiness was the accountability of AI developers for the outputs of AI systems, hinging on the identification of accountable moral agents and perceived value alignment between the user and developer’s interests. (shrink)

On February 13, 2020, the Toronto Police Services (TPS) issued a statement admitting that its members had used Clearview AI’s controversial facial recognition technology (FRT). The controversy sparked widespread outcry by the media, civil society, and community groups, and put pressure on policy-makers to address FRTs. Public consultations presented a key tool to contain the scandal in Toronto and across Canada. Drawing on media reports, policy documents, and expert interviews, we investigate four consultations held by the Toronto Police Services Board (...) (TPSB), the Office of the Privacy Commissioner (OPC), and the parliamentary Standing Committee on Access to Information, Privacy and Ethics (ETHI) to understand how public opinion and outrage translate into policy. We find that public consultations became a powerful closure mechanism in the policy-making toolbox, inhibiting rather than furthering democratic debate. Our findings show that consultations do not advance public literacy; that opportunities for public input are narrow; that timeframes are short; and that mechanisms for inclusion are limited. Even in the best-case circumstances, consultations are merely one of many factors in AI governance and seldom impact concrete policy outcomes in the cases studied here. (shrink)

This paper explores the intersection of René Girard's mimetic theory and the algorithmic society, particularly in the context of the potential advent of Artificial General Intelligence (AGI). Girard's theory, which elucidates the dynamics of desire, rivalry, scapegoating, and the sacrificial crisis, provides a unique lens through which to examine the complexities of our relationship with AI and its role in the creation of the sacred. As individuals increasingly rely on AI recommendations, the distinction between personal choice and algorithmic manipulation becomes (...) less clear, raising concerns about the authenticity of cultural expressions and the role of algorithms in shaping cultural narratives. The triangular structure of desire, with AI as the model and individuals as the imitators, underscores the power of algorithms in this process. The sacrificial crisis, a key concept in Girard's theory, becomes a critical point of reflection in the algorithmic society. The exposure of the scapegoating mechanism reveals the destructive potential of algorithmic manipulation and calls for new forms of understanding, empathy, and non-violent solutions. This paper argues that recognizing the sacrificial crisis can prompt individuals and society to critically examine the impact of AI's influence, challenge the narratives it perpetuates, and reclaim agency in the face of algorithmic dominance. This paper further discusses the potential implications of the emergence of AGI, which could intensify the influence of algorithms on the creation of the sacred due to its advanced cognitive capabilities and deep understanding of human desires and behaviors. This could fuel a rapid evolution of the mimetic ecosystem, with profound implications for personal freedom, independent decision-making, and the formation and preservation of individual identity. This paper concludes by emphasizing the need for responsible algorithmic practices and ethical considerations to ensure that the creation of the sacred serves the common good in the algorithmic society. (shrink)

The phenomenon of missed interactions between online users is a specific issue occurring when users of different language games interact on social media platforms. We use the lens of institutional theory to analyze this phenomenon and argue that current online institutions will necessarily fail to regulate user interactions in a way that creates common meanings because online institutions are not set up to deal with the multiplicity of language games and forms of life co-existing in the online social space. We (...) argue for the need to enable and foster grassroots online institutions that can stabilize the norms of interaction by redesigning algorithms and user interfaces. Such online grassroots institutions would facilitate user orientation at three distinct levels: informational, normative, and semantic-pragmatic. We propose user orientation as a principle that would facilitate the formation of institutions aiming to regulate information exchanges between users inhabiting various forms of life. This principle of user orientation should guide design decisions, while designer teams would need to become aware of the institutional power unleashed when they set up interfaces and algorithms for user-generated content. (shrink)

All theories of world creation, whether scientific, philosophical, or religious, can readily acknowledge the fact that humans have primarily evolved to engage with nature, the individual self, fellow human beings, society, and other naturalistic aspect of existence. Nevertheless, several novel challenges ascend when the human mind engages with technology, media, machines, and related concepts such as—ChatGPT, artificial intelligence, and to name a few. For that reason, we need philosophy and critical assessment of the uncovered essence of advanced technologies, media and (...) machines and our way of life concerning them. In other words, protectively assessing their impact requires a thorough examination of ethical and existential concerns, including technology’s implications for freedom, AI’s evolving role, the essence of human being, and the unexamined transformative societal changes that follow. Building upon the premise that these phenomena share a common thread despite their apparent disparities, our interdisciplinary pursuit draws inspiration from philosophical luminaries such as Luciano Floridi, Karamjit S. Gill, David Kaplan, Aldous Huxley, Martin Heidegger, Hannah Arendt, and Gandhi. Through philosophical insights, we explore the essence of technology and its broad effects, with a focus on its impact on human freedom and essence in both public and private domains. (shrink)

Fear and concerns regarding AI and robots have existed for a long time, and the emergence of strong artificial intelligence, on par with human intelligence, is likely just a few decades away. The primary purpose of this article is to establish a theoretical framework for navigating the relationship between humans and this advanced form of artificial intelligence. This article first points out that the most fundamental characteristic of life is its continuous process of evolution and iteration. By analyzing the developmental (...) history of intelligence in different species, it can be observed that intelligence also exhibits a similar evolutionary phenomenon. Therefore, from this perspective, intelligence can be defined as a new form of information life. Under this premise, similarities and differences between information life forms and conventional biological life become apparent. The most significant distinction lies in the fact that the survival of biological life is based on non-replicable matter and energy, leading to extensive competition and food chain phenomena within ecosystems. In contrast, the survival of information life relies more on replicable information, fostering tendencies towards peace and communication. Based on this theoretical premise, there is a potential for a harmonious coexistence between humans and AI. This theory also provides guidance for the positive development of human society. (shrink)

Machine learning algorithms have begun to enter clinical settings traditionally resistant to digitalisation, such as psychiatry. This raises questions around how algorithms will be incorporated in professionals’ practices, and with what implications for care provision. This paper addresses such questions by examining the pilot of an algorithm for the prediction of inpatient violence in two acute psychiatric clinics in the Netherlands. Violence is a prominent risk in acute psychiatry, and professional sensemaking, corrective measures (such as patient isolation and sedation), and (...) quantification instruments (such as the Brøset Violence Checklist, henceforth BVC) have previously been developed to deal with it. We juxtapose the different ways in which psychiatric nurses, the BVC, and algorithmic scores navigate assessments of the potential of future inpatient violence. We find that nurses approach violence assessment with an attitude of doubt and precaution: they aim to understand warning signs and probe alternative explanations to them, so as not to punish patients when not necessary. Being in charge of quantitative capture, they incorporate this attitude of doubt in the BVC scores. Conversely, the algorithmic risk scores import a logic of pre-emption into the clinic: they attempt to flag targets before warning signs manifests and are noticed by nurses. Pre-emption translates into punitive attitudes towards patients, to which nurses refuse to subscribe. During the pilots, nurses solely engage with algorithmic scores by attempting to reinstate doubt in them. We argue that pre-emption can hardly be incorporated into professional decision-making without importing punitive attitudes. As such, algorithmic outputs targeting ethically laden instances of decision-making are a cause for academic and political concern. (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)

Several competing narratives drive the contemporary AI ethics discourse. At the two extremes are sociotechnical dogmatism, which holds that society is full of inefficiencies and imperfections that can only be solved by better technology; and sociotechnical skepticism, which highlights the unacceptable risks AI systems pose. While both narratives have their merits, they are ultimately reductive and limiting. As a constructive synthesis, we introduce and defend sociotechnical pragmatism—a narrative that emphasizes the central role of context and human agency in designing and (...) evaluating emerging technologies. In doing so, we offer two novel contributions. First, we demonstrate how ethical and epistemological considerations are intertwined in the AI ethics discourse by tracing the dialectical interplay between dogmatic and skeptical narratives across disciplines. Second, we show through examples how sociotechnical pragmatism does more to promote fair and transparent AI than dogmatic or skeptical alternatives. By spelling out the assumptions that underpin sociotechnical pragmatism, we articulate a robust stance for policymakers and scholars who seek to enable societies to reap the benefits of AI while managing the associated risks through feasible, effective, and proportionate governance. (shrink)

Artificial intelligence (AI) is rapidly changing the way that art is created and consumed, allowing artists to create unique, engaging works with high computing power that can supplement their creative process. This manuscript explores the creative process of using AI technology in digital art to create paintings and evaluates creativity based on the aesthetic value and components of works created by AI. This research seeks to understand how AI technology influences the art world through a practice-led methodology with a descriptive (...) qualitative approach and observational methodology. Pioneering artwork such as Edmond de Belamy, created by French collective obvious using generative adversarial networks (GANs), has raised questions among the creative fields concerning originality, creativity, and authorship. Through analyses of AI-generated artwork and comparison with traditional artwork, the research investigates potential opportunities and challenges that AI presents to the art world. Ultimately, AI technology can provide a creative spark for human artists who, with an appropriate understanding of the limitations of AI algorithms, can create incredible pieces of art that embrace the contributions of both humans and machines. This research seeks to fill in the gaps left by earlier works and provide a more multi-faceted look at the changing landscape of AI in art, gaining a better understanding of the ways AI is impacting the art world and what the future may look like in the coming years. (shrink)

The recent emergence of generative AI software as viable tools for use in the cultural and creative industries has sparked debates about the potential for “creativity” to be automated and “augmented” by algorithmic machines. Such discussions, however, begin from an ontological position, attempting to define creativity by either falling prey to universalism (i.e. “creativity is X”) or reductionism (i.e. “only humans can be truly creative” or “human creativity will be fully replaced by creative machines”). Furthermore, such an approach evades addressing (...) the real and material impacts of AI on creative labour in these industries. This article thus offers more expansive methodological and conceptual approaches to the recent hype on generative AI. By combining (Csikszentmihalyi, The systems model of creativity, Springer, Dordrecht, 2014) systems view of creativity, in which we emphasise the shift from “what” to “where” is creativity, with (Lievrouw, Media technologies, The MIT Press, 2014) relational-materialist theory of “mediation”, we argue that the study of “creativity” in the context of generative AI must be attentive to the interactions between technologies, practices, and social arrangements. When exploring the relational space between these elements, three core concepts become pertinent: creative labour, automation, and distributed agency. Critiquing “creativity” through these conceptual lenses allows us to re-situate the use of generative AI within discourses of labour in post-industrial capitalism and brings us to a conceptualisation of creativity that privileges neither the human user nor machine algorithm but instead emphasises a relational and distributed form of agency. (shrink)

Narrative generation is growing in importance for data utilization, particularly in the context of co-creation with artificial intelligence (AI) agents. Narratives can, for example, bridge theoretical objects with social understanding and promote human actions. Furthermore, clarifying the narrative generation mechanism is essential for constructing effective relationships between humans and AI agents. However, the narrative generation mechanism in data utilization processes has not been fully elucidated. In this study, we developed a framework called the hierarchical narrative representation (HieNaR) to systematize the (...) structure of narrative generation in data utilization processes. HieNaR comprises twelve levels, ranging from the set of texts down to the particle level (e.g., text, sentence, word, character, and stroke), allowing for a comprehensive analysis of narrative structures. We evaluated the usefulness of HieNaR through case studies, examining both individual user experiences and collaborative work between humans and an AI agent. The results demonstrated that the data utilization process interprets data by inquiring whether it satisfies higher-level expectations. In collaboration, AI agents can be understood as co-creative partners in data utilization, possessing their own worldviews. Through these findings, this study not only elucidates the mechanism of narrative generation in data utilization processes but also provides a foundation for improving human–AI collaboration. (shrink)

Deepfakes, as hyperrealistic digital fabrications, reveal gaps and uncertainties in existing ontological frameworks. Neither simply images nor realities, deepfakes occupy an ambiguous metaphysical position between concepts such as representation/simulation, human/machine, and real/artificial. Their emergent generation via AI and experiential traction as credible synthetic media underscores limitations in prevailing paradigms reliant on purified binaries and anthropocentric assumptions. Rather than anomalies, deepfakes epitomize the imperative for new ontological cartographies and conceptual vocabularies attuned to increasingly unbounded algorithmic creation. The paper surveys debates about (...) digital objects and theories of representation to contextualize this argument. Deepfakes’ ontological novelty stems from their ambiguous origins, autonomous proliferation, and infiltration of perceivable situations with credible fictions. This destabilizes ontological foundations such as creative intentionality and indexical truth. I conclude deepfakes signal the insufficiency of existing ontology for navigating realities transformed by generative technologies. New paradigms are needed that grapple with their radical metaphysical challenges. (shrink)

Over the years, the urban heat vulnerability has evolved as a pressing global concern for researchers and policymakers alike. Numerous studies have aimed at mitigating the adverse effects of urban heat vulnerability on public health and safety. However, the critical task of selecting the most fitting indicator for urban heat islands in public spaces is not emphasized in the existing studies, considering the diverse indices available. Beyond identification, studies that delve into the prioritization of these indices and the determination of (...) optimal variables along with their respective weights are scanty. The present study attempts to address these gaps in urban heat vulnerability research through the lens of natural solutions. The study employs a fuzzy analytical hierarchy approach to ascertain the weights of selected criteria, providing a nuanced understanding of the multifaceted factors influencing their applicability. Real-time impact estimation using the fuzzy technique for order of preference by similarity to ideal solutions enhances the practicality of the findings. The results reveal a set of pivotal characteristics crucial for constructing a robust heat vulnerability index, facilitating the prioritization of selected criteria. The implementation of this hybrid methodology culminates in a streamlined, precise, and practical tool for evaluating heat vulnerability in hot urban public spaces. These findings contribute valuable insights to the academic discourse and offer a tangible resource for policymakers and practitioners. The proactive approach provides a roadmap for addressing impending challenges related to urban heat vulnerability, marking a positive step toward creating resilient and sustainable urban environments. (shrink)

In this paper, we will survey the different uses of the term algorithm in contemporary legal practice. We will argue that the concept of algorithm currently exhibits a substantial degree of open texture, co-determined by the open texture of the concept of algorithm itself and by the open texture inherent to legal discourse. We will substantiate our argument by virtue of a case study, in which we analyze a recent jurisprudential case where the first and second-degree judges have carved-out contrasting (...) notions of algorithm. We will see that, thanks to our analysis of the open texture of the notion of algorithm in legal language, we can make sense of the different decisions taken by the judges as different contextually-determined sharpenings of the concept of algorithm. Finally, we will draw some general conclusions concerning the use of technical terms in legal instruments that address new technologies, such as the EU AI Act. (shrink)

Artificial intelligence (AI) is being tightly integrated into healthcare today. Even though AI is being utilized in healthcare, its application in clinical settings and health professions education is still controversial. The study described the perceptions of AI and its integration into health professions education and healthcare among health professions students. This descriptive phenomenological study analyzed the data from a purposive sample of 33 health professions students at a university in Kazakhstan using the thematic approach. Data collection was conducted from March (...) 30 to May 5, 2023, using an online questionnaire with four open-ended questions. Four significant themes describing the perceptions of the health professions students on AI and its integration into health profession education and healthcare was derived: enhanced interactive learning experiences, integrating artificial intelligence-powered diagnostic and decision-support tools into health professions education, AI technologies assist students in preparing for future roles in healthcare and integrating AI technologies presents several challenges. Health professions students perceived that integrating AI into health professions education and healthcare enhances their interactive learning experiences, increases knowledge and application of complicated medical topics, and prepares them for future healthcare roles. (shrink)

As computational systems burgeon with advancing artificial intelligence (AI), the deterministic frameworks underlying them face novel challenges, especially when interfacing with self-modifying code. The Executioner Paradox, introduced herein, exemplifies such a challenge where a deterministic Executioner Machine (EM) grapples with self-aware and self-modifying code. This unveils a self-referential dilemma, highlighting a gap in current deterministic computational frameworks when faced with self-evolving code. In this article, the Executioner Paradox is proposed, highlighting the nuanced interactions between deterministic decision-making and self-aware code, and (...) the ensuing challenges. This article advocates for a re-evaluation of existing deterministic frameworks, emphasizing the need for adaptive decision-making mechanisms in computational systems. By dissecting the Executioner Paradox, the aim is to foster a robust discussion on evolving deterministic frameworks to accommodate the dynamic nature of self-modifying code, thereby contributing a forward-looking lens to the discourse on computational systems amidst advancing AI. (shrink)

Evidence on AI acceptance comes from a diverse field comprising public opinion research and largely experimental studies from various disciplines. Differing theoretical approaches in this research, however, imply heterogeneous ways of studying AI acceptance. The present paper provides a framework for systematizing different uses. It identifies three families of theoretical perspectives informing research on AI acceptance—user acceptance, delegation acceptance, and societal adoption acceptance. These models differ in scope, each has elements specific to them, and the connotation of technology acceptance thus (...) changes when shifting perspective. The discussion points to a need for combining the three perspectives as they have all become relevant for AI. A combined approach serves to systematically relate findings from different studies. And as AI systems affect people in different constellations and no single perspective can accommodate them all, building blocks from several perspectives are needed to comprehensively study how AI is perceived in society. (shrink)

The guide dog robot (GDR) is a low-speed companion robot that serves visually impaired people and is used to guide blind people to walk steadily, carrying a variety of intelligent technologies and needing to have the ability to guide with optimal energy consumption in specific scenarios. This paper proposes an innovative technique for virtual-real collaborative path planning and navigation of the GDR specific indoor scenarios, and designs an experimental method for virtual-real collaborative path planning of the GDR specific scenarios. The (...) energy consumption integral equation is used to solve for the energy consumption of the GDR with virtual-real synergy, and the difference in energy consumption is compared for three different navigation directions: horizontal, vertical and oblique obstacle avoidance. The results show that the optimized GDR saves 6.91% in rectilinear movement and 10.60% in curved movement. The efficiency of planning and navigating the GDR in specific domestic scenarios is verified by a virtual-real cooperative. The realization of optimal path planning for energy consumption is instrumental in exploring many of the most significant thought in the path planning and navigation of mobile robots in indoor specific scenarios. (shrink)

Don Ihde’s alterity relation focuses on the quasi-otherness of dynamic technologies that interact with humans. The alterity relation is one means to study relations between humans and artificial intelligence (AI) systems. However, research on alterity relations has not defined the difference between playing with a toy, using a computer, and interacting with a social robot or chatbot. We suggest that Ihde’s quasi-other concept fails to account for the interactivity, autonomy, and adaptability of social robots and chatbots, which more closely approach (...) human alterity. In this article, we will examine experiences with a chatbot, Replika, and a humanoid robot, a RealDoll, to show how some users experience AI systems as companions. First, we show that the perception of social robots and chatbots as intimate companions is grounded in communication. Advances in natural language processing (NLP) and natural language generation (NLG) allow a relationship to form between some users and social robots and chatbots. In this relationship, some users experience social robots and chatbots as more than quasi-others. We will use Kanemitsu’s another-other concept to analyze cases where social robots and chatbots should be distinguished from quasi-others. (shrink)

Artificial intelligence (AI) systems will increasingly be used to cause harm as they grow more capable. In fact, AI systems are already starting to help automate fraudulent activities, violate human rights, create harmful fake images, and identify dangerous toxins. To prevent some misuses of AI, we argue that targeted interventions on certain capabilities will be warranted. These restrictions may include controlling who can access certain types of AI models, what they can be used for, whether outputs are filtered or can (...) be traced back to their user, and the resources needed to develop them. We also contend that new restrictions on non-AI capabilities needed to cause harm will be required. For example, concerns about AI-enabled bioweapon acquisition have motivated efforts to introduce DNA synthesis screening. Though capability restrictions risk reducing use more than misuse (resulting in an unfavorable Misuse–Use Tradeoff), we argue that interventions on capabilities are warranted in some circumstances when other interventions are insufficient, the potential harm from misuse is high, and there are targeted interventions. We provide a taxonomy of interventions that can reduce AI misuse, focusing on the specific steps required for a misuse to cause harm (the Misuse Chain), and a framework to determine if an intervention is warranted. We exemplify our framework to three examples: predicting novel toxins, creating harmful images, and automating spear phishing campaigns. (shrink)

This paper asks whether workers’ experience of working with new technologies and workers’ perceived threats of new technologies are associated with expected well-being. Using survey data for 25 OECD countries we find that both experiences of new technologies and threats of new technologies are associated with more concern about expected well-being. Controlling for the negative experiences of COVID-19 on workers and their macroeconomic outlook both mitigate these findings, but workers with negative experiences of working alongside and with new technologies still (...) report lower expected well-being. (shrink)

This article analyses the forms of dividuation workers undergo when they are linked to technologies, such as algorithms or artificial intelligence. It examines functionalities and operations deployed by certain types of Talent Management software and apps—UKG, Tribepad, Afiniti, RetailNext and Textio. Specifically, it analyses how talented workers materialise in relation to the profiles and the statistical models generated by such artificial intelligence machines. It argues that these operate as a nooscope that allows the transindividual plane to be quantified through a (...) process known as dividuation. Finally, by way of conclusion, the notion of the dividual is presented as the logic that characterises the human–machine relationship in the case of artificial intelligence and as the horizon of what Felix Guattari called “machinic capitalism”. (shrink)

Since the beginning of the current hype around Artificial Intelligence (AI), governments, research institutions, and the industry invited ethical, legal, and social sciences (ELS) scholars to research AI’s societal challenges from various disciplinary viewpoints and perspectives. This approach builds upon the tradition of supporting research on the societal aspects of emerging sciences and technologies, which started with the Ethical, Legal, and Social Implications (ELSI) Program in the Human Genome Project (HGP) in the early 1990s. However, although a diverse ELS research (...) community has formed since then, AI’s societal challenges came to be mostly understood under the narrow framing of ethics and disconnected from the insights and experiences of past ELS research. In this article, we make up for this gap and connect insights from past ELS researchers with current approaches to research the societal challenges of AI. We analyse and summarize the history of “ELS programs” (programs that emerged since the HGP to support ELS research in a given domain) as three distinct eras: a genomics era, a nano era, and an RRI era. Each of these eras comprises several achievements and challenges relevant to ELS programs in AI research, such as the setup of independent funding bodies, the engagement of the wider public in research practice, and the increasing importance of private actors. Based on these insights, we argue that AI research currently falls back on self-regulatory, less participatory, and industry-led approaches that trouble ELS programs’ past achievements and hinder opportunities to overcome the still-existing challenges. (shrink)

Biases and misunderstanding stemming from pre-training in Generative Pre-Trained Transformers are more likely for users of underrepresented English varieties, since the training dataset favors dominant Englishes (e.g., American English). We investigate (potential) bias in GPT-4 when it interacts with Trinidadian English Creole (TEC), a non-hegemonic English variety that partially overlaps with standardized English (SE) but still contains distinctive characteristics. (1) Comparable responses: we asked GPT-4 18 questions in TEC and SE and compared the content and detail of the responses. (2) (...) Accurate translation: we assessed how accurate and authentic 29 TEC and 34 SE translations were. (3) Language knowledge and attitudes: we asked what language the prompts were written in and categorized the responses and examined any language attitudes that were exhibited. Content and detail in prompts were comparable. The model was proficient at translating TEC pronouns and many grammatical categories. It was weaker at processing spelling and vocabulary items. In addition, it produced several inauthentic features. Only 39% of TEC-generated sentences were fully grammatical. While GPT-4 was perfect at identifying SE, it was 21% accurate at identifying TEC, which it sometimes classified as English with “errors” and “corrected”. GPT-4’s scope of use is limited for non-hegemonic English users. It is problematic that some of its analyses perpetuate bias against underrepresented Englishes. Increased research on lesser-documented Englishes is necessary and we anticipate that this problem affects dialects of other languages. We intend to partner with Trinidadian stakeholders to train GPT-4 in the future. (shrink)

Recent technological advances have accelerated the use of artificial intelligence (AI) in the world. Public concerns over AI in ethical, legal, and social issues (ELSI) may have been enhanced, but their awareness has not been fully examined between countries and cultures. We created four scenarios regarding the use of AI: “voice,” “recruiting,” “face,” and “immigration,” and compared public concerns in Japan, the US, Germany, and the Republic of Korea (hereafter Korea). Additionally, public ELSI concerns in respect of AI were measured (...) using four items: ethics, tradition, law and social benefit. Respondents with AI knowledge tended to exhibit stronger concern about ELSI in various situations. In terms of law concerns, Japanese respondents displayed greater concerns. In contrast, the US, when compared Japan, expressed a relatively optimistic view of the current law landscape. Regarding social benefits, Korea, compared to Japan, exhibited a more positive outlook, whereas Germany, in comparison to Japan, expressed heightened concerns about it across different scenarios. (shrink)

This study addresses the critical shortage of parallel corpora for the Kashmiri language, a significant barrier to advancing language processing technologies for under-resourced languages. Despite Kashmiri's rich cultural heritage, the development of language technology resources, especially parallel corpora, has been notably limited. Our research involves a detailed analysis of the only available parallel corpora for Kashmiri, utilizing these datasets to develop and evaluate Neural Machine Translation (NMT) models. Through this evaluation, we categorize errors and assess the corpora's adequacy in quality (...) and quantity for supporting effective language processing tasks. Additionally, we investigate the reasons behind the scarcity of high-quality resources and identify the challenges inherent in creating robust parallel corpora for Kashmiri. By proposing solutions to these challenges, our study aims to contribute to the revitalization and global recognition of the Kashmiri language, bridging a significant gap in the field of language technology and emphasizing the importance of parallel corpora in preserving linguistic diversity and facilitating technological advancement. (shrink)

Public administrations, including national government agencies as well as the EU institutions, face not only structural changes, but are increasingly talking about the need to transform management, foster innovation, and share responsibilities. The role of AI is the key composite element of this process. However, not only from the technological point of view. AI also needs the human “perspective”. It is very important to include the so-called soft components (institutional culture, inter-cultural awareness, and organizational needs) to facilitate the mental shift (...) and thus the buy-in. Technological advances in the area of AI inevitably result in further change and this alteration has to be managed. A need to break silo mentality moves organizations towards matrix-based structures with advanced reporting relationships. With the focus on the people side of change and the boundaries of the data-driven decision-making, this study provides insights in the correlations between AI as a tool and change process in public administrations. (shrink)

Monitoring and assistive technologies (MATs) are being used more frequently in healthcare. A central ethical concern is the compatibility of these systems with the moral preferences of their users—an issue especially relevant to participatory approaches within the ethics-by-design debate. However, users’ incapacity to communicate preferences or to participate in design processes, e.g., due to dementia, presents a hurdle for participatory ethics-by-design approaches. In this paper, we explore the question of how the value preferences of users in the field of dementia (...) care can be integrated into AI-based MATs. First, we briefly introduce different ethics-by-design approaches and explain the challenges they face in dementia care. Next, we introduce a novel approach for addressing these challenges. Through a qualitative content analysis of interviews with persons with dementia and their family caregivers (n = 27), we identified multiple ideal–typical value preference profiles. We then applied these profiles in a computer simulation, by which we also introduce the concept of ethical compliance quantification to scale the moral preferences of the interviewees for the simulation. Finally, we discuss study results, the advantages of using computer simulations, and general study limitations before drawing conclusions for further research. The study contributes to the ongoing debate on participatory ethics-by-design by defining on the basis of empirical data ideal–typical value preference frameworks that can be used to guide MAT actions and their outcomes. Going forward, MAT end-users with dementia and other communication-impaired persons could be enabled to choose a value profile that best fits their moral preferences. (shrink)