In the last few years, we have witnessed a surge in scholarly interest and scientific evidence of how algorithms can produce discriminatory outcomes, especially with regard to gender and race. However, the analysis of fairness and bias in AI, important for the debate of AI for social good, has paid insufficient attention to the category of age and older people. Ageing populations have been largely neglected during the turn to digitality and AI. In this article, the concept of AI ageism (...) is presented to make a theoretical contribution to how the understanding of inclusion and exclusion within the field of AI can be expanded to include the category of age. AI ageism can be defined as practices and ideologies operating within the field of AI, which exclude, discriminate, or neglect the interests, experiences, and needs of older population and can be manifested in five interconnected forms: (1) age biases in algorithms and datasets (technical level), (2) age stereotypes, prejudices and ideologies of actors in AI (individual level), (3) invisibility of old age in discourses on AI (discourse level), (4) discriminatory effects of use of AI technology on different age groups (group level), (5) exclusion as users of AI technology, services and products (user level). Additionally, the paper provides empirical illustrations of the way ageism operates in these five forms. (shrink)

This study investigates the mechanism of how sensory experiences influence visitors’ digital engagement with a destination through establishing a strong bond and identification between a destination and tourist utilizing a two-step process. First, visitors’ sensory experiences in a destination are identified through a content analysis of online review comments posted by visitors. Afterward, the effects of those sensory experiences on visitors’ digital engagement through destination dependence and identification with that destination are examined. Findings suggest that sensory experiences are critical (...) antecedents of visitors’ bond and identification with a destination. Visitors’ positive destination-related sensory experiences increase their dependence on and identification with the destination, and this dependence and identification positively influence their digital engagement behavior on social media. (shrink)

Large language models (LLMs) such as ChatGPT are opening up new areas of research and teaching potential across a variety of domains. The purpose of the present conceptual paper is to map this new terrain from the point of view of Critical Discourse Studies (CDS). We demonstrate that the usage of LLMs raises concerns that definitely fall within the remit of CDS; among them, power and inequality. After an initial explanation of LLMs, we focus on three key areas (...) of reflection. The first is a general stock-taking, where we look at CDS’ theoretical underpinnings and what they imply for working with AI-generated language data. The second issue is authorship, where we assess the traceability of linguistic metadata and the ethically sensitive situation with regard to ownership of texts. The third area is linguistic homogenisation, where we examine how LLM usage privileges the mainstream. Afterwards, we explore ways in which LLMs could be used in research, and we discuss the implications of exploring their use in the classroom through a CDS lens. We close the paper with some observations on likely future developments in AI and how CDS can contribute with its distinctive theoretical, methodological and critical apparatus. (shrink)

To realize the coordinated and sustainable development of hydropower projects and regional society, comprehensively evaluating hydropower projects’ influence is critical. Usually, hydropower project development has an impact on environmental geology and social and regional cultural development. Based on comprehensive consideration of complicated geological conditions, fragile ecological environment, resettlement of reservoir area, and other factors of future hydropower development in each country, we have constructed a comprehensive evaluation index system of hydropower projects, including 4 first-level indicators of social economy, environment, (...) safety, and fairness, which contain 26 second-level indicators. To solve the problem that existing models cannot evaluate dynamic nonlinear optimization, a projection pursuit model is constructed by using rough set reduction theory to simplify the index. Then, an accelerated genetic algorithm based on real number coding is used to solve the model and empirical study is carried out with the Y hydropower station as a sample. The evaluation results show that the evaluation index system and assessment model constructed in our paper effectively reduce the subjectivity of index weight. Applying our model to the social impact assessment of related international hydropower projects can not only comprehensively analyze the social impact of hydropower projects but also identify important social influencing factors and effectively analyze the social impact level of each dimension. Furthermore, SIA assessment can be conducive to project decision-making, avoiding social risks and social stability. (shrink)

Here I use aspects of Phil Graham’s discourse analytical work to examine forms of e/valuations and critically analyse the formulation of truths in the constitution of Artificial Intelligence (hereafter, AI). This paper focuses on two 2019 documents: Ethics guidelines for trustworthy AI (AI HLEG, Citation2019a) and Policy and investment recommendations for trustworthy AI (AI HLEG, Citation2019b). My aim here is to provide a timely contribution to contemporary philosophical–methodological innovations in documenting the constellation of values that are prefigured in human-centric constructions (...) of AI. The analysis is informed primarily by principles from Graham’s distinctive approach to critical discourse analysis (CDA), which I take to be the philosophical study of valuation. In that approach, political economy is taken as a composite formulation of values whereby neo-liberalism is discursively entwined and progressed through a system of principles of e/valuation. This paper presents a roadmap to demonstrate the usefulness of a philosophically grounded interdisciplinary piece of linguistic research through which evaluative semantic categories can be usefully synthesised with CDA to systematically expose the assumptions which underpin current truth claims and values – in this case, about and around the ethics of AI. (shrink)

In response to calls for greater interdisciplinary involvement from the social sciences and humanities in the development, governance, and study of artificial intelligence systems, this paper presents one sociologist’s view on the problem of algorithmic bias and the reproduction of societal bias. Discussions of bias in AI cover much of the same conceptual terrain that sociologists studying inequality have long understood using more specific terms and theories. Concerns over reproducing societal bias should be informed by an understanding of the ways (...) that inequality is continually reproduced in society—processes that AI systems are either complicit in, or can be designed to disrupt and counter. The contrast presented here is between conservative and radical approaches to AI, with conservatism referring to dominant tendencies that reproduce and strengthen the status quo, while radical approaches work to disrupt systemic forms of inequality. The limitations of a conservative approach to racial bias are discussed through the specific example of biased criminal risk assessments and Indigenous overrepresentation in Canada’s criminal justice system. This illustrates the dangers of treating racial bias as a generalizable problem and equality as a generalizable solution, emphasizing the importance of considering inequality in context. Societal issues can no longer be out of scope for AI and machine learning, given the impact of these systems on human lives. This requires engagement with a growing body of critical AI scholarship that goes beyond biased data to analyze structured ways of perpetuating inequality, opening up the possibility for interdisciplinary engagement and radical alternatives. (shrink)

Upon previous research, the matrilineal system seems to oppose Islamic teaching. However, the matrilineal system practiced by the Minangkabau society in West Sumatra, Indonesia has its uniqueness. Thus, this study aims to examine the correlation between the Qur’an and gender roles within the context of Minangkabau customs, specifically focusing on the matrilineal aspect. The present study employs qualitative methods for conducting library research through critical analysis. This study discovered that the matrilineal system practiced by the Minangkabau society aligns with (...) Qur’anic teachings that respect the position of women in Islam. In the matrilineal system of Minangkabau, women hold significant strength and play an influential role in cultural and traditional practices. The Minangkabau tribe’s matrilineal system encompasses three key elements: marriage, inheritance and offspring. The marriage system is exogamous. Additionally, the practice of marriage is localised, with the husband typically residing in the wife’s household. Their inheritance is divided into pusako tinggi [from ancestors from generation to generation] and pusako randah (from the efforts of married couple). Women get pusako tinggi as they serve as protectors and a symbol of their community. In comparison, men take the responsibility of overseeing its preservation to prevent any form of misuse. Pusako randah is distributed as Islamic teaching. Lineage determination is primarily based on paternal lineage, aligning with Islamic teaching. Upon comprehensive analysis, it becomes evident that there is no conflict between the matrilineal system and Islamic teachings, particularly concerning principles of gender equality. Both women and men have significant roles, as the Qur’an provides extensive explanations regarding gender equality.Contribution: This research holds significant findings in establishing a great relation between Islamic teachings based on the Qur’an and the matrilineal principles practiced by the Minangkabau tribe. (shrink)

Despite its elusiveness as a concept, ‘artificial intelligence’ (AI) is becoming part of everyday life, and a range of empirical and methodological approaches to social studies of AI now span many disciplines. This article reviews the scope of ethnomethodological and conversation analytic (EM/CA) approaches that treat AI as a phenomenon emerging in and through the situated organization of social interaction. Although this approach has been very influential in the field of computational technology since the 1980s, AI has only recently (...) emerged as such a pervasive part of daily life to warrant a sustained empirical focus in EM/CA. Reviewing over 50 peer-reviewed publications, we find that the studies focus on various social and group activities such as task-oriented situations, semi-experimental setups, play, and everyday interactions. They also involve a range of participant categories including children, older participants, and people with disabilities. Most of the reviewed studies apply CA’s conceptual apparatus, its approach to data analysis, and core topics such as turn-taking and repair. We find that across this corpus, studies center on three key themes: openings and closing the interaction, miscommunication, and non-verbal aspects of interaction. In the discussion, we reflect on EM studies that differ from those in our corpus by focusing on praxeological respecifications of AI-related phenomena. Concurrently, we offer a critical reflection on the work of literature reviewing, and explore the tortuous relationship between EM and CA in the area of research on AI. (shrink)

This paper reframes the issue of appropriation, extraction, and dispossession through AI—an assemblage of machine learning models trained on big data—in terms of enclosure and foreclosure. While enclosures are the product of a well-studied set of operations pertaining to both the constitution of the sovereign State and the primitive accumulation of capital, here, I want to recover an older form of the enclosure operation to then contrast it with foreclosure to better understand the effects of current algorithmic rationality. I argue (...) that the act of enclosing is to be understood as a set of fundamental operations that consist in producing structural distinctions between inside and outside, inclusion and exclusion—whether by drawing lines on a map, constructing border walls, or by algorithmically categorizing and (mis)recognizing people and things. Tracking the transformation of an enclosure-logic into one of foreclosure, I show how current AI perpetuates and at the same time expends forms of extraction, exclusion, and dispossession toward a totalizing horizon. For, while the outside is essential and constitutive to the logic of enclosure, foreclosure, by contrast, is characterized by the “totalizing desire” to not leave anything out of it. The totalizing desire to move beyond the logic of the enclosure forecloses that the enclosure has just gotten bigger and that the operations of exclusion have been masked and displaced, making them harder to contest. (shrink)

Member States of the United Nations proposed Seventeen Sustainable Development Goals (SDGs) in 2015, emphasizing the well-being of people, planet, prosperity, peace, and partnership. Countries are expected to work diligently to achieve these goals by the year 2030. The paths chosen to achieve the SDGs depend on each country’s specific needs, challenges, and opportunities. This contribution conducts a bibliometric study of selected SDG research related to hunger and climate change among countries of the North Asia Pacific region. A review of (...) literature related to the seventeen SDGs is provided to update the current research in SDGs as a background for the regional bibliometric search. The academic published literature related to this work were collected and text mined to create a research database for trend analysis. In this research, the natural language model KeyBERT and a text mining algorithm for normalized term frequency were used to extract key terminologies for bibliometric analysis. The study provides an overview of the seventeen SDGs in the literature review and then focuses on SDG 2 (zero hunger) and SDG 13 (climate action) publication trends. These two SDGs are in close alignment with sustainable food systems and agricultural development. The conclusion indicates that greater cooperation (SDG 17) is critical to improving the quality of life within the region and in building an ethical framework that restricts external exploitation of resources that benefit newly developed economies over developing economies. (shrink)

In recent years, there has been a growing public discourse regarding the influence AI will have on the future of work. Simultaneously, considerable critical attention has been given to the implications of AI on gender equality. Far from making precise predictions about the future, this discourse demonstrates that new technologies are instances for renegotiating the relation of gender and work. This paper examines how gender is addressed in news media discourse on AI and the future of work, focusing on (...) Germany. We approach this question from a perspective of feminist technology studies and discourse analysis, exploring a corpus of 178 articles from 2015 to 2021 from German newspapers and newsmagazines. The findings indicate that critical AI and gender knowledge circulates in public discourse in the form of specific discursive frames, thematizing algorithmic bias, automatization and enhancement, and gender stereotypes. As a result, we show that, first, the discourse takes up feminist and scholarly discourse on gender and discusses AI in a way that is informed by social constructivism and standpoint theories. Second, gender appears as a—to some extent intersectional—diversity category which is critical to AI, while at the same time omitting important perspectives. Third, it can be shown that there is a renegotiating of the ideal worker norm taking place, and finally, we argue that the gendered frame of the powerful men developer responsible for AI’s risk is a concept to be challenged. (shrink)

Background Caring behaviour is critical for nursing quality, and the clinical internship environment is a crucial setting for preparing nursing students for caring behaviours. Evidence about how to develop nursing students’ caring behaviour in the clinical environment is still emerging. However, the mechanism between the clinical internship environment and caring behaviour remains unclear, especially the mediating role of moral sensitivity and the moderating effect of self-efficacy. Research objective This study aimed to examine the mediating effect of moral sensitivity and (...) the moderating function of self-efficacy on the association between the clinical internship environment and caring behaviours. Research design A cross-sectional design used acceptable validity scales. The hypothesised moderated mediation model was tested in the SPSS PROCESS macro. Participants and research context This survey collected data from 504 nursing students in an internship at a teaching hospital in Changsha, China. Ethical considerations This study was pre-approved by the ethics committee of the medical school (No. E2022210). Informed consent was obtained from all students. Results The clinical internship environment ( B = 0.450, 95% CI = [0.371, 0.530]) and moral sensitivity ( B = 1.352, 95% CI = [1.090, 1.615]) had positive direct effects on nursing students' caring behaviours. Clinical internship environment also indirectly influenced students’ caring behaviours via moral sensitivity ( B = 0.161, 95% CI = [0.115, 0.206]). In addition, self-efficacy played a moderating role between the clinical internship environment and caring behaviours ( B = 0.019, 95% CI = [0.007, 0.031]), as well as the relationship between the clinical internship environment and moral sensitivity ( B = 0.006, 95% CI = [0.003, 0.010]). Conclusion Moral sensitivity mediates the effect of the clinical internship environment on caring behaviour, and self-efficacy strengthens both direct and indirect effects. This study emphasises the importance of self-efficacy in developing moral sensitivity and caring behaviours in nursing students. (shrink)

This paper seeks to bypass assumptions that researchers in critical algorithmic studies and urban studies find it difficult to study algorithmic systems due to their black-boxed nature. In addition, it seeks to work against the assumption that advocating for transparency in algorithms is, therefore, the key for achieving an enhanced understanding of the role of algorithmic technologies on modern life. Drawing on applied assemblage thinking via the concept of the urban assemblage, I demonstrate how the notion of (...) urban assemblage can work as an alternative way to explore the distributed and potential dimensions of what has been termed as Urban AI phenomena. Rather than seeing Urban AI phenomena as black-boxed, unknown and opaque, the notion of urban assemblage locates such entities within the wider contests of the city: urban places, communities and politics, where human-algorithmic relationships gather and disperse. In addition, this approach focuses on the potentialities of Urban AI phenomena—how algorithmic systems can operate differently through different aspects of the city—which can be seen to manifest new forms of resistance, collective actions and democracy. I use a case study of an algorithmic system designed to facilitate digital democracy—vTaiwan—to exemplify how assemblage methodology foregrounds the role of cities as spaces and places for exploring the democratic possibilities of algorithmic systems. This paper concludes with discussion of how the assemblage methodology contributes to serve as a bridge between critical algorithm studies and recent studies of platform urbanism. (shrink)

This article provides a comparative analysis of the regulatory landscapes governing artificial intelligence (AI) in healthcare in the European Union (EU) and South Africa (SA). It critically examines the approaches, frameworks and mechanisms each jurisdiction employs to balance innovation with ethical considerations, patient safety, data privacy and accountability. The EU’s proactive stance, embodied by the AI Act, offers a structured and risk-based categorisation for AI applications, emphasising stringent guidelines for risk management, data governance and human oversight. In contrast, SA’s regulatory (...) environment is characterised by its infancy and lack of specificity, with existing legislation such as the National Health Act and the Medicines and Related Substances Act providing a foundational but limited framework for addressing the unique challenges posed by AI in healthcare. The article delves into the dynamic nature of AI technologies, highlighting the need for continuous risk assessment, the importance of transparent and responsible data governance and the critical role of human oversight in ensuring patient safety and autonomy. It discusses the obligation of clear liability frameworks to address potential malfunctions and security breaches in AI applications. Through this comparative lens, the manuscript identifies regulatory gaps and proposes that the South African Law Reform Commission (SALRC) should play a predominant role in developing draft legislation for AI prior to the evolution of challenges related to these technologies. (shrink)

The purpose of this paper is to discuss the responsibility of AI experts for guiding the development of AI in a desirable direction. More specifically, the aim is to answer the following research question: To what extent are AI experts responsible in a forward-looking way for effects of AI technology that go beyond the immediate concerns of the programmer or designer? AI experts, in this paper conceptualised as experts regarding the technological aspects of AI, have knowledge and control of AI (...) technology that non-experts do not have. Drawing on responsibility theory, theories of the policy process, and critical algorithm studies, we discuss to what extent this capacity, and the positions that these experts have to influence the AI development, make AI experts responsible in a forward-looking sense for consequences of the use of AI technology. We conclude that, as a professional collective, AI experts, to some extent, are responsible in a forward-looking sense for consequences of use of AI technology that they could foresee, but with the risk of increased influence of AI experts at the expense of other actors. It is crucial that a diversity of actors is included in democratic processes on the future development of AI, but for this to be meaningful, AI experts need to take responsibility for how the AI technology they develop affects public deliberation. (shrink)

Current work in language models (LMs) helps us speed up or even skip thinking by accelerating and automating cognitive work. But can LMs help us with critical thinking -- thinking in deeper, more reflective ways which challenge assumptions, clarify ideas, and engineer new concepts? We treat philosophy as a case study in critical thinking, and interview 21 professional philosophers about how they engage in critical thinking and on their experiences with LMs. We find that philosophers do not (...) find LMs to be useful because they lack a sense of selfhood (memory, beliefs, consistency) and initiative (curiosity, proactivity). We propose the selfhood-initiative model for critical thinking tools to characterize this gap. Using the model, we formulate three roles LMs could play as critical thinking tools: the Interlocutor, the Monitor, and the Respondent. We hope that our work inspires LM researchers to further develop LMs as critical thinking tools and philosophers and other 'critical thinkers' to imagine intellectually substantive uses of LMs. (shrink)

This study investigates the intricate process of visualizing the concept of paradise through the lens of Artificial Intelligence (AI), employing neural networks to craft intricate visual depictions of utopian realms. The project scrutinizes the prevalent themes associated with paradisiacal imagery, dissecting the intricate weave of religious doctrines, mythologies, and the intrinsic nature of paradise – be it a tangible realm or a metaphysical state. This inquiry critically assesses the role of AI-generated art, derived from complex algebraic formulations, in mirroring conventional (...) iconography and exposing inherent biases. Such revelations underscore the cultural resonance of diverse traditions and the potential presence of subconscious prejudices. Employing AI algorithms capable of transforming textual prompts into vivid illustrations, this research unveils insights into the nexus of AI and cultural portrayals of utopia, thereby provoking profound philosophical deliberations. Central to these contemplations is the extent of human dominion over conceptualized ideals and the prospect of AI-crafted art inadvertently molding our paradisiacal perceptions, with implications ranging from reinforcement of stereotypes to shaping intrinsic cognitive schemas. (shrink)

This article critically examines the paradigm shift from the attention economy to the intimacy economy—a market system where personal and emotional data are exchanged for customized experiences that cater to individual emotional and psychological needs. It explores how AI transforms these personal and emotional inputs into services, thereby raising essential questions about the authenticity of digital interactions and the potential commodification of intimate experiences. The study delineates the roles of human–computer interaction and AI in deepening personal connections, significantly impacting emotional (...) dynamics, and underscores AI’s role in various applications, from healthcare to grief tech, highlighting both enhancements in emotional connections and potential disruptions to genuine human interactions. An AI-mediated framework (AMIE) is introduced to assess how AI reshapes these connections and the overall digital society through personalized interactions. This framework explores the interplay between human emotions and AI-generated responses within the new Avatar Sphere, emphasizing the necessity for regulatory measures to safeguard digital identities, recognize emotional data as intellectual property, and maintain system transparency. It highlights the critical need for maintaining genuine human interactions and advocates for context-aware consent, continuous monitoring, and cross-cultural considerations to foster ethical AI practices. Leveraging blockchain technology and decentralized autonomous organizations, the framework proposes methods to enhance individual control over emotional data, mitigating the commodification risks. The findings contribute to ongoing discussions on AI ethics, digital privacy, and the future of human-AI interactions, providing valuable insights for cultivating a responsible intimacy economy. (shrink)

By looking at the politics of classification within machine learning systems, this article demonstrates why the automated interpretation of images is an inherently social and political project. We begin by asking what work images do in computer vision systems, and what is meant by the claim that computers can “recognize” an image? Next, we look at the method for introducing images into computer systems and look at how taxonomies order the foundational concepts that will determine how a system interprets the (...) world. Then we turn to the question of labeling: how humans tell computers which words will relate to a given image. What is at stake in the way AI systems use these labels to classify humans, including by race, gender, emotions, ability, sexuality, and personality? Finally, we turn to the purposes that computer vision is meant to serve in our society—the judgments, choices, and consequences of providing computers with these capacities. Methodologically, we call this an archeology of datasets: studying the material layers of training images and labels, cataloguing the principles and values by which taxonomies are constructed, and analyzing how these taxonomies create the parameters of intelligibility for an AI system. By doing this, we can critically engage with the underlying politics and values of a system, and analyze which normative patterns of life are assumed, supported, and reproduced. (shrink)

AI’s new ability to create artworks is seen as a major challenge to today’s understanding of art. There is a strong tension between people who predict that AI will replace artists and critics who claim that AI art will never be art. Furthermore, recent studies have documented a negative bias towards AI art. This paper provides a philosophical explanation for this negative bias, based on our shared understanding of the ontological differences between objects. We argue that our perception of (...) art depends on our understanding of the context of its creation: human-made art is experienced as an interplay between the artist and nature. In AI-generated art, this interplay is either absent or minimised. We conclude that the displacement of the “human factor” in art will not lead to an evolution of art, but to the end of art. (shrink)

Applications of artificial intelligence/machine learning in health care are dynamic and rapidly growing. One strategy for anticipating and addressing ethical challenges related to AI/ml for health care is patient and public involvement in the design of those technologies – often referred to as ‘co-design’. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, AI/ml introduces challenges to co-design that are often underappreciated. Informed by perspectives from critical data studies and (...) critical digital health studies, we review the research literature on involvement in health care, and involvement in design, and examine the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ml for health care. We suggest that AI/ml technologies have amplified and modified existing challenges related to patient and public involvement, and created entirely new challenges. We outline three pitfalls associated with co-design for ethical AI/ml for health care and conclude with suggestions for addressing these practical and conceptual challenges. (shrink)

This article offers a critical inquiry of contemporary neural network models as an instance of machine learning, from an interdisciplinary perspective of AI studies and performativity. It shows the limits on the architecture of these network systems due to the misemployment of ‘natural’ performance, and it offers ‘context’ as a variable from a performative approach, instead of a constant. The article begins with a brief review of machine learning-based natural language processing systems and continues with a concentration on (...) the relevant model of recurrent neural networks, which is applied in most commercial research such as Facebook AI Research. It demonstrates that the logic of performativity is not brought into account in all recurrent nets, which is an integral part of human performance and languaging, and it argues that recurrent network models, in particular, fail to grasp human performativity. This logic works similarly to the theory of performativity articulated by Jacques Derrida in his critique of John L. Austin’s concept of the performative. Applying Jacques Derrida’s work on performativity, and linguistic traces as spatially organized entities that allow for this notion of performance, the article argues that recurrent nets fall into the trap of taking ‘context’ as a constant, of treating human performance as a ‘natural’ fix to be encoded, instead of performative. Lastly, the article applies its proposal more concretely to the case of Facebook AI Research’s Alice and Bob. (shrink)

The use of Artificial Intelligence (AI) in educational gamification marks a significant advancement, transforming traditional learning methods by offering interactive, adaptive, and personalized content. This approach makes historical content more relatable and promotes active learning and exploration. This research presents an innovative approach to heritage education, combining AI and gamification, explicitly targeting the Silk Roads. It represents a significant progression in a series of research, transitioning from basic 2D textual interactions to a 3D environment using photogrammetry, combining historical authenticity and (...) immersive gameplay. It features AI-driven characters developed in Unreal Engine, which provides heritage insights augmented by personalized interactions, highlighting the importance of collaborative tools like interactive quizzes for enriching education and promoting critical thinking and community among learners. In conclusion, this research underlines the transformative impact of AI and gamification in heritage education enhancement, integrating real-time voice conversation and interactive pedagogical methods into immersive 3D environments as a supplementary tool. (shrink)

Abbreviations Works by Alfred North Whitehead 1) Adventures of Ideas. New York: Macmillan Co., 1967 AI 2) Concept of Nature. Cambridge: Cambridge University Press, 1971 CN 3) Modes of Thought. New York: Macmillan Co., 1968 MT 4) Process ..

The year 2012 has witnessed worldwide celebrations of Alan Turing’s 100th birthday. A great number of conferences and workshops were organized by logicians, computer scientists and researchers in AI, showing the continued flourishing of computer science, and the fruitful interfaces between logic and computer science. Logic is no longer just the concept that Frege had about one hundred years ago, let alone that of Aristotle twenty centuries before. One of the prominent features of contemporary logic is its interdisciplinary character, connecting (...) across mathematics, philosophy, modern computer science, and even the cognitive and social sciences. -/- China is no exception. This special issue explores interfaces of logic with AI and other disciplines, and it attempts to give a bird’s eye view of the developing landscape of logic and AI in China. Our contributors come from computer science, AI, philosophy and linguistics, united by their interest in using formal logical tools and notions to deal with substantial problems in their fields. We are aware that AI is a vast area, and that the limitations of space in a volume like this may provide a somewhat incomplete or biased view. Still we hope that the six papers selected here illustrate the concerns and curiosity driving Chinese researchers, on topics shared with our colleagues around the world. -/- One of the active research areas in AI is planning under uncertainty, with incomplete knowledge, where a well-established logical framework is the action language of Son and Baral (Son and Baral 2001). This language can express the notions of sensing actions and making conditional plans. However, its current semantics is not yet satisfactory, since according to the semantics an agent would not have knowledge of what happens after a plan is executed, which can be a serious problem in a safety-critical environment. In their paper Proof Systems for Planning under Cautious Semantics (Shen and Zhao 2013), Yuping Shen and Xishun Zhao address this problem and propose a cautious and weakly cautious semantics for the action language. This new semantics enables the agent to know exactly what happens after executing an action. Hoare style proof systems are then proposed and proved to be sound and complete. What is more, the proposed new system reduces the reasoning complexity of the action language. -/- In Preferential Semantics for Plausible Subsumption in Possibility Theory (Qi and Zhang 2013), Guilin Qi and Zhizheng Zhang investigate another important issue in AI: how to handle exceptions in a knowledge-based system. This has become a hot topic in recent years, especially in ontological design, where description logics are widely used. The question then arises whether we can get a nonmonotonic extension of description logic. To answer this, the authors first propose three preferential semantics for plausible subsumption in the framework of possibility theory (Dubois and Prade 1985) and study their properties and their relationships. Then they introduce preferential subsumptions to a description logic-based knowledge system, and define an entailment relation of plausible subsumption. Moreover, they study reductions of the new semantics to standard semantics for an expressive description logic. -/- Counterfactual reasoning has been explored extensively by philosophers, cf. Lewis (1973), Stalnaker (1968). But in the last two decades, causal models have been proposed for modeling counterfactual reasoning by researchers in AI. In A Lewisian Logic of Causal Counterfactuals (Zhang 2013), Jiji Zhang studies classes of causal models and provides formal characterizations. In particular, a new logic system is proposed and proved complete for the class of ‘Lewisian models’ satisfying all the principles of David Lewis’s logic of counterfactuals. Moreover, Zhang compares his new framework with those of Lewis and Stalnaker, and also establishes formal connections with more recent approaches by Galles and Pearl, and by Halpern. -/- Consistency is a fundamental notion in logic, but it also plays a key role in many techniques for solving constraint satisfaction problems (Mackworth 1977). In Variable-Centered Consistency in Model RB (Li et al. 2013), Liang Li, Tian Liu and Ke Xu start with a discussion of i-consistency in ‘Model RB’ and ‘Model RD’, two models of random constraint satisfaction problems with growing domain size, then compare it with the notion of t-consistency and strong t-consistency in well-known earlier work by Freuder. After that, the authors define a new kind of variable-centered consistency, and show an upper bound on a suitably chosen parameter in Model RB and Model RD, such that up to this bound, all typical instances of Model RB are variable-centered consistent. -/- Language understanding is a cognitive process that human beings carry out every day. Metaphor is a pervasive phenomenon in natural languages, and its cognitive role calls for interpretation. There is a growing body of literature on cognitive mechanisms underlying metaphor. The paper An Ontology-Based Approach to Metaphor Cognitive Computation (Huang et al. 2013) by Xiaoxi Huang, Huaxin Huang, Beishui Liao, and Cihua Xu proposes a theoretical framework for metaphor understanding based on recent results from cognitive science (Shutova 2010). They then introduce ontology as a knowledge representation method, and present a new ontological model to formalize metaphor-based knowledge. An algorithmic description is provided using a quantitative measure of integrated degree, and its effectiveness is demonstrated. -/- Puzzles and their solution mechanisms are a recurrent theme in many fields. Dynamic epistemic logic (van Ditmarsch et al. 2007); (van Benthem 2011) is a recent framework that can handle information dynamics in knowledge puzzles. In Reasoning About Agent Types and the Hardest Logic Puzzle Ever (Liu and Wang 2013), Fenrong Liu and Yanjing Wang propose a new dynamic-epistemic logic that can specify different types of agents and analyse agents’ knowledge, communication and reasoning. To demonstrate its power, Smullyan’s well-known Knights and Knaves puzzles are formalized, as well as the Hardest Logic Puzzle Ever (HLPE) of Boolos (Boolos 1996). Moreover, a spectrum of new puzzles is found involving knowledge-based agent types, and their solution complexity is shown to be harder than that for existing logic puzzles. It is also shown that a version of HLPE in which the agents do not know the others’ types does not have a solution at all. -/- Finally, we would like to thank the editor of Minds and Machines, Gregory Wheeler, for his efficient assistance and kind support. We also thank Ties Nijssen at Springer for his encouragement to start this project at the first place. And of course, our appreciation goes to our authors, as well as all the colleagues who have helped us review the papers in this collection. (shrink)

Autonomy has been central to moral and political philosophy for millenia, and has been positioned as a critical aspect of both justice and wellbeing. Research in psychology supports this position, providing empirical evidence that autonomy is critical to motivation, personal growth and psychological wellness. Responsible AI will require an understanding of, and ability to effectively design for, human autonomy (rather than just machine autonomy) if it is to genuinely benefit humanity. Yet the effects on human autonomy of digital (...) experiences are neither straightforward nor consistent, and are complicated by commercial interests and tensions around compulsive overuse. This multi-layered reality requires an analysis that is itself multidimensional and that takes into account human experience at various levels of resolution. We borrow from HCI and psychological research to apply a model (“METUX”) that identifies six distinct spheres of technology experience. We demonstrate the value of the model for understanding human autonomy in a technology ethics context at multiple levels by applying it to the real-world case study of an AI-enhanced video recommender system. In the process we argue for the following three claims: 1) There are autonomy-related consequences to algorithms representing the interests of third parties, and they are not impartial and rational extensions of the self, as is often perceived; 2) Designing for autonomy is an ethical imperative critical to the future design of responsible AI; and 3) Autonomy-support must be analysed from at least six spheres of experience in order to approriately capture contradictory and downstream effects. (shrink)

In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance pricing, and many more aspects of our lives. Artificial intelligence systems can help us make evidence-driven, efficient decisions, but can also confront us with unjustified, discriminatory decisions wrongly assumed to be accurate because they are made automatically and quantitatively. It is becoming evident that these technological developments are consequential to people’s fundamental human rights. Despite increasing attention to (...) these urgent challenges in recent years, technical solutions to these complex socio-ethical problems are often developed without empirical study of societal context and the critical input of societal stakeholders who are impacted by the technology. On the other hand, calls for more ethically and socially aware AI often fail to provide answers for how to proceed beyond stressing the importance of transparency, explainability, and fairness. Bridging these socio-technical gaps and the deep divide between abstract value language and design requirements is essential to facilitate nuanced, context-dependent design choices that will support moral and social values. In this paper, we bridge this divide through the framework of Design for Values, drawing on methodologies of Value Sensitive Design and Participatory Design to present a roadmap for proactively engaging societal stakeholders to translate fundamental human rights into context-dependent design requirements through a structured, inclusive, and transparent process. (shrink)

The increasing use of artificial intelligence (AI) by public actors has led to a push for more transparency. Previous research has conceptualized AI transparency as knowledge that empowers citizens and experts to make informed choices about the use and governance of AI. Conversely, in this paper, we critically examine if transparency-as-knowledge is an appropriate concept for a public realm where private interests intersect with democratic concerns. We conduct a practice-based design research study in which we prototype and evaluate a transparent (...) smart electric vehicle charge point, and investigate experts’ and citizens’ understanding of AI transparency. We find that citizens experience transparency as burdensome; experts hope transparency ensures acceptance, while citizens are mostly indifferent to AI; and with absent means of control, citizens question transparency’s relevance. The tensions we identify suggest transparency cannot be reduced to a product feature, but should be seen as a mediator of debate between experts and citizens. (shrink)

This study presents a critical review of the emerging field of Artificial Intelligence (AI) Sociology, examining the social implications and ethical considerations of AI technologies. Through a qualitative methodology incorporating a systematic literature review and thematic analysis, this research explores the intersection of AI and sociology, aiming to bridge the gap between technological advancement and societal impact. The study investigates key theoretical frameworks, including critical theory and actor-network theory, to analyse power relations, social stratification, and the dynamic interplay (...) between AI and society. The findings reveal the multifaceted influence of AI on social structures, ethical challenges, and the need for interdisciplinary approaches to address the societal implications of AI. (shrink)

In all three versions of the “Jian’ai” 兼愛 Chapter in the Mozi 墨子, variations of a central argument may be found. This argument proceeds by advancing a diagnosis for what causes the various evils that beset the world, and it is on this basis that the Mohists propose jian’ai as the solution. The study examines this main argument in some detail, with the aim of improving both our understanding of the Mohist ethical doctrine and also our appreciation of their argumentative (...) practices. The study shows that distinct ethical injunctions of varying degrees of stringency can be derived from the argument, though they all embody an underlying notion of impartiality. This impartiality—while in many ways recognizably attractive to us—puts Mohist jian’ai in tension with certain notions regarding the ethical significance of special relations. In addition, the paper argues that the Mohists main argument for jian’ai contains a critical flaw. (shrink)

A growing number of studies on fairness in artificial intelligence (AI) use the notion of intersectionality to measure AI fairness. Most of these studies take intersectional fairness to be a matter of statistical parity among intersectional subgroups: an AI algorithm is “intersectionally fair” if the probability of the outcome is roughly the same across all subgroups defined by different combinations of the protected attributes. This paper identifies and examines three fundamental problems with this dominant interpretation of intersectional fairness (...) in AI. First, the dominant approach is so preoccupied with the intersection of attributes/categories (e.g., race, gender) that it fails to address the intersection of oppression (e.g., racism, sexism), which is more central to intersectionality as a critical framework. Second, the dominant approach faces a dilemma between infinite regress and fairness gerrymandering: it either keeps splitting groups into smaller subgroups or arbitrarily selects protected groups. Lastly, the dominant view fails to capture what it really means for AI algorithms to be fair, in terms of both distributive and non-distributive fairness. I distinguish a strong sense of AI fairness from a weak sense that is prevalent in the literature, and conclude by envisioning paths towards strong intersectional fairness in AI. (shrink)

Scholars, policymakers and organizations in the EU, especially at the level of the European Commission, have turned their attention to the ethics of (trustworthy and human-centric) Artificial Intelligence (AI). However, there has been little reflexivity on (1) the history of the ethics of AI as an institutionalized phenomenon and (2) the comparison to similar episodes of “ethification” in other fields, to highlight common (unresolved) challenges.Contrary to some mainstream narratives, which stress how the increasing attention to ethical aspects of AI is (...) due to the fast pace and increasing risks of technological developments, Science and Technology Studies(STS)-informed perspectives highlight that the rise of institutionalized assessment methods indicates a need for governments to gain more control of scientific research and to bring EU institutions closer to the public on controversies related to emerging technologies.This article analyzes how different approaches of the recent past (i.e. bioethics, technology assessment (TA) and ethical, legal and social (ELS) research, Responsible Research and Innovation (RRI)) followed one another, often “in the name of ethics”, to address previous criticisms and/or to legitimate certain scientific and technological research programs. The focus is on how a brief history of the institutionalization of these approaches can provide insights into present challenges to the ethics of AI related to methodological issues, mobilization of expertise and public participation. (shrink)

The thesis introduces and criticizes the discourse on technology, with a specific reference to the concept of AI. The discourse on AI is particularly saturated with reified metaphors which drive connotations and delimit understandings of technology in society. To better analyse the discourse on AI, the thesis proposes the concept of “Expected AI”, a composite signifier filled with historical and sociocultural connotations, and numerous referent objects. Relying on cultural semiotics, science and technology studies, and a diverse selection of heuristic (...) concepts, the thesis delves beneath the surface of AI discourse and demonstrates the hidden political, social, cultural, and ecological dangers of AI. The entanglement of the discourse(s) with (science) fiction, folklore, myth, and religion impacts how AI is perceived and received, as well as the expectations to AI-enabled technologies now and in the future. The thesis also proposes a more ethical and comprehensive ontological model for AI systems. The model describes AI systems as complex figurations, considering their socio-material organisation, global economic-material becoming, and impact on the environment, social institutions, and the semiosphere. The dissertation argues that AI should be understood not just as an object or sociotechnical system, but as its entire product chain encompassing people and cultures, as well as the used resources and impact (both material-ecological and semiotic) on a planetary scale. (shrink)

Artificial Intelligence (AI) techniques have become popular in architecture and design, and several studies have focused on using these technological advancements to solve various architectural problems. AI is used in various architectural design applications, from intelligent material composition to layout solutions, and it is also vital in supporting the architecture and design education mechanism. A comprehensive understanding of literature is necessary to use these powerful tools in education adequately. This is due to the large volume of research being created (...) and disseminated on this subject as well as the increasing application of AI techniques to address various education design-related questions. This article offers a comprehensive and critical assessment of the study of artificial intelligence applications in architecture and interior design education as a course application in the history of architecture and interior design. The study's conclusions indicate that AI's implications in architecture and design re-imagination are beneficial; however, it was concluded that AI- in its current phase- cannot replace human input and perspective. The students' feedback indicates that critical thinking skills cannot be replaced, and AI complements but doesn't replace their intellect. (shrink)

Ensuring public safety is a critical challenge for rapidly growing urban areas. Traditional policing and emergency response systems often struggle to keep pace with the complexity and scale of modern cities. Artificial Intelligence (AI) offers a transformative solution by enabling real-time crime prediction, optimizing emergency resource allocation, and enhancing situational awareness through IoT-enabled systems. This paper explores how AI-driven analytics, combined with data from surveillance cameras, social media, and environmental sensors, can improve public safety in smart cities. By addressing (...) challenges such as data privacy, algorithmic bias, and system scalability, this study demonstrates the potential of AI to create safer, more resilient urban environments. Experimental results highlight improvements in crime detection rates, emergency response times, and resource utilization, paving the way for smarter public safety systems. (shrink)

Cities today are dynamic urban ecosystems with evolving physical, socio-cultural, and technological infrastructures. Many contestations arise from the effects of inequitable access and intersecting crises currently faced by cities, which may be amplified by the algorithmic and data-centric infrastructures being introduced in urban contexts. In this article, I argue for a critical lens into how inter-related urban technologies, big data and policies, constituted as Urban AI, offer both challenges and opportunities. I examine scenarios of contestations in _urban mobility_, defined (...) broadly to include equitable access, movement, and liberty to engage with the socio-cultural, political, and urban fabric of cities. I anchor my arguments through a framework of _rights, risks,_ and _responsibilities_ for critically examining and configuring the roles, values and ethical implications for all stakeholders including human, AI and non-human entities within an urban ecosystem. As a way forward, I examine the European Commission’s proposed regulations on AI systems through an illustrative case study of an automated parking control system introduced by the City of Amsterdam. In moving beyond the city to broader urban ecosystems, I highlight the role of engaging Indigenous perspectives for designing and reconciling the implications of equitable and sustainable Urban AI ecosystems in the future. (shrink)

This study analyzes how ChatGPT portrays and describes itself, revealing misleading myths about AI technologies, specifically conversational agents based on large language models. This analysis allows for critical reflection on the potential harm these misconceptions may pose for public understanding of AI and related technologies. While previous research has explored AI discourses and representations more generally, few studies focus specifically on AI chatbots. To narrow this research gap, an experimental-qualitative investigation into auto-generated AI representations based on prompting was (...) conducted. Over the course of a month, ChatGPT (both in its GPT-4 and GPT-4o models) was prompted to “Draw an image of yourself,” “Represent yourself visually,” and “Envision yourself visually.” The resulting data (n = 50 images and 58 texts) was subjected to a critical exploratory visual semiotic analysis to identify recurring themes and tendencies in how ChatGPT is represented and characterized. Three themes emerged from the analysis: anthropomorphism, futuristic/futurism and (social)intelligence. Importantly, compared to broader AI imaginations, the findings emphasize ChatGPT as a friendly AI assistant. These results raise critical questions about trust in these systems, not only in terms of their capability to produce reliable information and handle personal data, but also in terms of human–computer relations. (shrink)

Urban resilience is critical for ensuring the sustainability and adaptability of cities in the face of growing challenges such as climate change, population growth, and infrastructure degradation. Predictive analytics, powered by Artificial Intelligence (AI) and the Internet of Things (IoT), offers a transformative approach to enhancing urban resilience. This paper explores how AI-driven predictive analytics can optimize disaster preparedness, infrastructure maintenance, and resource allocation in smart cities. By integrating real-time data from IoT sensors with advanced machine learning models, cities (...) can proactively address vulnerabilities and improve decision-making. This study highlights key applications, challenges, and future directions for leveraging predictive analytics to build resilient urban ecosystems. (shrink)

This text analyses how generative AI systems are being employed in current artistic practice to question certain historical visual narratives, creating representations that challenge some conventional perceptions of the past and thus opening up new perspectives on the experience of temporality. In this regard, special emphasis will be placed on some artistic projects based on generative historical photography practices. These are works that develop new ways around ‘archival aesthetics’ (Sekula in October 39:3–64 1986; Buchloh in Deep storage. collecting, storing and (...) archiving in art [Exhibition catalog]. P.S.1, Nueva York, 1999; Guasch in Arte y archivo, 1920-2010. Genealogías, tipologías y discontinuidades. Akal, Madrid, 2015, etc.) by producing visual archives that do not exist or are alternatives to others. We will therefore analyse works that critically examine how these generative systems can contribute to a revision and re-evaluation of the past, as well as to the problematisation of the ways in which photography has been used for the historical record. These poetics invite subtle reflections on the role of the visual archive in the processes of shaping subjectivity and personal and communal identity. In the final part of the text, we will deal with the study of some artists who, through appropriationist strategies and remakes assisted by generative AI models, revise artistic works from the past, specifically from the photoconceptualism of the 1970s. In these strategies, the thematisation of the relations between photographic register and temporality also plays a leading role. (shrink)

Artificial intelligence is among the fastest developing areas of advanced technology in medicine. The most important qualia of AI which makes it different from other advanced technology products is its ability to improve its original program and decision-making algorithms via deep learning abilities. This difference is the reason that AI technology stands out from the ethical issues of other advanced technology artifacts. The ethical issues of AI technology vary from privacy and confidentiality of personal data to ethical status and value (...) of AI entities in a wide spectrum, depending on their capability of deep learning and scope of the domains in which they operate. Developing ethical norms and guidelines for planning, development, production, and usage of AI technology has become an important issue to overcome these problems. In this respect three outstanding documents have been produced:1. The Montréal Declaration for Responsible Development of Artificial Intelligence2. Ethics Guidelines for Trustworthy AI3. Asilomar Artificial Intelligence PrinciplesIn this study, these three documents will be analyzed with respect to the ethical principles and values they involve, their perspectives for approaching ethical issues, and their prospects for ethical reasoning when one or more of these values and principles are in conflict. Then, the sufficiency of these guidelines for addressing current or prospective ethical issues emerging from the existence of AI technology in medicine will be evaluated. The discussion will be pursued in terms of the ambiguity of interlocutors and efficiency for working out ethical dilemmas occurring in practical life. (shrink)

This paper provides a critical review of economic outcome metrics used in healthcare value assessment, emphasizing the evolving landscape of resource allocation, patient-centered approaches, and standardization efforts. With healthcare costs rising globally, the efficient allocation of limited resources is essential. Metrics like Quality-Adjusted Life Years (QALYs), Disability-Adjusted Life Years (DALYs), Incremental Cost-Effectiveness Ratios (ICERs), and Cost-Benefit Analysis (CBA) are central to guiding funding decisions, influencing insurance coverage, and shaping treatment prioritization. Emerging trends, such as the integration of artificial intelligence (...) (AI) and big data, are enhancing the precision of these assessments, while patient-centered metrics underscore the importance of patient satisfaction and quality of life. Additionally, there is a growing push for the standardization of these metrics to create consistent frameworks across diverse health systems. This paper explores case studies, practical applications, and future directions to provide insights into how healthcare systems can adopt more effective, globally aligned economic assessments. (shrink)

Although artificial intelligence has been given an unprecedented amount of attention in both the public and academic domains in the last few years, its convergence with other transformative technologies like cloud computing, robotics, and augmented/virtual reality is predicted to exacerbate its impacts on society. The adoption and integration of these technologies within industry and manufacturing spaces is a fundamental part of what is called Industry 4.0, or the Fourth Industrial Revolution. The impacts of this paradigm shift on the human operators (...) who continue to work alongside and symbiotically with these technologies in the industry bring with it novel ethical issues. Therefore, how to design these technologies for human values becomes the critical area of intervention. This paper takes up the case study of robotic AI-based assistance systems to explore the potential value implications that emerge due to current design practices and use. The design methodology known as Value Sensitive Design (VSD) is proposed as a sufficient starting point for designing these technologies for human values to address these issues. (shrink)

Narratives of artificial intelligence frame public perceptions and expectations, and have a performative role, potentially leading to increased attention and resource allocation, acceptance of AI, or resistance to the technology. However, research on AI narratives frequently produces generalized and decontextualized accounts. This paper argues for closer examination of the specific processes that shape AI narratives in particular contexts. To explore this, nine AI-related exhibitions held in German museums from 2022 to 2023 were analyzed. The study draws on interviews with curatorial (...) teams and exhibition materials to investigate what narratives of AI museums are formed and how those relate to the dominant AI narratives described in previous research. It is shown that curators are critical of dominant AI narratives and aim to deconstruct common myths and present more nuanced portrayals of AI. Yet, they also face challenges in balancing this critical stance with the need for creating engaging, accessible exhibitions. The analysis reveals that while some curatorial strategies successfully counter AI stereotypes, others fail or inadvertently reproduce mainstream imaginaries. Curators discover that avoiding problematic understandings of AI in the way they had initially intended is challenging or even impossible. In other cases, when elements of mainstream AI discourse resurface in museum exhibits despite the critical stance of the curators, they remain unexamined, or are regarded as insignificant and inconsequential. (shrink)

More organizations use AI in the hiring process than ever before, yet the perceived ethicality of such processes seems to be mixed. With such variation in our views of AI in hiring, we need to understand how these perceptions impact the organizations that use it. In two studies, we investigate how ethical perceptions of using AI in hiring are related to perceptions of organizational attractiveness and innovativeness. Our findings indicate that ethical perceptions of using AI in hiring are positively (...) related to perceptions of organizational attractiveness, both directly and indirectly via perceptions of organizational innovativeness, with variations depending on the type of hiring method used. For instance, we find that individuals who consider it ethical for organizations to use AI in ways often considered to be intrusive to privacy, such as analyzing social media content for traits and characteristics, view such organizations as both more innovative and attractive. Our findings trigger a timely discussion about the critical role of ethical perceptions of AI in hiring on organizational attractiveness and innovativeness. (shrink)

This book addresses the European Court of Human Rights’ fairness standards in criminal appeal, filling a gap in this less researched area of studies. Based on a fair trial immediacy requirement, the Court has found several violations of Article 6 of the European Convention on Human Rights at the appellate level by at least eighteen States of the Council of Europe in a vast array of cases, particularly in contexts of first instance acquittals overturning and of sentences increasing on (...) appeal. -/- On the one hand, the book critically engages this case-law with the law revisions it has recently inspired in European countries, as well as with the critiques and difficulties that it continues to raise. On the other hand, it interweaves insight from criminal procedure theory with new discoveries in the field of cognitive sciences (neuroscience of memory, philosophy of knowledge, AI), shedding an interdisciplinary light on the (in)adequacy and limits of the Strasbourg Court’s jurisprudence. (shrink)

This paper is addressed to recent theoretical discussions of the Anthropocene, in particular Bernard Stiegler’s Neganthropocene (Open Universities Press, 2018), which argues: “As we drift past tipping points that put future biota at risk, while a post-truth regime institutes the denial of ‘climate change’ (as fake news), and as Silicon Valley assistants snatch decision and memory, and as gene-editing and a financially-engineered bifurcation advances over the rising hum of extinction events and the innumerable toxins and conceptual opiates that Anthropocene Talk (...) fascinated itself with—in short, as ‘the Anthropocene’ discloses itself as a dead-end trap…”. The objective of this paper is therefore twofold: (1) to discuss how the Anthropocene is appropriated to certain ideological discourses (paradoxically) to maintain the hegemony of precisely those systems of production that have most accelerated climate change etc.; (2) to consider how the factography of the Anthropocene is exploited in this process to mask the ideological character of industry-aligned “technocratic” environmental management. The paper is not concerned with specific case studies in terms of government and industry policy, or climate science, but rather with the ways in which the discourse of the Anthropocene has been inflected within the humanities and the broader cultural field—that is to say, ideologically, as a system or logic of meaning. How the Anthropocene “means” is, in this respect, a question of some importance. This paper does not attempt to address all the facets of this question, but focuses upon a central “apocalyptic” strain in the discourse of the Anthropocene drawn particularly from Francis Fukuyama’s millennial posthumanism and centred in the question of “sustainability” as catastrophe management—with the risk that real environmental degradation will become an alibi for a revived neoliberalism. In other words, that the critical Earth system transformations that characterise the Anthropocene are themselves commodities, and that the project of their amelioration is in process of defining a future (opportunistic) “crisis” rhetoric with a global political franchise. The ideological import of the Anthropocene stems precisely from the fact that it is planetary and, while catalysed by human agency, independent in its specific behaviour from it. The Anthropocene objectively presents as the contemporary counterpart of the Cold War doctrine of Mutually Assured Destruction and the most compelling argument for a new kind of technological “arms race.” But it also presents as the condition of an emerging ideological discourse which will determine how this race is run. From the discourse on “energy security” to the widespread “security crackdown” on environmental activists across the so-called developed & developing world, the Anthropocene has come to represent the co-option of a scientific factography for the thinly disguised resurgence of “ideological science” of the Fukuyamaesque variety (post-history, post-human). For Fukuyama, the true meaning of “posthuman” is thus the accomplishment of humanity’s historical mission. As the “End of History” designates an end of ideological struggle, so too the dénouement of the Anthropocene and the “ends of man” represent the accomplished purpose of species warfare: dominion, not simply over the world, but over all possible worlds. According to this narrative, science—like technology—must be uniquely at the service of the maintenance of the global order, organised around a universal appeal to “crisis management.” It is precisely for this reason that what calls itself post-human masks the return of an ever-more-apocalyptic Humanism. (shrink)

Analysing how news media portray A.I. reveals what interpretative frameworks around the technology circulate in public discourses. This allows for critical reflections on the making of meaning in prevalent narratives about A.I. and its impact. While research on the public perception of datafication and automation is growing, only a few studies investigate news framing practices. The present study connects to this nascent research area by charting A.I. news frames in four internationally renowned media outlets: The New York Times, (...) The Guardian, Wired, and Gizmodo. The main goals are to identify dominant emphasis frames in AI news reporting over the past decade, to explore whether certain A.I. frames are associated with specific data risks, and what journalists and experts contribute to the media discourse. An automated content analysis serves for inductive frame detection, identification of risk references, and network analysis of news writers. The results show how A.I.’s ubiquity emerged rapidly in the mid-2010s, and that the news discourse became more critical over time. It is further argued that A.I. news reporting is an important factor in building critical data literacy among lay audiences. (shrink)

Given the widespread integration of Social AI like ChatGPT, Gemini, Copilot, and MyAI, in personal and professional contexts, it is crucial to understand their effects on information and knowledge processing, and individual autonomy. This paper builds on Bråten’s concept of model power, applying it to Social AI to offer a new perspective on the interaction dynamics between humans and AI. By reviewing recent user studies, we examine whether and how models of the world reflected in Social AI may disproportionately (...) impact human-AI interactions, potentially leading to model monopolies where Social AI impacts human beliefs, behaviour and homogenize the worldviews of its users. The concept of model power provides a framework for critically evaluating the impact and influence that Social AI has on communication and meaning-making, thereby informing the development of future systems to support more balanced and meaningful human-AI interactions. (shrink)

This essay offers a comprehensive review of the transformative role of Artificial Intelligence (AI) in music composition and soundscape generation, providing both a historical overview and a critical analysis of its impact. Tracing AI’s evolution from its early applications in the mid-20th century to its sophisticated use in contemporary auditory arts, the paper explores how AI has reshaped creative processes, blurred traditional boundaries between music and soundscapes, and catalyzed the emergence of new genres. Additionally, it critically examines the ethical, (...) cultural, and aesthetic challenges posed by AI’s integration, addressing concerns such as creativity, authenticity, and the potential homogenization of musical outputs. By balancing both positive and critical dimensions, the essay aims to deepen understanding of AI’s dual role in transforming not only creative methodologies but also the conceptual frameworks of the auditory arts. (shrink)

Substantial research over the last ten years has indicated that many generative artificial intelligence systems (“GAI”) have the potential to produce biased results, particularly with respect to gender. This potential for bias has grown progressively more important in recent years as GAI has become increasingly integrated in multiple critical sectors, such as healthcare, consumer lending, and employment. While much of the study of gender bias in popular GAI systems is focused on text-based GAI such as OpenAI’s ChatGPT and Google’s (...) Gemini (formerly Bard), this article describes the results of a confirmatory experiment of gender bias in visual GAI systems. The authors argue that the potential for gender bias in visual GAI systems is potentially more troubling than bias in textual GAI because of the superior memorability of images and the capacity for emotional communication that images represent. They go on to offer four potential approaches to gender bias in visual GAI based on the roles visual GAI could play in modern society. The article concludes with a discussion of how dominant societal values could influence a choice between those four potential approaches to gender bias in visual GAI and some suggestions for further research. (shrink)