AI-developers face a challenge when seeking to use models that aim to be culturally sensitive. While we agree that culture is an emergent reality, there is always the risk of creating algorithms that treat culture as objective to account for various facets of the social realm. As a result, culture becomes prepackaged and autonomous. Nonetheless, culture is not only emergent but dialogically and socially invented. In this article, the point is to advance the discussion about culture by addressing a crucial (...) philosophical issue and proposing some practical themes on how to avoid culturalism in AI development. (shrink)

The human-centred debate in Britain focuses on the idea of human-machine symbiosis, and the “Dialogue” debate in Scandinavia focuses on the deep understanding of human communication, through a process of inner reflection. Both of these debates provide a framework for the participatory design of AI systems.The emergence of “social Europe” creates the desirability for a sharing of social and cultural knowledge and resources among the citizens of Europe. This raises the possibility of exploiting the potential of new technology for (...) the distribution and transfer of knowledge and skill among the citizens of Europe whilst retaining the diversity of their cultures and languages. These issues of transfer have been the focus of many AI researchers who have been concerned with the design of AI systems for the education, training and welfare of disadvantaged citizens. It is suggested that central to such a transfer is the design of participatory learning systems which focus on the mediation and distribution of knowledge in diverse socio-cultural contexts.In this paper, the SEAKE Centre's projects, especially “Brighton Parosi”, and “Adult Literacy” are discussed to provide an insight into the concepts and practice of designing such participatory systems. The philosophy of these projects was rooted in the sharing of social and cultural experiences, through participatory learning. The development of the projects involved a process of exchange of language and culture in both formal and informal learning environments. For the Parosi Project social interaction was the central core for the exchange of cultural experiences and the language acquisition process. The Adult Literacy project built on the exchange process, and used the idea of the mediation of knowledge for the design of a knowledge based system. The design process developed by the above two projects could be described as a participatory design approach which builds upon and extends the human-machine symbiosis and dialogue approaches. (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)

In this paper, we empirically and conceptually examine how distributed human–machine networks of labour comprise a form of underlying intelligence within Artificial Intelligence (AI), considering the implications of this for Responsible Artificial Intelligence (R-AI) innovation. R-AI aims to guide AI research, development and deployment in line with certain normative principles, for example fairness, privacy, and explainability; notions implicitly shaped by comparisons of AI with individualised notions of human intelligence. However, as critical scholarship on AI demonstrates, this is a limited (...) framing of the nature of intelligence, both of humans and AI. Furthermore, it dismisses the skills and labour central to developing AI systems, involving a distributed network of human-directed practices and reasoning. We argue that inequities in the agency and recognition of different types of practitioners across these networks of AI development have implications beyond RAI, with narrow framings concealing considerations which are important within broader discussions of AI intelligence. Drawing from interactive workshops conducted with AI practitioners, we explore practices of data acquisition, cleaning, and annotation, as the point where practitioners interface with domain experts and data annotators. Despite forming a crucial part of AI design and development, this type of data work is frequently framed as a tedious, unskilled, and low-value process. In exploring these practices, we examine the political role of the epistemic framings that underpin AI development and how these framings can shape understandings of distributed intelligence, labour practices, and annotators’ agency within data structures. Finally, we reflect on the implications of our findings for developing more participatory and equitable approaches to machine learning applications in the service of R-AI. (shrink)

Current national and international guidelines for the ethical design and development of artificial intelligence (AI) and robotics emphasize ethical theory. Various governing and advisory bodies have generated sets of broad ethical principles, which institutional decisionmakers are encouraged to apply to particular practical decisions. Although much of this literature examines the ethics of designing and developing AI and robotics, medical institutions typically must make purchase and deployment decisions about technologies that have already been designed and developed. The primary problem facing (...) medical institutions is not one of ethical design but of ethical deployment. The purpose of this paper is to develop a practical model by which medical institutions may make ethical deployment decisions about ready-made advanced technologies. Our slogan is “more process, less principles.” Ethically sound decisionmaking requires that the process by which medical institutions make such decisions include participatory, deliberative, and conservative elements. We argue that our model preserves the strengths of existing frameworks, avoids their shortcomings, and delivers its own moral, practical, and epistemic advantages. (shrink)

In the scenario of growing polarization of promises and dangers that surround artificial intelligence (AI), how to introduce responsible AI and robotics in healthcare? In this paper, we develop an ethical–political approach to introduce democratic mechanisms to technological development, what we call “Caring in the In-Between”. Focusing on the multiple possibilities for action that emerge in the realm of uncertainty, we propose an ethical and responsible framework focused on care actions in between fears and hopes. Using the theoretical perspective (...) of Science and Technology Studies and empirical research, “Caring in the In-Between” is based on three movements: the first is a change of focus from the world of promises and dangers to the world of uncertainties; the second is a conceptual shift from assuming a relationship with robotics based on a Human–Robot Interaction to another focused on the network in which the robot is embedded (the “Robot Embedded in a Network”); and the last is an ethical shift from a general normative framework to a discussion on the context of use. Based on these suggestions, “Caring in the In-Between” implies institutional challenges, as well as new practices in healthcare systems. It is articulated around three simultaneous processes, each of them related to practical actions in the “in-between” dimensions considered: monitoring relations and caring processes, through public engagement and institutional changes; including concerns and priorities of stakeholders, with the organization of participatory processes and alternative forms of representation; and making fears and hopes commensurable, through the choice of progressive and reversible actions. (shrink)

While debate is heating up regarding the development of AI and its perceived impacts on human society, policymaking is struggling to catch up with the demand to exercise some regulatory control over its rapid advancement. This paper aims to introduce the concept of entangled AI that emerged from participatory backcasting research with an AI expert panel. The concept of entanglement has been adapted from quantum physics to effectively capture the envisioned form of artificial intelligence in which a strong (...) interconnectedness between AI, humans, society, and nature is reflected. Entanglement assumes that AI should serve nature, social well-being, justice, and the resilience of this intertwined network simultaneously and promote a dynamic balance among these factors. This approach allows us to understand the pervasive role of this technology and the scope of human agency in its development. The study shows how such concepts seem to transcend the dominant discourses related to expectations, technological determinism, and humanism. An additional aim of this paper is to demonstrate how backcasting can contribute to generating useful understandings of the future of AI and fruitful insights for policymaking. (shrink)

Putting laypeople in an active role as direct expert contributors in the design of service robots becomes more and more prominent in the research fields of human–robot interaction and social robotics. Currently, though, HRI is caught in a dilemma of how to create meaningful service robots for human social environments, combining expectations shaped by popular media with technology readiness. We recapitulate traditional stakeholder involvement, including two cases in which new intelligent robots were conceptualized and realized for close interaction with humans. (...) Thereby, we show how the robot narrative together with aspects of power balancing stakeholders, such as hardware constraints and missing perspectives beyond primary users, and the adaptivity of robots through machine learning that creates unpredictability, pose specific challenges for participatory design processes in HRI. We conclude with thoughts on a way forward for the HRI community in developing a culture of participation that considers humans when conceptualizing, building, and using robots. (shrink)

Critics are calling for the decolonization of AI (artificial intelligence). The problem is that this technology is marginalizing other modes of knowledge with dehumanizing applications. What is needed to remedy this situation is the development of human-centric AI. However, there is a serious blind spot in this strategy that is addressed in this paper. The corrective that is usually proposed—participatory design—lacks the philosophical rigor to undercut the autonomy of AI, and thus the colonization spawned by this technology. A (...) more radical or substantial proposal is advanced in this discussion that is known as community-based design. This alternative makes a theoretical maneuver that allows AI design to be directed by human agency, thereby introducing a safeguard that may help to prevent colonization by this technology. (shrink)

As artificial intelligence (AI) becomes progressively more engaged with society, its shift from technical tool to participating in society raises questions about AI personhood. Drawing upon developmental psychology and systems theory, a mediating structure for AI proto-personhood is defined analogous to an early stage of human development. The proposed AI bridges technical, psychological, and theological perspectives on near-future AI and is structured by its hardware, software, computational, and sociotechnical systems through which it experiences its world as embodied (even for (...) putatively disembodied AI). Further social and moral construction can occur building upon a simple “self” for AI synthesized from symbolic and statistical approaches to AI. (shrink)

With focus on the development and use of artificial intelligence (AI) systems in the digital health context, we consider the following questions: How does the European Union (EU) seek to facilitate the development and uptake of trustworthy AI systems through the AI Act? What does trustworthiness and trust mean in the AI Act, and how are they linked to some of the ongoing discussions of these terms in bioethics, law, and philosophy? What are the normative components of trustworthiness? (...) And how do the requirements of the AI Act relate to these components? We first explain how the EU seeks to create an epistemic environment of trust through the AI Act to facilitate the development and uptake of trustworthy AI systems. The legislation establishes a governance regime that operates as a socio-epistemological infrastructure of trust which enables a performative framing of trust and trustworthiness. The degree of success that performative acts of trust and trustworthiness have achieved in realising the legislative goals may then be assessed in terms of statutorily defined proxies of trustworthiness. We show that to be trustworthy, these performative acts should be consistent with the ethical principles endorsed by the legislation; these principles are also manifested in at least four key features of the governance regime. However, specified proxies of trustworthiness are not expected to be adequate for applications of AI systems within a regulatory sandbox or in real-world testing. We explain why different proxies of trustworthiness for these applications may be regarded as ‘special’ trust domains and why the nature of trust should be understood as participatory. (shrink)

Technological development and increased international competition have imposed a significant burden on the product development function of many companies. The growing complexity of products demands a larger product development team with people having various competencies. Simultaneously the importance of good quality, usability and customisation of products is growing, and many companies want to involve customers and users directly in the development work. Both the complexity and quality demand new ways of working that support collaboration between people (...) with various competencies, interests and responsibilities both inside and outside the company. This paper reports experiences from using action research to introduce new user-centred work practices in two commercial product development projects. The interventions varied. In the first project it was found rewarding to engage customers and users in workshops based on participatory inquiry and collaborative design. The design process was iterative and the workshops took place several times involving concept through detailed design. In the second project, new design representations are introduced. The experiences highlight the importance of creating and reifying insights in design representations and using these to both support collaboration, and create continuity in the project. The paper ends with a discussion of scientific rigor in action research and what the new work practices imply for the development team. (shrink)

Across the globe, our work and social lives are increasingly integrated with Information and Communication Technologies, yet massive disparities in the values, uses and benefits of ICT exist. New methods are needed to shed light on unique and integrative concepts of ICT across cultures. This paper explores the use of visual methods to facilitate critical engagement with ICT—defined as situational awareness, reflexive ICT practice and power and control over ICT. This definition of critical ICT engagement is informed by a cultural (...) identity lens, and intends to improve participatory methods in ICT for Development and community technology design and application. Our notion of critical ICT engagement is developed through an analysis of three case studies, each employing visual methods to shed light on concepts and practices of ICT cross-culturally. This paper makes three contributions to the ICT4D literature. First, it establishes a cultural identity lens to chart out cultural differences between researchers and participants, and to develop situational awareness of ICT in context. Second, it defines the conceptual domain of reflexive ICT practice and establishes the key role of researchers in facilitating it. Third, it argues for the need to support participants to develop capacity to engage critically with ICT as a means to influence social and organizational structures. This paper offers a way for researchers and practitioners to engage with cultural issues in community-based research and design using visual methodologies. (shrink)

In this article I discuss some potential problems inherent in dialogue based methods when it comes to contributing to enduring participatory change. By dialogue-based methods I refer mainly to the dialogue conference and the development organisation, as described by Gustavsen (1992) and Pålshaugen (1998), (2001) and (2002). In a broader sense I refer to the linguistically oriented framework of these methods. The empirical context for the paper is a planned enterprise development project. This will be run as (...) a network project among four to seven small and medium sized companies and at a general level it aims to increase the capacity for continuous learning and change in the enterprises. Here the involvement and mobilisation of all employees is important, and dialogue-based methods will be used. Based on prior work with these enterprises, I see some potential obstacles up front concerning the ability of dialogue-based methods to contribute to enduring participatory change. In the article these concerns are discussed through different theoretical perspectives and illustrated with examples from the field. (shrink)

Community informatics and Information and Communications Technology for Development research projects frequently focus on the appropriation of ICTs and the design of information systems to meet the needs of communities. Such projects typically involve a range of participants reflecting different cultures and depend for their success on the ability of the project to bridge differences. Using PROTIC, a 5-year collaborative project between Monash University, Oxfam Australia and Oxfam in Bangladesh as a case study, this paper reflects on the use (...) of a “mainstream” form of participatory action research as a tool capable of engaging in more sustainable projects by helping to identify and to take into account localised or context-specific social and cultural issues in the design of the information system itself, consequently improving the effectiveness and sustainability of the systems developed. The idea of emic understandings of culture have also been used to interpret the project and PAR as an intercultural exchange around developing a community-focussed sociotechnical project. (shrink)

This article offers several contributions to the interdisciplinary project of responsible research and innovation in data science and AI. First, it provides a critical analysis of current efforts to establish practical mechanisms for algorithmic auditing and assessment to identify limitations and gaps with these approaches. Second, it provides a brief introduction to the methodology of argument-based assurance and explores how it is currently being applied in the development of safety cases for autonomous and intelligent systems. Third, it generalises this (...) method to incorporate wider ethical, social, and legal considerations, in turn establishing a novel version of argument-based assurance that we call ‘ethical assurance.’ Ethical assurance is presented as a structured method for unifying the myriad practical mechanisms that have been proposed. It is built on a process-based form of project governance that enlists reflective innovation practices to operationalise normative principles, such as sustainability, accountability, transparency, fairness, and explainability. As a set of interlocutory governance mechanisms that span across the data science and AI lifecycle, ethical assurance supports inclusive and participatory ethical deliberation while also remaining grounded in social and technical realities. Finally, this article sets an agenda for ethical assurance, by detailing current challenges, open questions, and next steps, which serve as a springboard to build an active (and interdisciplinary) research programme as well as contribute to ongoing discussions in policy and governance. (shrink)

This paper aims to provide a basis for renewed talk about ‘use’ in computing. Four current ‘discourse arenas’ are described. Different intentions manifest in each arena are linked to failures in ‘translation’, different terminologies crossing disciplinary and national boundaries non-reflexively. Analysis of transnational use discourse dynamics shows much miscommunication. Conflicts like that between the ‘Scandinavian System Development School’ and the ‘usability approach’ have less current salience. Renewing our talk about use is essential to a participatory politics of information (...) technology and will lead to clearer perception of the implications of letting new systems becoming primary media of social interaction. (shrink)

Background There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race). Objectives Our objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias. Methodology The study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers. Results Findings reveal considerable (...) divergent views on three key issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias. Conclusion/significance Based on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection. (shrink)

Introduction: The coronavirus disease 2019 pandemic has placed intensive care units (ICU) triage at the center of bioethical discussions. National and international triage guidelines emerged from professional and governmental bodies and have led to controversial discussions about which criteria—e.g. medical prognosis, age, life-expectancy or quality of life—are ethically acceptable. The paper presents the main points of agreement and disagreement in triage protocols and reviews the ethical debate surrounding them. Sources of data: Published articles, news articles, book chapters, ICU triage guidelines (...) set out by professional societies and health authorities. Areas of agreement: Points of agreement in the guidelines that are widely supported by ethical arguments are (i) to avoid using a first come, first served policy or quality-adjusted life-years and (ii) to rely on medical prognosis, maximizing lives saved, justice as fairness and non-discrimination. Areas of controversy: Points of disagreement in existing guidelines and the ethics literature more broadly regard the use of exclusion criteria, the role of life expectancy, the prioritization of healthcare workers and the reassessment of triage decisions. Growing points: Improve outcome predictions, possibly aided by Artificial intelligence (AI); develop participatory approaches to drafting, assessing and revising triaging protocols; learn from experiences with implementation of guidelines with a view to continuously improve decision-making. Areas timely for developing research: Examine the universality vs. context-dependence of triaging principles and criteria; empirically test the appropriateness of triaging guidelines, including impact on vulnerable groups and risk of discrimination; study the potential and challenges of AI for outcome and preference prediction and decision-support. (shrink)

This paper presents a novel methodology for integrating indigenous knowledge systems into AI development to counter cognitive imperialism and foster inclusivity. By critiquing the dominance of Western epistemologies and highlighting the risks of bias, the authors argue for incorporating diverse epistemologies. The proposed framework outlines a participatory approach that includes indigenous perspectives, ensuring AI benefits all. The methodology draws from AI ethics, indigenous studies, and postcolonial theory, emphasizing co-creation with indigenous communities, ethical protocols for indigenous data governance, and (...) adaptation of AI algorithms. Case studies in natural language processing, content moderation, and healthcare demonstrate the methodology’s effectiveness and importance. By offering a concrete methodology for decolonizing AI, this paper contributes significantly to AI ethics and social justice, providing a roadmap for equitable, culturally respectful AI. (shrink)

Identity building in organisations is often viewed as legitimacy of value systems of the organisation. Based on empirical studies the task of this article is to argue that such a legitimacy approach risks failing in the longer perspective, if the proactive capability development is neglected. The participatory scenario method presented in this article is one of the possible methods to enhance identity building based on proactive capability development.

The book examines the extent to which Chinese cyber and network security laws and policies act as a constraint on the emergence of Chinese entrepreneurialism and innovation. Specifically, how the contradictions and tensions between data localisation laws affect innovation in artificial intelligence. The book surveys the globalised R&D networks, and how the increasing use of open-source platforms by leading Chinese AI firms during 2017–2020, exacerbated the apparent contradiction between Network Sovereignty and Chinese innovation. The drafting of the Cyber Security Law (...) did not anticipate the changing nature of globalised AI innovation. It is argued that the deliberate deployment of what the book refers to as 'fuzzy logic' in drafting the Cyber Security Law allowed regulators to subsequently interpret key terms regarding data in that Law in a fluid and flexible fashion to benefit Chinese innovation. (shrink)

In this paper, we will report annotation experiments which show the advantage of applying a formal ontological methodology for constructing a schema for semantic annotation to mark up terms in the...

Dependency stands for manygrievances and is generally considered asymptom of oppression. An opposing concept,offered as the preferred state, isself-reliance. Dependency and self-reliance arekey concepts in sustainable developmentprograms that feature participatory approaches.Some of the ways in which development projectsemploy the concepts of dependency andself-reliance, however, are troubling.Dependency and self-reliance in two programsfor participatory sustainable development areexamined, one in Canada and the other in NewZealand. Frameworks for dependency and self-reliance aredrawn from social psychology and philosophy toexamine problematic aspects (...) associated with theconcepts. Analysis produced a proposal foruse of the term situatedinterdependence as a way to cast the outcomesof participatory sustainable development moreprecisely. The location of the cases (Canadaand New Zealand) centers the discussion withina context of industrialized agriculture, butalso points to issues pertinent to developingcountries. (shrink)

We suggest that as people move to construe robots as social agents, interact with them, and treat them as capable of social ties, they might develop (close) relationships with them. We then ask what kind of relationships can people form with bots, what functions can bots fulfill, and what are the societal and moral implications of such relationships.

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)

There is a need recognized by the National Institute of Dental & Craniofacial Research and the National Cancer Institute to advance basic, translational and clinical saliva research. The goal of the Salivaomics Knowledge Base (SKB) is to create a data management system and web resource constructed to support human salivaomics research. To maximize the utility of the SKB for retrieval, integration and analysis of data, we have developed the Saliva Ontology and SDxMart. This article reviews the informatics advances in saliva (...) diagnostics made possible by the Saliva Ontology and SDxMart. (shrink)

As an instrument for participatory technology development, Scenario-Based Design offers significant potential for an early inclusion of future users. Over the course of a 3-year research project, this method was examined as a procedure for participatory technology development. Methods and instruments aimed at achieving a potential user’s participation, and the resulting cooperation of heterogeneous social groups can be seen as translation tools. Their purpose is to act as translators between different social fields and the specific knowledge (...) associated with them. These translation capabilities and participatory methods should result in the best possible convergence of different orientations and purposes. In this paper, attempting to achieve the best possible convergence is described as a dilemma of alignment. Several approaches will be used to describe the dynamic of the alignment dilemma within the above-mentioned project. The reconstruction follows one question that is proposed as a heuristic pattern to meet the requirements of an accurate analysis of holistic participatory methods: Who or what has to adjust to whom or what, why, when, and in which way? The main conclusions include the finding that the alignment dilemma is not equally balanced, that the agency of epistemic objects within the process has to be captured, and that it is easy for translation—provided primarily by core instruments of the participatory method used—to begin to overwrite the needs and purposes of one social group with the interests and orientations of another. (shrink)

Modelling that exploits visual elements and information visualisation are important areas that have contributed immensely to understanding and the computerisation advancements in many domains and yet remain unexplored for the benefit of the law and legal practice. This paper investigates the challenge of modelling and expressing structures and processes in legislation and the law by using visual modelling and information visualisation (InfoVis) to assist accessibility of legal knowledge, practice and knowledge formalisation as a basis for legal AI. The paper uses (...) a subset of the well-defined Unified Modelling Language (UML) to visually express the structure and process of the legislation and the law to create visual flow diagrams called lawmaps, which form the basis of further formalisation. A lawmap development methodology is presented and evaluated by creating a set of lawmaps for the practice of conveyancing and the Landlords and Tenants Act 1954 of the United Kingdom. This paper is the first of a new breed of preliminary solutions capable of application across all aspects, from legislation to practice; and capable of accelerating development of legal AI. (shrink)

While the social benefits of AI often outweigh its trade-offs, what about its environmental impact? To what extent can AI counterbalance the ecological burdens it creates? Can the Earth sustain itself until AI is successfully developed in the era of climate change and environmental degradation? -/- As Nguyen suggests, humanity must seek wisdom by confronting the foolishness that they are doing in environmental matters. Such wisdom urges us to reevaluate our thoughts, choices, and behaviors to minimize environmental harm and promote (...) ecological sustainability. A critical first step in using AI responsibly for the environment lies in ensuring its effective and efficient utilization. (shrink)

Creativity has a special role in enabling humans to develop beyond the fulfilment of simple primary functions. This factor is significant for Artificial Intelligence (AI) developers who take replication to be the primary goal, since moves toward creating autonomous artificial-beings beg questions about their potential for creativity. Using Wittgenstein’s remarks on rule-following and language-games, I argue that although some AI programs appear creative, to call these programmed acts creative in our terms is to misunderstand the use of this word in (...) language. I conclude that replication is not the best way forward for AI development in matters of creativity. (shrink)

The purpose of this paper is to increase the understanding of how different types of experts with influence over the development of AI, in this role, reflect upon distribution of forward-looking responsibility for AI development with regard to safety and democracy. Forward-looking responsibility refers to the obligation to see to it that a particular state of affairs materialise. In the context of AI, actors somehow involved in AI development have the potential to guide AI development in (...) a safe and democratic direction. This study is based on qualitative interviews with such actors in different roles at research institutions, private companies, think tanks, consultancy agencies, parliaments, and non-governmental organisations. While the reflections about distribution of responsibility differ among the respondents, one observation is that influence is seen as an important basis for distribution of responsibility. Another observation is that several respondents think of responsibility in terms of what it would entail in concrete measures. By showing how actors involved in AI development reflect on distribution of responsibility, this study contributes to a dialogue between the field of AI governance and the field of AI ethics. (shrink)

Knowledge can be expressed in language using a plethora of grammatical means. Four major groups of meanings related to knowledge are Evidentiality: grammatical expression of information source; Egophoricity: grammatical expression of access to knowledge; Mirativity: grammatical expression of expectation of knowledge; and Epistemic modality: grammatical expression of attitude to knowledge. The four groups of categories interact. Some develop overtones of the others. Evidentials stand apart from other means in many ways, including their correlations with speech genres and social environment. This (...) essay presents a framework which connects the expression of knowledge across the world's languages in a coherent way, showing their dependencies and complexities, and pathways of historical development in various scenarios, including language obsolescence. (shrink)

The epistemological foundation of unity of knowledge is used to formulate a system-model of participatory socioeconomic development. The micro-properties of such a participatory development approach are deeply ethical in nature. In order to bring out the endogenous role of ethics derived from the moral law in reference to the epistemic foundation, and thereby explain their impact on the socioeconomic development experience, the methods of topological space and topological mappings are found to be appropriate for formalizing (...) the complex nature of participatory dynamics. They emerge in the midst of institutional and organic interaction, integration, and evolution. The application of topological methods to participatory socioeconomic development thus opens up a field that is rarely used by mathematical economists. In this sense this article is an original contribution to the area of ethical development theory and its topological explanation and application. (shrink)

AI technology is capturing the African imaginations as a gateway to progress and prosperity. There is a growing interest in AI by different actors across the continent including scientists, researchers, humanitarian and aid organizations, academic institutions, tech start-ups, and media organizations. Several African states are looking to adopt AI technology to capture economic growth and development opportunities. On the other hand, African researchers highlight the gap in regulatory frameworks and policies that govern the development of AI in the (...) continent. They argue that this could lead to AI technology exacerbating problems of inequalities and injustice in the continent. However, most of the literature on AI ethics is biased toward Euro-American perspectives and lack the understanding of how AI development is apprehended in the Global South, and particularly Africa. Drawing on the case study of the first African Master’s in Machine Intelligence program, this paper argues for looking beyond the question of ethics in AI and examining AI governance issues through the analytical lens of the raciality of computing and the political economy of technoscience to understand AI development in Africa. By doing so, this paper seeks a different theorization for AI ethics from the South that is based on lived experiences of those in the margins and avoids the framings of technological futures that simplistically pathologize or celebrate Africa. (shrink)

Background While the theoretical benefits and harms of Artificial Intelligence (AI) have been widely discussed in academic literature, empirical evidence remains elusive regarding the practical ethical challenges of developing AI for healthcare. Bridging the gap between theory and practice is an essential step in understanding how to ethically align AI for healthcare. Therefore, this research examines the concerns and challenges perceived by experts in developing ethical AI that addresses the healthcare context and needs. Methods We conducted semi-structured interviews with 41 (...) AI experts and analyzed the data using reflective thematic analysis. Results We developed three themes that expressed the considerations perceived by experts as essential for ensuring AI aligns with ethical practices within healthcare. The first theme explores the ethical significance of introducing AI with a clear and purposeful objective. The second theme focuses on how experts are concerned about the tension that exists between economic incentives and the importance of prioritizing the interests of doctors and patients. The third theme illustrates the need to develop context-sensitive AI for healthcare that is informed by its underlying theoretical foundations. Conclusions The three themes collectively emphasized that beyond being innovative, AI must genuinely benefit healthcare and its stakeholders, meaning AI also aligns with intricate and context-specific healthcare practices. Our findings signal that instead of narrow product-specific AI guidance, ethical AI development may need a systemic, proactive perspective that includes the ethical considerations (objectives, actors, and context) and focuses on healthcare applications. Ethically developing AI involves a complex interplay between AI, ethics, healthcare, and multiple stakeholders. (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)

The Salivaomics Knowledge Base (SKB) is designed to serve as a computational infrastructure that can permit global exploration and utilization of data and information relevant to salivaomics. SKB is created by aligning (1) the saliva biomarker discovery and validation resources at UCLA with (2) the ontology resources developed by the OBO (Open Biomedical Ontologies) Foundry, including a new Saliva Ontology (SALO). We define the Saliva Ontology (SALO; http://www.skb.ucla.edu/SALO/) as a consensus-based controlled vocabulary of terms and relations dedicated to the salivaomics (...) domain and to saliva-related diagnostics following the principles of the OBO (Open Biomedical Ontologies) Foundry. The Saliva Ontology is an ongoing exploratory initiative. The ontology will be used to facilitate salivaomics data retrieval and integration across multiple fields of research together with data analysis and data mining. The ontology will be tested through its ability to serve the annotation ('tagging') of a representative corpus of salivaomics research literature that is to be incorporated into the SKB. Background Saliva (oral fluid) is an emerging biofluid for non-invasive diagnostics used in the detection of human diseases. The need to advance saliva research is strongly emphasized by the National Institute of Dental and Craniofacial Research (NIDCR), and is included in the NIDCR's 2004- 2009 expert panel long-term research agenda [1]. The ability to monitor health status, disease onset, progression, recurrence and treatment outcome through noninvasive means is highly important to advancing health care management. Saliva is a perfect medium to be explored for personalized individual medicine including diagnostics, offering a non-invasive, easy to obtain means for detecting and monitoring diseases. Saliva testing potentially allows the patient to collect their own saliva samples at home, yielding convenience for the patient and savings in health costs, and facilitating multiple sampling. Specimen collection is less objectionable to patients and easier in children and elderly individuals. Due to these advantages. (shrink)

This paper explores the potential of integrating ancient educational principles from diverse eastern cultures into modern AI ethics curricula. It draws on the rich educational traditions of ancient China, India, Arabia, Persia, Japan, Tibet, Mongolia, and Korea, highlighting their emphasis on philosophy, ethics, holistic development, and critical thinking. By examining these historical educational systems, the paper establishes a correlation with modern AI ethics principles, advocating for the inclusion of these ancient teachings in current AI development and education. The (...) proposed integration aims to provide a comprehensive education that not only encompasses foundational knowledge but also advanced learning, thereby equipping future AI professionals with the necessary tools to develop AI systems that are ethically responsible, culturally aware, and aligned with human values such as fairness, safety, transparency, and collaboration. This approach not only addresses the AI alignment problem but also fosters cultural harmony and global understanding, which are crucial in an increasingly interconnected world. The paper posits that the wisdom of ancient educational systems, when harmonized with modern AI ethics, can guide the development of AI technologies that are beneficial for humanity, ensuring these advancements are not just technologically sound but also ethically and culturally informed. (shrink)

Drawing upon the General Learning Model, the present study developed a moderated mediation model to provide an in-depth understanding of whether and how adolescents’ reading prosocial content in books predicts their prosocial behavior. The target population in this study is Chinese adolescents, and we adopted a paper-based survey to collect data. The age range of the sample was from 12 to 19. Among all participants, 49.3% were female, and 50.7% were male. PROCESS SPSS Macro was used to analyze the proposed (...) moderated mediation model. The results showed that prosocial content reading was positively associated with adolescents’ prosocial behavior. The positive association included a direct relationship and an indirect relationship through the mediation of moral identity. Furthermore, this study revealed the moderation effect of age on the relationships among prosocial content reading, moral identity, and prosocial behavior. Specifically, as age increases, the effects of prosocial content reading on moral identity and prosocial behavior attenuate, and the mediation effect of moral identity also decreases. The study adds to the body of knowledge on the prosocial media effect by extending it to book reading. (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)

Investigating the causal relationship between exposure and time-to-event outcome is an important topic in biomedical research. Previous literature has discussed the potential issues of using hazard ratio (HR) as the marginal causal effect measure due to noncollapsibility. In this article, we advocate using restricted mean survival time (RMST) difference as a marginal causal effect measure, which is collapsible and has a simple interpretation as the difference of area under survival curves over a certain time horizon. To address both measured and (...) unmeasured confounding, a matched design with sensitivity analysis is proposed. Matching is used to pair similar treated and untreated subjects together, which is generally more robust than outcome modeling due to potential misspecifications. Our propensity score matched RMST difference estimator is shown to be asymptotically unbiased, and the corresponding variance estimator is calculated by accounting for the correlation due to matching. Simulation studies also demonstrate that our method has adequate empirical performance and outperforms several competing methods used in practice. To assess the impact of unmeasured confounding, we develop a sensitivity analysis strategy by adapting the E-value approach to matched data. We apply the proposed method to the Atherosclerosis Risk in Communities Study (ARIC) to examine the causal effect of smoking on stroke-free survival. (shrink)

Background Machine learning (ML) is utilized increasingly in health care, and can pose harms to patients, clinicians, health systems, and the public. In response, regulators have proposed an approach that would shift more responsibility to ML developers for mitigating potential harms. To be effective, this approach requires ML developers to recognize, accept, and act on responsibility for mitigating harms. However, little is known regarding the perspectives of developers themselves regarding their obligations to mitigate harms.Methods We conducted 40 semi-structured interviews with (...) developers of ML predictive analytics applications for health care in the United States.Results Participants varied widely in their perspectives on personal responsibility and included examples of both moral engagement and disengagement, albeit in a variety of forms. While most (70%) of participants made a statement indicative of moral engagement, most of these statements reflected an awareness of moral issues, while only a subset of these included additional elements of engagement such as recognizing responsibility, alignment with personal values, addressing conflicts of interests, and opportunities for action. Further, we identified eight distinct categories of moral disengagement reflecting efforts to minimize potential harms or deflect personal responsibility for preventing or mitigating harms.Conclusions These findings suggest possible facilitators and barriers to the development of ethical ML that could act by encouraging moral engagement or discouraging moral disengagement. Regulatory approaches that depend on the ability of ML developers to recognize, accept, and act on responsibility for mitigating harms might have limited success without education and guidance for ML developers about the extent of their responsibilities and how to implement them. (shrink)

This paper explores the development of an ethical guardrail framework for AI systems, emphasizing the importance of customizable guardrails that align with diverse user values and underlying ethics. We address the challenges of AI ethics by proposing a structure that integrates rules, policies, and AI assistants to ensure responsible AI behavior, while comparing the proposed framework to the existing state-of-the-art guardrails. By focusing on practical mechanisms for implementing ethical standards, we aim to enhance transparency, user autonomy, and continuous improvement (...) in AI systems. Our approach accommodates ethical pluralism, offering a flexible and adaptable solution for the evolving landscape of AI governance. The paper concludes with strategies for resolving conflicts between ethical directives, underscoring the present and future need for robust, nuanced and context-aware AI systems. (shrink)

Galleries, libraries, archives and museums are striving to retain audience attention to issues related to cultural heritage, by implementing various novel opportunities for audience engagement through technological means online. Although born-digital assets for cultural heritage may have inundated the Internet in some areas, most of the time they are stored in “digital warehouses,” and the questions of the digital ecosystem’s sustainability, meaningful public participation and creative reuse of data still remain. Emerging technologies, such as artificial intelligence, are used to bring (...) born-digital archives to light, aiming to enhance the public’s engagement and participation. At the core of this debate lies both the openness of data and issues of privacy. How open to the public should born-digital archives be? Should everything be open and available online, and what does it take to achieve balance between openness and privacy, especially through AI initiatives? The study is qualitative and builds on the rationale of grounded theory. The role of AI development is critically investigated in relation to opening up born-digital archives online, by considering privacy and ethics issues. Grounded in the context of the author’s PhD research, the paper proposes a human-centred approach to AI development for democratising its development towards fairness and social inclusion, contrary to the stereotypical cliché of blackboxing, allowing space for the plurality of born-digital archives to flourish. (shrink)

BackgroundExisting clinical ethics support (CES) instruments are considered useful. However, users report obstacles in using them in daily practice. Including end users and other stakeholders in developing CES instruments might help to overcome these limitations. This study describes the development process of a new ethics support instrument called CURA, a low-threshold four-step instrument focused on nurses and nurse assistants working in palliative care. MethodWe used a participatory development design. We worked together with stakeholders in a Community of (...) Practice throughout the study. Potential end users (nurses and nurse assistants in palliative care) used CURA in several pilots and provided us with feedback which we used to improve CURA.ResultsWe distinguished three phases in the development process. Phase one, Identifying Needs, focused on identifying stakeholder and end user needs and preferences, learning from existing CES instruments, their development and evaluation, and identify gaps. Phase two, Development, focused on designing, developing, refining and tailoring the instrument on the basis of iterative co-creation. Phase three, Dissemination, focused on implementation and dissemination. The instrument, CURA, is a four-step low-threshold instrument that fosters ethical reflection.ConclusionsParticipatory development is a valuable approach for developing clinical ethics support instruments. Collaborating with end users and other stakeholders in our development study has helped to meet the needs and preferences of end users, to come up with strategies to refine the instrument in order to enhance its feasibility, and to overcome reported limitations of existing clinical ethics instruments. (shrink)

With the emergence of Artificial Intelligence (AI) in the Anthropocene, we are faced with “humanizing AI before it dehumanizes us.” Before the advent of the “posthuman,” will our technologies help develop a better world, or enable us to more efficiently destroy it? This essay is an appeal to Black philosophers to contribute to the critique and value theory of AI. OpenAI’s GPT-4 has opened new ethical questions. This examination of AI’s history, and the possibility of “thinking machines,” concludes that emerging (...) technologies have disproportionately adverse effects on Black and brown people. To counter this, as a sentient tool, AI ought not be an instrument enabling excess capital accumulation, increased cognitive class division, surveillance for the authoritarian state, and pernicious anti-Black racism. Because of this, a new value theory for this technology should be based on participatory socialist principles of access to resources, environmentalism, and redistribution of the global commons. Informed by broader perspectives, as a more useful tool in bridging power differentials, AI should be the people’s tool. (shrink)