Marco Autili, Gianluca Filippone, Mashal Afzal Memon
et al.
Self-adaptive systems increasingly operate in close interaction with humans, often sharing the same physical or virtual environments and making decisions with ethical implications at runtime. Current approaches typically encode ethics as fixed, rule-based constraints or as a single chosen ethical theory embedded at design time. This overlooks a fundamental property of human-system interaction settings: ethical preferences vary across individuals and groups, evolve with context, and may conflict, while still needing to remain within a legally and regulatorily defined hard-ethics envelope (e.g., safety and compliance constraints). This paper advocates a shift from static ethical rules to runtime ethical reasoning for self-adaptive systems, where ethical preferences are treated as runtime requirements that must be elicited, represented, and continuously revised as stakeholders and situations change. We argue that satisfying such requirements demands explicit ethics-based negotiation to manage ethical trade-offs among multiple humans who interact with, are represented by, or are affected by a system. We identify key challenges, ethical uncertainty, conflicts among ethical values (including human, societal, and environmental drivers), and multi-dimensional/multi-party/multi-driver negotiation, and outline research directions and questions toward ethically self-adaptive systems.
Silvia Helena Galvis Navarrete, Fritz Eduardo Gempeler Rueda
El propósito de la presente publicación es dar a conocer la implementación del registro institucional del Servicio de Ética Clínica y presentar los análisis de los primeros datos obtenidos durante el periodo prepandemia, comprendido entre la creación del SEC en el año 2015 hasta el inicio de la pandemia en marzo de 2020.
Medical philosophy. Medical ethics, Business ethics
Business cycles (a periodic change of e.g. GDP over five to ten years) exist, but a proper explanation for it is still lacking. Here we extend the well-known NAIRU (non-accelerating inflation rate of unemployment) model, resulting in a set of differ-ential equations. However, the solution is marginal stable. Therefore we find a nat-ural sinusoidal oscillation of inflation and unemployment just as observed in busi-ness cycles. When speculation is present, the instability becomes more severe. So we present for the first time a mathematical explanation for business cycles. The steering of central banks by setting interest rates to keep inflation stable and low needs an overhaul. One has to distinguish between real monetary instability and the one caused naturally by business cycles.
Many organizations strive to increase the level of automation in their business processes. While automation historically was mainly concerned with automating physical labor, current automation efforts mostly focus on automation in a digital manner, thus targeting work that is related to the interaction between humans and computers. This type of automation, commonly referred to as business process automation, has many facets. Yet, academic literature mainly focuses on Robotic Process Automation, a specific automation capability. Recognizing that leading vendors offer automation capabilities going way beyond that, we use this paper to develop a detailed understanding of business process automation in industry. To this end, we conduct a structured market analysis of the 18 predominant vendors of business process automation solutions as identified by Gartner. As a result, we provide a comprehensive overview of the business process automation capabilities currently offered by industrial vendors. We show which types and facets of automation exist and which aspects represent promising directions for the future.
This inquiry explores underrepresented employees’ perceptions and receptivity toward artificial intelligence (AI) adoption, specifically focusing on how organizational leaders’ stakeholder engagement influences these dynamics. Guided by stakeholder theory, the study critically synthesizes recent literature. It evaluates existing technology adoption frameworks, including the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the Theory of Planned Behavior (TPB). Findings highlight that inclusive stakeholder engagement practices emphasizing transparency, ethical accountability, psychological safety, and culturally competent communication significantly enhance employee receptivity, particularly among marginalized groups. The study identifies substantial limitations in existing frameworks, which inadequately address intersectional diversity, transparency concerns, and ethical dimensions impacting underrepresented employees. To mitigate these gaps, this research proposes the innovative organizational role of the Chief People Readiness Officer (CPRO), strategically designed to manage AI transitions, facilitate authentic engagement, and provide transformational leadership explicitly tailored to diverse employee groups. The study concludes by emphasizing the necessity of targeted, inclusive engagement practices and recommends empirical validation of the CPRO model, longitudinal research on engagement effectiveness, and the development of intersectional receptivity metrics. This research contributes significantly to scholarly understanding and organizational practices, ultimately supporting equitable, inclusive, and effective AI adoption within contemporary organizations.
Este artículo es una reflexión sobre los dilemas éticos de la intervención y la toma de decisiones en contextos poco habituales, como es la asistencia a personas de otras culturas. Los contextos multiculturales representan un gran desafío para los profesionales sanitarios. Un ejemplo es la gestión del tiempo: al haber sido formados en una cultura monocrónica, estos profesionales a menudo encuentran dificultades para comprender y adaptarse a las perspectivas temporales de personas provenientes de culturas policrónicas. El desconocimiento de las claves culturales de las personas inmigrantes que son atendidas en las estructuras sanitarias se ha convertido en un factor de estrés para muchos profesionales y constituye un riesgo para una praxis clínica alejada de los estándares éticos. El artículo tiene por objetivo identificar las cuestiones éticas en la relación asistencial multicultural y proponer algunas estrategias que pensamos que pueden contribuir en la gestión ética de los conflictos que surgen en estos ámbitos.
Medical philosophy. Medical ethics, Business ethics
Begimai Z. Toichieva , Nadezhda K. Savelyeva , Vergine L. Kirakosyan
et al.
The article examines the transformation of marketing activities under the influence of the concept of management of Quality 5.0. We prove that Quality 5.0 is no longer just a technical category – it integrates ethical, social, and environmental dimensions, relying on the principles of sustainable development, human-centrism, digital ethics, and cyber resilience. We demonstrate that, to preserve competitiveness, modern global brands modify the traditional marketing mix (7P), adapting it to address the challenges of digital transformation and the needs of stakeholders. We consider new approaches to the development of products, which are based on eco-innovations, sustainable supply chains, transparent pricing, personalised channels of distribution, digital communications with the focus on environmental responsibility, partnership relations, and social role of the brand. The methodological foundation of the research is the combination of the theory of quality, marketing concepts of sustainable development, approaches to digital transformation of business, and the case method. We use the methods of content analysis of scholarly sources, analysis of the practices of responsible business of global companies, and methods of comparison, generalisation, deduction, and interpretation. The scientific novelty of this paper lies in the updated interpretation of the marketing mix through the lens of Quality 5.0, in which each of its elements is considered as a tool of strategic influence on the formation of the values of sustainability, ethical consumption, and digital responsibility. We distinguish the key mechanisms of implementing these principles by the example of the activities of global brands, which demonstrate the ability to combine technological innovations with ethical positioning and social impact.
Business wargaming is a central tool for developing sustaining strategies. It transfers the benefits of traditional wargaming to the business environment. However, building wargames that support the process of decision-making for strategy require respective intelligence. This paper investigates the role of intelligence in the process of developing strategic foresight. The focus is on how intelligence is developed and how it relates to business wargaming. The so-called intelligence cycle is the basis and reference of our investigation. The conceptual part of the paper combines the theoretical background from military, business as well as serious gaming. To elaborate on some of the lessons learned, we examine specific business wargames both drawn from the literature and conducted by us at the Center for Intelligence and Security Studies (CISS). It is shown that business wargaming can make a significant contribution to the transformation of data to intelligence by supporting the intelligence cycle in two crucial phases. Furthermore, it brings together business intelligence (BI) and competitive intelligence (CI) and it bridges the gap to a company's strategy by either testing or developing a new strategy. We were also able to confirm this finding based on the business wargame we conducted at a major semiconductor manufacturer.
Research and activism have increasingly denounced the problematic environmental record of the infrastructure and value chain underpinning Artificial Intelligence (AI). Water-intensive data centres, polluting mineral extraction and e-waste dumping are incontrovertibly part of AI's footprint. In this article, I turn to areas affected by AI-fuelled environmental harm and identify an ethics of resistance emerging from local activists, which I term 'elemental ethics'. Elemental ethics interrogates the AI value chain's problematic relationship with the elements that make up the world, critiques the undermining of local and ancestral approaches to nature and reveals the vital and quotidian harms engendered by so-called intelligent systems. While this ethics is emerging from grassroots and Indigenous groups, it echoes recent calls from environmental philosophy to reconnect with the environment via the elements. In empirical terms, this article looks at groups in Chile resisting a Google data centre project in Santiago and lithium extraction (used for rechargeable batteries) in Lickan Antay Indigenous territory, Atacama Desert. As I show, elemental ethics can complement top-down, utilitarian and quantitative approaches to AI ethics and sustainable AI as well as interrogate whose lived experience and well-being counts in debates on AI extinction.
Olumide Adisa, Enio Alterman Blay, Yasaman Asgari
et al.
Complexity science, despite its broad scope and potential impact, has not kept pace with fields like artificial intelligence, biotechnology and social sciences in addressing ethical concerns. The field lacks a comprehensive ethical framework, leaving us, as a community, vulnerable to ethical challenges and dilemmas. Other areas have gone through similar experiences and created, with discussions and working groups, their guides, policies and recommendations. Therefore, here we highlight the critical absence of formal guidelines, dedicated ethical committees, and widespread discussions on ethics within the complexity science community. Drawing on insights from the disciplines mentioned earlier, we propose a roadmap to enhance ethical awareness and action. Our recommendations include (i) initiating supportive mechanisms to develop ethical guidelines specific to complex systems research, (ii) creating open-access resources, and (iii) fostering inclusive dialogues to ensure that complexity science can responsibly tackle societal challenges and achieve a more inclusive environment. By initiating this dialogue, we aim to encourage a necessary shift in how ethics is integrated into complexity research, positioning the field to address contemporary challenges more effectively.
In analyzing the destruction of democracy, political culture, morals and political ethics through the determinants of Vote Buying in general elections in Indonesia, this article uses the literature study method. The method used is through data collection by finding sources and constructing from various sources such as books, journals, and existing research. The determinant of Vote Buying which destroys democracy, political culture, morals and political ethics. The intended determinants such as poverty, education, politico-business, patron-client relations should be sought for the root of the problem and its solution. Through analysis, Rational Choice Theory will dissect and examine the destruction of democracy, political culture, morals and political ethics through the determinants of Vote Buying in general elections in Indonesia. In conclusion, this article contains: (1). Nominal rules have not had a deterrent effect. (2). Low political awareness of people who are exposed to vote buying. (3). Educationally and economically marginalized people are politically neglected. (4). There is no anti-bribery formulation in the pilot scheme and sustainable maintenance practices (5). The bias of political party sovereignty as the main instrument in preventing politico-business intervention. (6). Unequal distribution of poverty and education. (7). There is a predatory network that is interrelated in maintaining the high political costs in Indonesia.
Christos Arvanitidis, Boris Barov, Alberto Basset
et al.
A network of European organisations is coordinating a workshop in New York (USA) on September 26, 2024, as part of the Science Summit 2024 at the 79th Session of the UN General Assembly (UNGA79). This network represents active communities from the fields of biodiversity, ecology, and engineering. It aims to strengthen science, technology, and innovation efforts to achieve the UN Sustainable Development Goals (SDGs).These communities, through European initiatives like the European Research Infrastructures, the European Open Science Cloud (EOSC), and Digital Twin projects, have selected the Kunming-Montreal Global Biodiversity Framework (K-M GBF) as a testbed for contributing to the SDGs. Their collective focus is on the network shared impact rather than individual projects. By examining a common approach to the K-M GBF, they aim to enhance their contributions to the framework's strategic goals, particularly its 2030 and 2050 targets.In this direction, the network: Recognises the contribution and rights of indigenous peoples and local communities as custodians of biodiversity and holders of traditional knowledge for the conservation, restoration, and sustainable use of ecosystems. By adhering to the Open Science principles of “Findable Accessible Interoperable Reusable” (FAIR) and “Collective Benefit, Authority to Control, Responsibility, Ethics” (CARE), and by being consistent with the practices adopted by the scientific community, the members of the network promote traceability of their work and of the materials they use, including those provided by indigenous peoples.Implements a variety of approaches to improve biodiversity monitoring, management, and protection. It promotes multi- and cross-disciplinary, integrative approaches to enhance its contribution to many of the Framework objectives. Its members support research on biodiversity at all levels of the biological organisation, from single-celled organisms, through collections and specimen data and up to the scale of ecosystems, as well as on how biodiversity responds to climate change. A key role in this process is already being played by the biodiversity Research Infrastructures, both in the EU and globally, through bi- and multi-directional linking and an increased interoperability of their data holdings, the provision of advanced access to semantically structured FAIR data, the provision of single points of access to federated data discovery from different data domains, thus supporting multi-disciplinary research addressing questions of high complexity and importance to society.All organisations in the network are committed to the three principal objectives of the Convention on the Biological Diversity, namely conservation, sustainable use, and fair sharing of benefits derived from the utilisation of natural resources. They contribute significantly to the three above principal objectives of the CBD, by: (a) making biodiversity information readily available and developing systems to support decision making and conservation efforts that directly contribute to our ability to live sustainably with nature, as concerns the first of the principal objectives above; (b) identifying priorities and targets and raising awareness of the need to streamline efforts among scientific and societal actors, are critical elements towards the second objective; (c) developing technologies to enable the sharing of data, services and other products related to genetic resources, which are used in combination with any other type of resource or product (e.g. taxonomic, literature, environmental, etc.), are included among the activities to achieve the third principal objective. Contributes to the achievement of the K-M GBF objectives through science, technology and innovation, based on scientific evidence, traditional knowledge, and innovative practices. This support is translated into activities such as: (a) providing solutions for research, data sharing and management, and scientific computing solutions to researchers, learners, policy makers, public administrations and businesses; (b) developing standard operating procedures, implementing standards, and promoting open science principles to enhance research integrity, accuracy and accountability in science; (c) providing federated research services, resources, and other research products to promote multidisciplinary knowledge and innovation; (d) creating models (e.g. of climate and human activity related land-use changes in biodiversity dynamics and ecosystem services), automated data flows (from sensors to data systems) and integration (e.g. biodiversity data flows combined with environmental and human activity variables; (e) building digital twins for informed decision making, such as the European Digital Twin of the Ocean (European DTO), with assured connectivity to newly collected high quality environmental and biodiversity data; (f) providing training and capacity building services for innovative tools.Supports the consideration of the ecosystem approach principle in the implementation of the K-M GBF, with a number of activities being developed by the network: (a) providing virtual representations of the ocean and land, integrating observations, modelling, and digital infrastructures, and creating digital twins that allow the scientific community to simulate and study “what if” scenarios; (b) developing and implementing technologies that enable a cross-domain, multidisciplinary approach to the study of biodiversity and ecosystems; (c) promoting ecosystem-based approaches to biodiversity management and habitat conservation in innovative publications venues (e.g. Nature Conservation, Biodiversity Data Journal, One Ecosystem, etc.).Promotes collaboration and synergies between the Convention on Biological Diversity and its Protocols, as well as with other biodiversity-related conventions, relevant multilateral agreements and international organisations and processes, as this will facilitate the implementation of the K-M GBF. The network is developing a variety of work, including: (a) collaborating with bodies and organisations responsible for the implementation of the CBD and its Protocols (e.g. IUCN, IPBES, European Commission) to co-design and co-develop research resources and products to support their mandates; (b) establishing strong links with policy actors such as the European Commission and the European Parliament, the JRC and others. Participate in social, scientific and technical initiatives in the European arena, such as the European Green Deal, the EU Knowledge Centre for Biodiversity and its Science Service for Biodiversity, the Biodiversity Knowledge Hub, the EU Pollinators Initiative and the EOSC. Developing links with the private sector through the Science/Business initiative, cooperation with the European Environmental Bureau (EEB), and the EOSC Digital Innovation Hub (EOSC DIH); (c) integrating and sharing of computational resources and expertise will not only advance the frontiers of scientific knowledge, but also ensure that data-driven research initiatives around the world are well supported.Contributes to the understanding and researching of the links between biodiversity and health. Particular emphasis will be placed on the following activities: (a) participating in initiatives and projects such as the EOSC Health Cluster, a platform for interdisciplinary research, EC projects such as B4Life, B-Cubed and BioAgora by publishing research that investigates how biodiversity affects human health; (b) using data from multiple sources to numerically demonstrate the links between human and environmental health, in the context of the One Health concept; (c) using digital twins to create Virtual Research Environments (VREs) that generate knowledge on how biodiversity patterns derived from taxa and habitats interact with patterns derived from data and information on their health; (d) publishing the results of the research, such as studies on zoonotic diseases, biodiversity and mental health, and the benefits of ecosystem services for public health. During the workshop, the participants will present their collective contribution to the implementation of the K-M GBF and invite international and regional stakeholders to present their expectations on the above topic. Based on stakeholder input, the network will publish a white paper outlining its approach.Finally, these communities will issue an open call to forge an international alliance to further integrate biodiversity conservation into the priorities of the UN Summit of the Future agenda priorities and the post-SDG agenda.
Case studies are typically used to teach 'ethics', but when the content of a course is focused on formulae and proofs, a case analysis and the knowledge, skills, and abilities they require can be distracting. Moreover, case analyses are typically focused narrowly on research issues: obtaining consent, dealing with research team members, and/or research policy violations. Not all students in quantitative courses plan to become researchers, and ethical practice of mathematics, statistics, data science, and computing is an essential topic regardless of the learner's career plans. While it is incorrect to treat 'social justice' as a proxy for 'ethical practice', the topic of 'social justice' may be more interesting to both students and instructors. This paper offers concrete recommendations for integrating social justice content into quantitative courses in ways that limit the burden of new knowledge, skills, and abilities but also support reproducible and actionable assessments. Five tools can be utilized to integrate social justice into a course in a way that also meets calls to integrate 'ethics'; minimizes the burden on instructors to create and grade new materials and assignments; minimizes the burden on learners to develop the skill set to complete a case analysis; and maximizes the likelihood that the ethics content will be embedded in the learners' cognitive representation of the knowledge being taught in the quantitative course. These tools are: a. Curriculum Development Guidelines b. 7-task Statistics and Data Science Pipeline c. ASA Ethical Guidelines for Statistical Practice d. Stakeholder Analysis e. 6-step Ethical Reasoning paradigm This paper discusses how to use these tools in quantitative courses. The tools and frameworks offer structure, and facilitate ensuring that changes made to any course are evaluable and generate actionable assessments for learners.
There is a growing movement in undergraduate computer science (CS) programs to embed ethics across CS classes rather than relying solely on standalone ethics courses. One strategy is creating assignments that encourage students to reflect on ethical issues inherent to the code they write. Building off prior work that has surveyed students after doing such assignments in class, we conducted focus groups with students who reviewed a new introductory ethics-based CS assignment. In this experience report, we present a case study describing our process of designing an ethics-based assignment and proposing the assignment to students for feedback. Participants in our focus groups not only shared feedback on the assignment, but also on the integration of ethics into coding assignments in general, revealing the benefits and challenges of this work from a student perspective. We also generated novel ethics-oriented assignment concepts alongside students. Deriving from tech controversies that participants felt most affected by, we created a bank of ideas as a starting point for further curriculum development.
Generative models (foundation models) such as LLMs (large language models) are having a large impact on multiple fields. In this work, we propose the use of such models for business decision making. In particular, we combine unstructured textual data sources (e.g., news data) with multiple foundation models (namely, GPT4, transformer-based Named Entity Recognition (NER) models and Entailment-based Zero-shot Classifiers (ZSC)) to derive IT (information technology) artifacts in the form of a (sequence of) signed business networks. We posit that such artifacts can inform business stakeholders about the state of the market and their own positioning as well as provide quantitative insights into improving their future outlook.
The technical progression of artificial intelligence (AI) research has been built on breakthroughs in fields such as computer science, statistics, and mathematics. However, in the past decade AI researchers have increasingly looked to the social sciences, turning to human interactions to solve the challenges of model development. Paying crowdsourcing workers to generate or curate data, or data enrichment, has become indispensable for many areas of AI research, from natural language processing to reinforcement learning from human feedback (RLHF). Other fields that routinely interact with crowdsourcing workers, such as Psychology, have developed common governance requirements and norms to ensure research is undertaken ethically. This study explores how, and to what extent, comparable research ethics requirements and norms have developed for AI research and data enrichment. We focus on the approach taken by two leading conferences: ICLR and NeurIPS, and journal publisher Springer. In a longitudinal study of accepted papers, and via a comparison with Psychology and CHI papers, this work finds that leading AI venues have begun to establish protocols for human data collection, but these are are inconsistently followed by authors. Whilst Psychology papers engaging with crowdsourcing workers frequently disclose ethics reviews, payment data, demographic data and other information, similar disclosures are far less common in leading AI venues despite similar guidance. The work concludes with hypotheses to explain these gaps in research ethics practices and considerations for its implications.
Eudora Welty, an American fiction writer, brings forth women’s issues and promotes feminist ethics in her writings: novels and short stories. Her stories reveal her concern with the extended subordination of women under machismo in Southern America. More significantly, her work highlights the growth of women’s liberal thinking during the development of modernity in the southern parts of America. She looks at the change in time and thought under modernity to examine the local culture and literature with a critical eye on the strict gender order in the South. Her fiction explores varied forms of oppression in marriage, kinship, and community structure of the changing South through female Gothicism. In depicting her female characters as fleeing spatial confinement for freedom and self-transformation, Welty develops an aesthetic of mobility that threatens the mythologized constructions of Southern culture. This eventually leads to a reactionary modernism that calls for the redefinition of identity and culture in the history of Southern America. For centuries, the South has been considered the most segregated, white-centric patriarchal society due to its particular culture, geography and history. The change in thought and culture caused by modernity becomes a threat to the customary plantation business as well as to the conservative male hierarchical order as it engenders a revision of women’s identity. This study may help in further research on Gothic literary studies in combination with discourses on culture and women’s identity in literary works.
Keywords: Female Gothic, mythologized culture, modernity, Southern America, women’s identity
Benchmarks are seen as the cornerstone for measuring technical progress in Artificial Intelligence (AI) research and have been developed for a variety of tasks ranging from question answering to facial recognition. An increasingly prominent research area in AI is ethics, which currently has no set of benchmarks nor commonly accepted way for measuring the 'ethicality' of an AI system. In this paper, drawing upon research in moral philosophy and metaethics, we argue that it is impossible to develop such a benchmark. As such, alternative mechanisms are necessary for evaluating whether an AI system is 'ethical'. This is especially pressing in light of the prevalence of applied, industrial AI research. We argue that it makes more sense to talk about 'values' (and 'value alignment') rather than 'ethics' when considering the possible actions of present and future AI systems. We further highlight that, because values are unambiguously relative, focusing on values forces us to consider explicitly what the values are and whose values they are. Shifting the emphasis from ethics to values therefore gives rise to several new ways of understanding how researchers might advance research programmes for robustly safe or beneficial AI. We conclude by highlighting a number of possible ways forward for the field as a whole, and we advocate for different approaches towards more value-aligned AI research.
Internet of Things is the name of a communication network that is formed by physical objects such as RFID tags, sensors and some lightweight development platforms that have the ability to connect to the internet. While the devices can communicate among themselves in this network, they can also be part of a large network. The data produced by those physical objects which are the member of IoT network are processed by different methods and the outputs obtained are used in processes such as decision making and learning. With this aspect of the Internet of Things, it affects all areas of human life and its number is increasing day by day. These devices appear to have security gaps due to their limited resources, their wide range of usage area and incomplete security standards. These devices, which are located in people's living areas, manufacturing and business processes also cause difficulties in protecting privacy. In this study, a solution has been developed for the communication security of the internet of things called ESP-Eye which includes a camera, wireless communication module and face recognition software. The proposed solution was implemented on the ESP-Eye.