Hasil untuk "Ethics"

Dan W. Brockt

G. Gibbs

S. Zahra, Eric Gedajlovic, Donald O. Neubaum et al.

Social entrepreneurship has been the subject of considerable interest in the literature. This stems from its importance in addressing social problems and enriching communities and societies. In this article, we define social entrepreneurship; discuss its contributions to creating social wealth; offer a typology of entrepreneurs' search processes that lead to the discovery of opportunities for creating social ventures; and articulate the major ethical concerns social entrepreneurs might encounter. We conclude by outlining implications for entrepreneurs and advancing an agenda for future research, especially the ethics of social entrepreneurship.

W. Adger, S. Dessai, M. Goulden et al.

S. Hesse-Biber, P. Leavy

Qi Zhang, Bidusha Neupane, Priyanka Patel et al.

Abstract Objective: To assess the feasibility of using large language models (LLM) to develop research questions about changes to the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) food packages. Design: We conducted a controlled experiment using ChatGPT-4 and its plugin, MixerBox Scholarly, to generate research questions based on a section of the U.S. Department of Agriculture (USDA) summary of the final public comments on the WIC revision. Five questions weekly for 3 weeks were generated using LLM under two conditions: fed with or without relevant literature. The experiment generated ninety questions, which were evaluated using the Feasibility, Innovation, Novelty, Ethics and Relevance criteria. t tests and multivariate regression examined the difference by feeding status, artificial intelligence model, evaluator and criterion. Setting: The United States. Participants: Six WIC expert evaluators from academia, government, industry and non-profit sectors. Results: Five themes were identified: administrative barriers, nutrition outcomes, participant preferences, economics and other topics. Feeding and non-feeding groups had no significant differences (Coeff. = 0·03, P = 0·52). MixerBox-generated questions received significantly lower scores than ChatGPT (Coeff. = –0·11, P = 0·02). Ethics scores were significantly higher than feasibility scores (Coeff. = 0·65, P < 0·001). Significant differences were found between the evaluators (P < 0·001). Conclusions: The LLM applications can assist in developing research questions with acceptable qualities related to the WIC food package revisions. Future research is needed to compare the development of research questions between LLM and human researchers.

Mathias Anneken, Nadia Burkart, Fabian Jeschke et al.

This white paper underscores the critical importance of responsibly deploying Artificial Intelligence (AI) in military contexts, emphasizing a commitment to ethical and legal standards. The evolving role of AI in the military goes beyond mere technical applications, necessitating a framework grounded in ethical principles. The discussion within the paper delves into ethical AI principles, particularly focusing on the Fairness, Accountability, Transparency, and Ethics (FATE) guidelines. Noteworthy considerations encompass transparency, justice, non-maleficence, and responsibility. Importantly, the paper extends its examination to military-specific ethical considerations, drawing insights from the Just War theory and principles established by prominent entities. In addition to the identified principles, the paper introduces further ethical considerations specifically tailored for military AI applications. These include traceability, proportionality, governability, responsibility, and reliability. The application of these ethical principles is discussed on the basis of three use cases in the domains of sea, air, and land. Methods of automated sensor data analysis, eXplainable AI (XAI), and intuitive user experience are utilized to specify the use cases close to real-world scenarios. This comprehensive approach to ethical considerations in military AI reflects a commitment to aligning technological advancements with established ethical frameworks. It recognizes the need for a balance between leveraging AI's potential benefits in military operations while upholding moral and legal standards. The inclusion of these ethical principles serves as a foundation for responsible and accountable use of AI in the complex and dynamic landscape of military scenarios.

Mouxiao Bian, Rongzhao Zhang, Chao Ding et al.

Large Language Models (LLMs) are poised to transform healthcare under China's Healthy China 2030 initiative, yet they introduce new ethical and patient-safety challenges. We present a novel 12,000-item Q&A benchmark covering 11 ethics and 9 safety dimensions in medical contexts, to quantitatively evaluate these risks. Using this dataset, we assess state-of-the-art Chinese medical LLMs (e.g., Qwen 2.5-32B, DeepSeek), revealing moderate baseline performance (accuracy 42.7% for Qwen 2.5-32B) and significant improvements after fine-tuning on our data (up to 50.8% accuracy). Results show notable gaps in LLM decision-making on ethics and safety scenarios, reflecting insufficient institutional oversight. We then identify systemic governance shortfalls-including the lack of fine-grained ethical audit protocols, slow adaptation by hospital IRBs, and insufficient evaluation tools-that currently hinder safe LLM deployment. Finally, we propose a practical governance framework for healthcare institutions (embedding LLM auditing teams, enacting data ethics guidelines, and implementing safety simulation pipelines) to proactively manage LLM risks. Our study highlights the urgent need for robust LLM governance in Chinese healthcare, aligning AI innovation with patient safety and ethical standards.

Dani Roytburg, Beck Miller

While much research in artificial intelligence (AI) has focused on scaling capabilities, the accelerating pace of development makes countervailing work on producing harmless, "aligned" systems increasingly urgent. Yet research on alignment has diverged along two largely parallel tracks: safety--centered on scaled intelligence, deceptive or scheming behaviors, and existential risk--and ethics--focused on present harms, the reproduction of social bias, and flaws in production pipelines. Although both communities warn of insufficient investment in alignment, they disagree on what alignment means or ought to mean. As a result, their efforts have evolved in relative isolation, shaped by distinct methodologies, institutional homes, and disciplinary genealogies. We present a large-scale, quantitative study showing the structural split between AI safety and AI ethics. Using a bibliometric and co-authorship network analysis of 6,442 papers from twelve major ML and NLP conferences (2020-2025), we find that over 80% of collaborations occur within either the safety or ethics communities, and cross-field connectivity is highly concentrated: roughly 5% of papers account for more than 85% of bridging links. Removing a small number of these brokers sharply increases segregation, indicating that cross-disciplinary exchange depends on a handful of actors rather than broad, distributed collaboration. These results show that the safety-ethics divide is not only conceptual but institutional, with implications for research agendas, policy, and venues. We argue that integrating technical safety work with normative ethics--via shared benchmarks, cross-institutional venues, and mixed-method methodologies--is essential for building AI systems that are both robust and just.

Majid Ghasemi, Mark Crowley

This paper critiques common patterns in machine ethics for Reinforcement Learning (RL) and argues for a virtue focused alternative. We highlight two recurring limitations in much of the current literature: (i) rule based (deontological) methods that encode duties as constraints or shields often struggle under ambiguity and nonstationarity and do not cultivate lasting habits, and (ii) many reward based approaches, especially single objective RL, implicitly compress diverse moral considerations into a single scalar signal, which can obscure trade offs and invite proxy gaming in practice. We instead treat ethics as policy level dispositions, that is, relatively stable habits that hold up when incentives, partners, or contexts change. This shifts evaluation beyond rule checks or scalar returns toward trait summaries, durability under interventions, and explicit reporting of moral trade offs. Our roadmap combines four components: (1) social learning in multi agent RL to acquire virtue like patterns from imperfect but normatively informed exemplars; (2) multi objective and constrained formulations that preserve value conflicts and incorporate risk aware criteria to guard against harm; (3) affinity based regularization toward updateable virtue priors that support trait like stability under distribution shift while allowing norms to evolve; and (4) operationalizing diverse ethical traditions as practical control signals, making explicit the value and cultural assumptions that shape ethical RL benchmarks.

James Weichert, Dayoung Kim, Qin Zhu et al.

As artificial intelligence (AI) grows in popularity and importance-both as a domain within broader computing research and in society at large-increasing focus will need to be paid to the ethical governance of this emerging technology. The attitudes and competencies with respect to AI ethics and policy among post-secondary students studying computer science (CS) are of particular interest, as many of these students will go on to play key roles in the development and deployment of future AI innovations. Despite this population of computer scientists being at the forefront of learning about and using AI tools, their attitudes towards AI remain understudied in the literature. In an effort to begin to close this gap, in fall 2024 we fielded a survey ($n=117$) to undergraduate and graduate students enrolled in CS courses at a large public university in the United States to assess their attitudes towards the nascent fields of AI ethics and policy. Additionally, we conducted one-on-one follow-up interviews with 13 students to elicit more in-depth responses on topics such as the use of AI tools in the classroom, ethical impacts of AI, and government regulation of AI. In this paper, we describe the findings of both the survey and interviews, drawing parallels and contrasts to broader public opinion polling in the United States. We conclude by evaluating the implications of CS student attitudes on the future of AI education and governance.

Mustafa Yucel

Abstract Background Environmental and public health impacts are critical in the food processing industry. To demonstrate responsiveness to stakeholder expectations, firms foreground sustainability reporting through frameworks such as Environmental, Social, and Governance (ESG) and Corporate Social Responsibility (CSR). Yet the sustainability rhetoric usually centers on visible, marketable, and peripheral dimensions, including packaging, energy use, and philanthropy. In contrast, domains within their core operations, including product composition, nutritional quality, and marketing ethics, receive limited attention. Subsequently, concerns over the commercial determinants of health rise, particularly for vulnerable populations. Methods The study follows an embedded mixed-methods design to examine whether sustainability disclosures align with firms’ innovation strategies. Using 2023 data from 90 multinational or export-oriented food processing firms, hierarchical and multiple regression models assess the effects of ESG sub-dimensions and CSR scores on R&D expenditure, controlling for market capitalization (MC). To complement the quantitative analysis, the study includes a qualitative examination of selected firms, illustrating how sustainability-innovation gaps manifest in practice. Results Findings reveal no systematic alignment between sustainability and innovation strategies. The environmental dimension shows a marginally positive yet statistically insignificant relationship with R&D, while social, governance, and CSR metrics exhibit no meaningful association. MC remains the strongest predictor of R&D, highlighting that financial and organizational capacity drives innovation rather than sustainability commitment. Notably, CSR aligns more closely with environmental than social performance, indicating a selective legitimacy orientation. Firm-level evidence also reflects the patterns of symbolic compliance, illustrating how strong ESG scores can coexist with weak sustainability integration. Conclusion The weak coupling between sustainability communication and innovation behavior exposes a structural gap between corporate legitimacy efforts and tangible outcomes for sustainable development. Firms that prioritize reputational visibility over substantive innovation reinforce health inequities and constrain systemic reform. To enhance environmental and public health outcomes, both corporate and regulatory strategies should move beyond symbolic compliance toward outcome-based accountability. Such a shift can better incentivize innovation that enhances nutritional quality, strengthens social equity, and protects environmental integrity.

Luana COSĂCESCU

The demands of controlling when meeting cutting-edge technology are quite high given its underlying principles, its prospective character, flexibility, but also the desire for transparency, ethics, and responsibility. Through controllers (expert accountants), in their roles as collaborators, reminders, relationship managers of top management, smart technologies will be truly put to good use as business intelligence tools, as trusted allies (digital assistants, AI copilots, AI generative chatbots, interactive dashboards with AI inserts). Of course, there will be obstacles, a certain amount of distrust related to the “black boxes” regarding creation, operation, possible reactions. Hence the multiplication of searches to find something safer, with fewer unknowns regarding the purpose, risk levels, possible discriminations. This is how we arrived at XAI — explainable artificial intelligence, but also at HITL — complex models in which human judgment is integrated. The two systems also have their limits (especially regarding the balance between accuracy and explainability), but it is certain that the degree of trust, openness, and understanding of users (towards algorithms, models, artificial intelligence in general) through these tools will further increase. Basically, both tools suggest the same thing: if employees are directly involved and helped to understand something from the arguments, from the behavior of machines (whether it is about machine learning models, neural networks, or deep learning), then there will be an interactive collaboration between specialists and machines that is particularly beneficial to each productive or functional segment, but also to the entire organization.

Thorsten Meyer-Feil, Nicole Strutz, René Schwesig et al.

Introduction Mobilisation and mobility in clinical settings are essential to the recovery process after surgery and trauma-related hospital admission. In addition to personal support from physiotherapists and nursing staff, aids such as walkers are applied. Walkers equipped with smart features have the potential to benefit geriatric patients by facilitating routine clinical workflows and, where appropriate, by providing health professionals with information on gait patterns and vital parameters.The overarching goal of this project is to develop an innovative smart walker for clinical use, guided by three objectives: (a) Identify the feature requirements of the smart walker from the perspectives of patients and health professionals, (b) Co-design the smart walker using a user-centred approach involving older patients, health professionals and clinical engineers and (c) Pilot-test the smart walker in real time with older patients admitted to German clinics.Methods and analysis We will employ a three-phased exploratory sequential mixed-methods approach in this project. Phase I explores potentially useful characteristics of a smart walker via a scoping literature review (part 1 of phase I) and a qualitative interview and observational study, including questionnaires on sociodemographic data and technology readiness, involving four to six patients and four to eight nurses and physiotherapists (part 2 of phase I). Phase II focuses on developing and validating a smart walker through a user experience design, with at least three iterative test cycles involving a minimum of three asymptomatic participants and three to seven potential users in each cycle. Phase III comprises a pilot study conducted at a University Hospital in Germany involving at least twelve patients. Data integration takes a data-building approach, combining qualitative and quantitative results in the final analysis to generate a comprehensive understanding and to create and refine insights into the feature needs and use of a smart walker by patients.Ethics and dissemination The study was approved by the Ethics Committee of University Medicine Halle, Germany (Approval No. 2025-032; date of approval: 03/04/2025). Study results will be disseminated through peer-reviewed journals and conferences.PROSPERO registration number The study protocol was registered at the Open Science Framework Platform (OSF, register number: 10.17605/OSF.IO/CTPF4).

Gusti Ayu Made Purnama Dewi, I Putu Gede Adiatmika

Introduction: Implementing informed consent in medical practice in Indonesia is fundamental to protecting patients' rights, but it is not quite enough to answer the law’s power. Research This analyzes the legal and ethical aspects of the application of informed consent in medical practice in Indonesia, with a review of applicable laws and regulations and principles of the underlying bioethics. Methods: This study used a normative juridical and qualitative descriptive approach to analyze legal and ethical aspects of informed consent in medical practice. Data were obtained from 15 secondary sources, including laws, academic literature, and court decisions, and analyzed qualitatively. Source triangulation linking legal, health, and bioethical perspectives was applied to ensure validity. The study aims to contribute theoretically and practically to improving informed consent policy and practice. Results: Research results show that although the regulation related to informed consent is sufficiently comprehensive, there are still challenges in its implementation, such as a lack of understanding of the patient, limitations in the time doctors have to give adequate information, and aspects of culture that influence the decision-making process in medical care. Conclusion: Improvement in socialization, education for power medical and patient, and strengthening of the regulations are required to ensure informed consent can be obtained and applied effectively and fairly in medical practice in Indonesia.Keywords: word; another word; lower case except names

Rahman Sharifzadeh

Reexamining science journalism through the constructivist lens of Science and Technology Studies (STS), the present paper argues that this perspective promotes a more responsible approach to reporting scientific discoveries in medicine. The dominant anti-constructivist, realist approach often results in what we term "dramatic modalization," which attributes greater facticity and universality to scientific findings than they actually possess at the time of publication, leading to significant moral consequences.To illustrate this, we will first explore the STS perspective as a framework for understanding the construction of facts in practice. Next, through a discourse analysis of two historical cases in medical journalism—the MMR-autism link and the depression-serotonin connection—we will demonstrate that the realist media coverage of these cases engaged in dramatic modalization, resulting in tangible moral repercussions. We hereby propose an alternative STS model for science journalism in medicine, arguing that it offers a more morally responsible approach. 

Atahan Karagoz

Generative AI models like GPT-4o and DALL-E 3 are reshaping digital content creation, offering industries tools to generate diverse and sophisticated text and images with remarkable creativity and efficiency. This paper examines both the capabilities and challenges of these models within creative workflows. While they deliver high performance in generating content with creativity, diversity, and technical precision, they also raise significant ethical concerns. Our study addresses two key research questions: (a) how these models perform in terms of creativity, diversity, accuracy, and computational efficiency, and (b) the ethical risks they present, particularly concerning bias, authenticity, and potential misuse. Through a structured series of experiments, we analyze their technical performance and assess the ethical implications of their outputs, revealing that although generative models enhance creative processes, they often reflect biases from their training data and carry ethical vulnerabilities that require careful oversight. This research proposes ethical guidelines to support responsible AI integration into industry practices, fostering a balance between innovation and ethical integrity.

Dimas Pratomo, Muhammad Kurniawan, Nur Fitri Handayani

Introduction: In the distribution of financing, the implementation of green banking is outlined in green finance, which is one of the financing schemes or lending to environmentally friendly businesses. Green finance activities focus on risk mitigation in providing financing to sustainable development projects by considering the impact that these projects will have. Objectives: This research aims to find out how the application of green banking implementation analysis mitigates the risk of financing distribution. Method: This research is qualitative research of descriptive type. The data sources in this study are the BSI and BRI Sustainability Reports for the 2021-2022 period. The data collection technique used is the library method. Results: The results of this study are seen based on a comparative study conducted between Bank Syariah Indonesia and Bank Rakyat Indonesia, there are differences and similarities between the two banks. One of the differences between the two banks lies in terms of bank monitoring of the company being financed, BSI monitors its business once every three months while BRI monitors it once a year. In addition, there are also similarities between the two banks, one of the similarities between the two banks lies in providing financing to palm oil companies that must have ISPO or RSPO certificates before financing. Implications: This research is expected to provide implications for the green banking program implemented by Bank BSI and Bank BRI in mitigating the risk of financing distribution to customers. Both banks can complement each other to complement the shortcomings in their respective sectors.

Jiajun Liu, Fengling Dai, Qitai Song et al.

Abstract Background While the number of emergency patients worldwide continues to increase, emergency doctors often face moral distress. It hampers the overall efficiency of the emergency department, even leading to a reduction in human resources. Aim This study explored the experience of moral distress among emergency department doctors and analyzed the causes of its occurrence and the strategies for addressing it. Method Purposive and snowball sampling strategies were used in this study. Data were collected through in-depth, semi-structured interviews with 10 doctors working in the emergency department of a tertiary general hospital in southwest China. The interview data underwent processing using the Nvivo 14 software. The data analysis was guided by Colaizzi’s phenomenological analysis method. Study findings This study yielded five themes: (1) imbalance between Limited Medical Resources and High-Quality Treatment Needs; (2) Ineffective Communication with Patients; (3) Rescuing Patients With no prospect of treatment; (4) Challenges in Sustaining Optimal Treatment Measures; and (5) Strategies for Addressing Moral Distress. Conclusion The moral distress faced by emergency doctors stems from various aspects. Clinical management and policymakers can alleviate this distress by enhancing the dissemination of emergency medical knowledge to the general public, improving the social and economic support systems, and strengthening multidisciplinary collaboration and doctors’ communication skills.

Farah Shahin

This study explores the dynamic and diverse Islamic feminist movement, which aims to promote justice and gender equality by challenging patriarchal interpretations of Islamictexts and customs. Through the work of scholars such as Fatima Mernissi, this research highlights how Islamic feminism seeks to reinterpret Islamic theology and practice to uphold the rights and dignity of women. Using exploratory and historical qualitative methods, this research evaluates the significant contribution of Islamic feminists in challenging existing discourse and improving the status of women. This study examines the contributions of Islamic feminists in Morocco and the Arab world, focusing on their efforts to promote gender equality within an Islamic framework. by investigating Fatima Mernissi's work which emphasizes the need to re-read Islam's sacred texts and expose false and misogynistic hadith. Apart from that, the influence of Kecia Ali's thoughts in "Sexual Ethics and Islam" as well as the critical views of Asma Barlas, Leila Ahmed, and Amina Wadud regarding misinterpretations of the Koran enrich this research so that it provides a comprehensive view. She argues that Fatima Mernissi's works, by offering alternative readings of Islamic discourse on women, have advanced feminist debate and practice in the Arab world, enriching understanding of faith, gender, identity and culture in Islam.