AI and ethics最新文献

{"title":"Uncovering the gap: challenging the agential nature of AI responsibility problems","authors":"Joan Llorca Albareda","doi":"10.1007/s43681-025-00685-w","DOIUrl":"10.1007/s43681-025-00685-w","url":null,"abstract":"<div><p>In this paper, I will argue that the responsibility gap arising from new AI systems is reducible to the problem of many hands and collective agency. Systematic analysis of the agential dimension of AI will lead me to outline a disjunctive between the two problems. Either we reduce individual responsibility gaps to the many hands, or we abandon the individual dimension and accept the possibility of responsible collective agencies. Depending on which conception of AI agency we begin with, the responsibility gap will boil down to one of these two moral problems. Moreover, I will adduce that this conclusion reveals an underlying weakness in AI ethics: the lack of attention to the question of the disciplinary boundaries of AI ethics. This absence has made it difficult to identify the specifics of the responsibility gap arising from new AI systems as compared to the responsibility gaps of other applied ethics. Lastly, I will be concerned with outlining these specific aspects.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3857 - 3870"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43681-025-00685-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145169900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What is the patient re-identification risk from using de-identified clinical free text data for health research?","authors":"Elizabeth Ford,&nbsp;Simon Pillinger,&nbsp;Robert Stewart,&nbsp;Kerina Jones,&nbsp;Angus Roberts,&nbsp;Arlene Casey,&nbsp;Katie Goddard,&nbsp;Goran Nenadic","doi":"10.1007/s43681-025-00681-0","DOIUrl":"10.1007/s43681-025-00681-0","url":null,"abstract":"<div><p>Important clinical information is recorded in free text in patients’ records, notes, letters and reports in healthcare settings. This information is currently under-used for health research and innovation. Free text requires more processing for analysis than structured data, but processing natural language at scale has recently advanced, using large language models. However, data controllers are often concerned about patient privacy risks if clinical text is allowed to be used in research. Text can be de-identified, yet it is challenging to quantify the residual risk of patient re-identification. This paper presents a comprehensive review and discussion of elements for consideration when evaluating the risk of patient re-identification from free text. We consider (1) the reasons researchers want access to free text; (2) the accuracy of automated de-identification processes, identifying best practice; (3) methods previously used for re-identifying health data and their success; (4) additional protections put in place around health data, particularly focussing on the UK where “Five Safes” secure data environments are used; (5) risks of harm to patients from potential re-identification and (6) public views on free text being used for research. We present a model to conceptualise and evaluate risk of re-identification, accompanied by case studies of successful governance of free text for research in the UK. When de-identified and stored in secure data environments, the risk of patient re-identification from clinical free text is very low. More health research should be enabled by routinely storing and giving access to de-identified clinical text data.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 5","pages":"4441 - 4454"},"PeriodicalIF":0.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12449363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ethical practices of artificial intelligence: a management framework for responsible AI deployment in businesses","authors":"Ajay Tripathi,&nbsp;Vinod Kumar","doi":"10.1007/s43681-025-00670-3","DOIUrl":"10.1007/s43681-025-00670-3","url":null,"abstract":"<div><p>AI is transforming how organizations operate, make choices, and compete in today's innovative world. AI approaches like machine learning, natural language processing, and robots may boost corporate efficiency, creativity, and client personalization. These advantages come with issues and problems that organizations must solve to guarantee ethical usage and public confidence. AI in business raises several ethical issues. It includes data privacy, biased algorithms, transparency, accountability, and social and economic effects on employment and equality. AI affects stakeholders like workers, consumers, and society. Thus, adopting AI into company processes requires a management structure that addresses these issues. This research paper proposed a framework that can help organizations to create, deploy, and employ AI technologies. This research article attempts to contribute to the developing topic of AI ethics in business by giving a clear AI management paradigm.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3845 - 3856"},"PeriodicalIF":0.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145168221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting fire incidents with ML: an XAI approach","authors":"Donghyeok Lee,&nbsp;Fernando Perez Tellez,&nbsp;Rajesh Jaiswal","doi":"10.1007/s43681-025-00683-y","DOIUrl":"10.1007/s43681-025-00683-y","url":null,"abstract":"<div><p>With increasing urbanization and industrial activities in Dublin city, there is a growing interest in natural disasters and accidents. In this research, we compared the regression performances for the number of fire incidents in Dublin with seven different machine learning models. We evaluated how each model performs with metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R-Squared scores. Among the used models which are Prophet, Auto-Regressive Integrated Moving Average (ARIMA), Simple Linear Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, and Random Forest Regression, the most precise model was the Prophet with the highest R-Squared score of 0.91 because it effectively captures the underlying trend, seasonality and holiday effects. This research also aims not only to establish the superior model but also to give clear and understandable reasons for these predictions using explainable AI (XAI). In particular, the trust in Prophet is enhanced by global explanation and local explanation for users to believe in the decision-making processes in the model. It enabled us to enhance the interpretability and transparency of the Prophet, which is aligning with ethical AI (Artificial Intelligence).</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 5","pages":"4429 - 4439"},"PeriodicalIF":0.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43681-025-00683-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145122434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT and ethics in healthcare facilities: an overview and innovations in technical efficiency analysis","authors":"Er-Rays Youssef,&nbsp;M’dioud Meriem,&nbsp;Hamid Ait-Lemqeddem","doi":"10.1007/s43681-025-00672-1","DOIUrl":"10.1007/s43681-025-00672-1","url":null,"abstract":"<div><p>Generative AI, such as OpenAI's ChatGPT, uses algorithms and models trained on vast amounts of textual data to understand and produce human-like responses. This technology has the potential to revolutionise healthcare management by improving efficiency, convenience, and personalization. However, the literature on applying ChatGPT and ethics to analyse healthcare facility efficiency is lacking. This paper aims to address this gap by conducting a scoping literature review. With the goal of exploring the application of ChatGPT in healthcare facilities, this review begins by outlining the key technologies that underpin ChatGPT and discussing the current state of efficient deployment infrastructure in various crucial fields. We then investigate the use of generative AI and LLMs in healthcare facilities. Subsequently, we examine how ChatGPT plays a pivotal role in enhancing efficiency in healthcare facility management. This entails analyzing its effect on various aspects of management processes. Following this, we scrutinise the existing challenges within smart healthcare and propose potential solutions to address them, such as ethics and trust. Finally, we look towards the future, evaluating the potential advancements and prospects of ChatGPT in improving the efficiency of healthcare facilities. We deduce that ChatGPT is poised to become an integral component within healthcare establishments as it continues to advance and becomes more finely adapted to the distinct environments and demands of the medical sector. We anticipate this as the legal, policy, and regulatory structures relevant to its application start to take shape.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3479 - 3496"},"PeriodicalIF":0.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI as artist: agency and the moral rights of creative works","authors":"David R. Charles","doi":"10.1007/s43681-025-00679-8","DOIUrl":"10.1007/s43681-025-00679-8","url":null,"abstract":"<div><p>The question of who possesses the moral rights of creative works made using the assistance of artificial intelligence (AI) is not fully resolved. In particular, the relationship between moral rights and moral agency in the production of creative works has been under-investigated in the literature. I explore these topics and argue that moral agency, intentionality and values-based reasoning are crucial for the entitlement of moral rights and hence the assignment of authorship. I conclude that, despite their great power to produce creative works, current generative AI systems cannot be the moral author of such works due to the absence of intentionality with values-based reasoning. Instead, the human end-user of a generative AI system is the moral author in most cases.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3833 - 3844"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145167279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The ethics of national artificial intelligence plans: an empirical lens","authors":"Manpriya Dua,&nbsp;J. P. Singh,&nbsp;Amarda Shehu","doi":"10.1007/s43681-025-00663-2","DOIUrl":"10.1007/s43681-025-00663-2","url":null,"abstract":"<div><p>Over fifty countries have published national infrastructure and strategy plans on Artificial Intelligence (AI), outlining their values and priorities regarding AI research, development, and deployment. This paper utilizes a deliberation and capabilities-based ethics framework rooted in providing freedom of agency and choice to human beings– to investigate how different countries approach AI ethics within their national plans. We explore the commonalities and variations in national priorities and their implications for a deliberation and capabilities-based ethics approach. Combining established and novel methodologies such as content analysis, graph structuring, and generative AI, we uncover a complex landscape where traditional geostrategic formations intersect with new alliances, thereby revealing how various groups and associated values are prioritized. For instance, the Ibero-American AI strategy highlights strong connections among Latin American nations, particularly with Spain, emphasizing gender diversity but pragmatically and predominantly as a workforce issue. In contrast, a US-led coalition of “science and tech first movers\" is more focused on advancing foundational AI and diverse applications. The European Union AI strategy showcases leading states like France and Germany while addressing regional divides, with more focus and detail on social mobility, sustainability, standardization, and democratic governance of AI. These findings offer an empirical lens into the current global landscape of AI development and ethics, revealing distinct national trajectories in the pursuit of ethical AI.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3803 - 3831"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43681-025-00663-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145167280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing artificial intelligence in Alzheimer's disease management: navigating ethical challenges in AI","authors":"Fatemeh Habibi,&nbsp;Shadi Ghaderkhani,&nbsp;Marzieh Shokoohi,&nbsp;Tara Banari,&nbsp;Mahsa Morsali,&nbsp;Reza Nejad Shahrokh Abadi,&nbsp;Hoora Kiamehr","doi":"10.1007/s43681-025-00673-0","DOIUrl":"10.1007/s43681-025-00673-0","url":null,"abstract":"<div><p>Alzheimer's disease (AD) presents a significant global health challenge, characterized by progressive cognitive decline and affecting millions worldwide, particularly among the elderly population. While aging remains the primary risk factor, the etiology of AD is multifactorial, involving genetic predispositions and environmental influences. Effective management strategies are essential, necessitating early detection and intervention. This article explores the potential role of artificial intelligence (AI) in addressing the complexities of AD management, emphasizing the ethical considerations inherent in AI applications. This systematic review follows PRISMA guidelines to synthesize existing literature on AI applications in AD management. The study involves a comprehensive literature search, study selection, data extraction, data analysis, and quality assessment using the appraisal tool for cross-sectional studies (AXIS). Data were analyzed, and figures were created using R programming. AI-driven technologies offer innovative approaches for early diagnosis, personalized treatment planning, and caregiver support. Leveraging intelligent sensing systems and genetic analysis, AI facilitates early detection by analyzing complex data patterns and identifying biomarkers associated with AD pathology. Additionally, AI enhances treatment outcomes through individualized interventions, utilizing advanced algorithms to analyze medical histories, genetic profiles, and lifestyle factors. Nanotechnology-based therapies and digital solutions further augment diagnostic and therapeutic capabilities, though rigorous evaluation is essential. Despite the promise of AI in AD management, ethical considerations such as algorithmic accuracy, data privacy, and the depersonalization of patient care must be addressed. Furthermore, the lack of standardized practices and regulatory guidelines presents challenges to the widespread implementation of AI technologies. Although AI shows promise in Alzheimer's disease management, collaborative efforts among policymakers, regulators, and the biomedical community are crucial to ensure the responsible and ethical integration of AI in AD management. By leveraging AI-driven innovations while addressing ethical concerns, this article advocates for improved patient outcomes and enhanced quality of life for individuals impacted by AD and their caregivers.Although AI shows promise in Alzheimer's disease management, collaborative efforts among policymakers, regulators, and the biomedical community are crucial to ensure the responsible and ethical integration of AI in AD management. By leveraging AI-driven innovations while addressing ethical concerns, this article advocates for improved patient outcomes and enhanced quality of life for individuals impacted by AD and their caregivers.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3461 - 3477"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An ecosystemic view on information, data, and knowledge: insights on agential AI and relational ethics","authors":"Stefano Calzati","doi":"10.1007/s43681-025-00665-0","DOIUrl":"10.1007/s43681-025-00665-0","url":null,"abstract":"<div><p>This article takes the lead from the data-information-knowledge-wisdom (DIKW) pyramid which is still a foundational paradigm in information science and applied fields. The goal is three-folded: (1) to outline a critique of such paradigm, with specific regard to its logico-objectivist standpoint; (2) to propose an information theory-based revisitation of the concepts of data, information, knowledge, and wisdom able to move beyond logico-objectivism; (3) to advance an ecosystemic rearrangement among data, information, and knowledge, whose key feature is the balanced entanglement between known and unknown. This will lead to conceptualizing agency as an <i>open-ended information-processing disposition</i>. Such conceptualization can prove useful to reframe discussions around Artificial Intelligence (AI) beyond sentience, emphasizing the epistemological <i>effects</i> that AI has in the world, as well as to advance an understanding of ethics as a relational <i>from-within</i> practice.</p></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3763 - 3776"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43681-025-00665-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145165928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hunting for humans: on slavery, the emergence of the US as the world’s first super industrial state and its deployment of artificial intelligence and other military technology to repress dissent and neutralize enemy combatants","authors":"Miron Clay-Gilmore","doi":"10.1007/s43681-025-00680-1","DOIUrl":"10.1007/s43681-025-00680-1","url":null,"abstract":"","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 4","pages":"3743 - 3762"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145166573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}