Front Public Health. 2026 Apr 16;14:1809934. doi: 10.3389/fpubh.2026.1809934. eCollection 2026.

ABSTRACT

BACKGROUND: Epidemiology has traditionally examined the distribution and determinants of health in populations. While early work focused on social determinants and collective conditions, recent decades have seen a shift toward individualized, molecular, and risk-based models emphasizing behavior, biology, and lifestyle. This shift has often obscured structural determinants and reinforced a biomedical paradigm. Feminist scholarship critiques these trends by centering lived experiences, power dynamics, and inequities in health research.

MAIN BODY: This commentary explores how feminist principles can inform epidemiology, and Public Health, bridging the divide between positivist health sciences and feminist epistemologies. It outlines key feminist contributions including epistemology, theory, methodology, and reflexivity, and demonstrates how they can be operationalized in epidemiological practice. Feminist epidemiology emphasizes problem definition grounded in marginalized experiences, co-production of knowledge, intersectional analysis of sex, gender, and other social determinants, and critical attention to power relations. It advocates for the integration of qualitative, quantitative, and mixed methods, including non-traditional data sources and inclusive language, while maintaining scientific rigor through reflexivity and contextual sensitivity.

CONCLUSION: Incorporating feminist principles transforms epidemiology and Public Health into a socially accountable, reflexive, and justice-oriented discipline. Health is both biological and political, and evidence production must account for structural inequalities, marginalized voices, and experiential knowledge. Feminist epidemiology does not sacrifice methodological rigor. It expands its scope to include ethical, social, and participatory dimensions, promoting more inclusive, accurate, and equitable science.

PMID:42077945 | PMC:PMC13128595 | DOI:10.3389/fpubh.2026.1809934

J Clim Chang Health. 2026 Apr 29;29:100653. doi: 10.1016/j.joclim.2026.100653. eCollection 2026 May-Jun.

ABSTRACT

BACKGROUND: Climate change poses significant public health challenges, particularly in low- and middle-income countries (LMICs), where ethical considerations are critical for equitable research. This systematic review synthesizes existing knowledge on climate change, public health, and research ethics in LMICs to identify key themes and research gaps.

METHODS: A systematic search of PubMed and Medline (2001-2024) identified 643 articles, of which 86 met inclusion criteria. Studies were thematically synthesized, and keyword co-occurrence mapping and cluster analysis were used to explore associations between health and ethical themes. Data visualization, including keyword co-occurrence mapping and hierarchical clustering, was performed to highlight thematic associations and research gaps.

RESULTS: Out of 86 studies 53.48 % were were published after the year 2022. Research is predominantly focused on mortality, outbreaks, and epidemics, mostly associated in ethical contextss such as community rights and beneficence. Associations were strongest between "Rights and Liberties" and "Community Rights." However, ethical considerations were inconsistently integrated, with equity and justice particularly underrepresented in studies on non-communicable diseases and maternal health. Most of the studies relied on secondary data, reflecting gaps in localized, context-specific evidence. Geographically, South Asia and parts of Africa were represented, while Southeast Asia and Latin America were markedly underrepresented despite major climate-related health risks.

CONCLUSION: This review highlights increasing research interests in climate change and health but identifies gaps in ethical frameworks and LMIC representation. Strengthening research agendas with context-specific ethical considerations and prioritizing vulnerable populations is essential for equitable health responses towards climate change in resource-limited settings.

PMID:42094743 | PMC:PMC13141464 | DOI:10.1016/j.joclim.2026.100653

Infect Dis Poverty. 2026 May 22;15(1):59. doi: 10.1186/s40249-026-01460-7.

ABSTRACT

Climate change poses an escalating threat to health, livelihoods, and economic development in Sierra Leone, a coastal, low-income country highly dependent on rain-fed agriculture for sustenance and revenue. Rising temperatures, erratic rainfall, floods, landslides, sea-level rise, and coastal erosion disrupt food systems and damage infrastructure, subsequently entrenching poverty, with projected gross domestic product losses of up to 10% by 2050. The health impacts fall disproportionately on children, adolescents and young people, pregnant women, the elderly, and the urban poor, including increased vector- and water-borne diseases, heat-related morbidity, non-communicable diseases, malnutrition, mental illness, and gender-based violence, particularly in informal coastal settlements. Despite these risks, climate adaptation and mitigation remain weakly integrated across sectors. Conflicting policies, fragmented governance systems, inadequate domestic financing, and over-reliance on unpredictable donor support undermine implementation of existing frameworks such as the National Adaptation Programme of Action. An example of policy conflicts is the extractive-sector priorities directly countering those of environmental protection and public health. This correspondence interrogates global and local institutional readiness to mitigate climate-related health risks, drawing on the WHO Operational Framework for Climate-Resilient Health Systems and the multidimensional climate justice approach. Using the July 2025 International Court of Justice advisory opinion on climate change as a legal and moral anchor, we argue for urgent, health-centred, and justice-oriented climate actions. We highlight the need for strengthened cross-sectoral governance, community-level implementation, and legal accountability, particularly in securing international climate financing for adaptation as part of States' human rights obligations under the United Nations Framework Convention on Climate Change Loss and Damage Framework. We contend that the International Court of Justice opinion provides Sierra Leone with a critical new basis to advocate for international support to protect the fundamental right to health.

PMID:42174741 | PMC:PMC13196226 | DOI:10.1186/s40249-026-01460-7

Milbank Q. 2026 May 24. doi: 10.1111/1468-0009.70095. Online ahead of print.

ABSTRACT

Policy Points The criminal justice system functions as a primary social determinant of health in the United States, generating disproportionate physical, psychological, and chronic health burdens on Black communities and other marginalized groups. Policing structural barriers-including qualified immunity, police union contracts, and municipal financing of misconduct settlements-systematically shield law enforcement from accountability and divert public resources from health-promoting investments. Evidence-based interventions-including coresponder programs, community violence interruption, diversion initiatives, and Medicaid prerelease enrollment-demonstrate measurable improvements in public safety and health equity outcomes. Policymakers must adopt a health-in-all-policies approach that reallocates resources from punitive criminal justice practices to upstream investments in housing, mental health care, youth employment, and community well-being. Transforming criminal justice into a health-promoting system requires cross-sectoral leadership, rigorous research, and training reform that centers racial equity, officer well-being, and community-driven public safety models.

CONTEXT: The United States incarcerates more people per capita than any peer nation, and its criminal justice system disproportionately impacts Black, Indigenous, and other communities of color. Police violence, mass incarceration, and carceral health crises each independently generate significant health burdens, while their intersection compounds longstanding racial health disparities. The COVID-19 pandemic amplified these structural failures, exposing the lethal consequences of overcrowded facilities, inadequate health care access, and systemic racism embedded across criminal justice institutions.

METHODS: This perspective piece synthesizes peer-reviewed literature, national surveillance data, and policy analyses to examine the criminal justice system as a social determinant of health. Drawing on the Public Health Critical Race Praxis framework, the authors identify mechanisms linking carceral practices to population health outcomes and evaluate both policy gains and persistent failures across policing, mass incarceration, and community health domains.

FINDINGS: Police violence, disproportionately directed at Black individuals-who are 3.5 times more likely than White individuals to be killed by police when unarmed-generates illness spillovers including elevated rates of chronic disease and mental health disorders in affected communities. Carceral settings function as breeding grounds for infectious disease, with COVID-19 infection rates in some US detention facilities reaching up to 14 times higher than surrounding general populations. Policing structural barriers including qualified immunity, police union contracts, and municipal financing of misconduct settlements insulate officers from accountability and redirect billions in public funds away from health-promoting services. Evidence-based alternatives-including coresponder programs, diversion initiatives, community violence interruption, and Medicaid prerelease enrollment-demonstrate measurable reductions in crime, use of force, and health disparities.

CONCLUSIONS: The criminal justice system is not a neutral arbiter of public safety but a potent and often detrimental determinant of health, particularly for Black and other marginalized communities. Dismantling the carceral shadow requires policymakers to adopt a health-in-all-policies approach that reallocates resources upstream, holds law enforcement accountable, and centers rehabilitation over punishment. A fundamental reconception of public safety as public health is both a moral imperative and an evidence-based strategy for advancing health equity and reducing the chronic disease, mental health, and mortality burdens generated by current carceral practices.

PMID:42178861 | DOI:10.1111/1468-0009.70095

JAMIA Open. 2026 May 22;9(3):ooag074. doi: 10.1093/jamiaopen/ooag074. eCollection 2026 Jun.

ABSTRACT

BACKGROUND: The integration of artificial intelligence (AI) into health care is critically dependent on vast quantities of patient data, igniting an urgent global debate on data ownership, privacy, and governance. While numerous perspectives exist, the empirical structure and evolution of this scholarly discourse remain uncharacterized. We aimed to systematically map the conceptual landscape of research on AI and health data governance to identify its core themes, temporal trends, and key focus areas.

METHODS: We conducted a scoping review according to PRISMA guidelines, searching PubMed, Scopus, and Web of Science for peer-reviewed articles published between January 1, 2018, and May 31, 2025. We performed a descriptive analysis of publication trends. Using Latent Dirichlet Allocation (LDA), we applied computational topic modelling to the abstracts, which serve as concise summaries of each article's core contributions, to identify latent thematic structures. Topic trends were analyzed using linear regression.

FINDINGS: Forty-three articles met the inclusion criteria. The volume of publications has increased substantially since 2018. Our LDA analysis identified five distinct research topics: (1) AI Applications & Ownership, (2) AI Models & Data Privacy, (3) Data Sharing Platforms & Technology, (4) Ethical & Legal Concerns, and (5) AI Development & Implementation. Over the study period, research on Ethical & Legal Concerns showed a statistically significant increasing trend in prevalence (slope = 0.023, P = .008), becoming the most dominant topic in recent years.

INTERPRETATION: The scholarly discourse on AI and health data has matured, shifting from foundational questions of technical implementation towards a dominant focus on complex ethical and legal challenges. This data-driven evidence signals an urgent need for clinical leaders and policymakers to move beyond theoretical discussions and implement robust, practical governance frameworks. Failure to address this governance gap risks impeding trustworthy AI innovation and eroding public trust, thereby limiting the potential of AI to improve patient outcomes equitably.

PMID:42181700 | PMC:PMC13197116 | DOI:10.1093/jamiaopen/ooag074

J Empir Res Hum Res Ethics. 2026 May 26:15562646261453477. doi: 10.1177/15562646261453477. Online ahead of print.

ABSTRACT

PurposeThis Commentary examines whether current ethics approval systems for medical research, grounded in the Belmont Report's principles of respect for persons, beneficence, and justice, paradoxically result in preventable deaths by delaying patient access to experimental therapies and proposes a framework for democratizing ethics oversight while maintaining safety.FindingsPeer-reviewed evidence demonstrates that ethics delays impose mortality costs that vastly exceed the harms they prevent, particularly for terminal illnesses. Bayesian decision analysis confirms current statistical thresholds are substantially more conservative than optimal for fatal diseases. COVID-19 pandemic responses proved that regulatory timelines can be dramatically compressed through organizational innovation, including accelerated vaccine development and distributed open-source manufacturing, without sacrificing safety.ConclusionsA five-part framework can enable patient autonomy in research ethics while preserving robust safeguards against exploitation: tiered consent based on disease severity, adaptive trial designs with patient governance, mandatory open-source transparency, post-market surveillance, and independent safety monitoring with patient representation.

PMID:42186370 | DOI:10.1177/15562646261453477

Int J Environ Res Public Health. 2026 May 2;23(5):604. doi: 10.3390/ijerph23050604.

ABSTRACT

Organizations ought to demonstrate a responsibility for conditions that reduce moral stress and enhance moral resilience for their employees. No literature to date has explored how Emergency Management Personnel (EMP) experience both moral stress and distress [(di)stress], building up to stigma during health crises, given their role in emergency management operations. This study draws from a primary study of EMP, including frontline and first responders and those in leadership, who reported structural stigma during the COVID-19 pandemic. Our research question was, In what ways did structural stigma shape the moral landscape of emergency management practice during COVID-19? This qualitative study draws on the paradigm of critical realism to conduct thematic analysis. Interviews and focus groups were collected in 2024 from a total of 23 participants in the Greater Toronto Area, Canada. Participants represented EMP across emergency and public service sectors. System-level stressors revealed disruptions or "cracks" from an overwhelmed public services system. In sum, systemic "cracks" gave rise to organizational mechanisms designed to compensate for system failures, inadvertently propagating structural stigma. At times these mechanisms generated moral distress and/or resilience, through simultaneously expanding and limiting EMP's responsibility and agency. The authors suggest that EMP build their leadership capacity to enhance skills of structural competency.

PMID:42196697 | DOI:10.3390/ijerph23050604

Healthcare (Basel). 2026 May 15;14(10):1364. doi: 10.3390/healthcare14101364.

ABSTRACT

Background: Artificial intelligence (AI) is transitioning from experimental pilots to core public health functions such as disease surveillance, resource planning, and analysis of social and structural determinants of health. Yet, health data collection and stewardship remain fragmented across the globe; some jurisdictions still rely on paper-based systems, while others operate noninteroperable digital systems that can exacerbate inequities. Treating health data as a global good therefore requires governance that enables innovation while protecting rights, safety, and trust. This study aims to develop a conceptual meso-level capability framework that translates responsible AI principles into organizational practices for public health agencies. Methods: We developed the framework using a targeted narrative synthesis of contemporary governance guidance and documented early implementation experiences, purposively selected to represent major strands of current practice and debate. A structured expert panel consultation (n = 9) was subsequently conducted to assess the face validity and content validity of the proposed framework domains. Results: We propose the Public Health Responsible AI Capability (PH-RAIC) framework, which adapts principles of transparency, accountability, fairness, ethics, and safety to institutional realities faced by public health agencies. PH-RAIC identifies four interdependent capability domains: (1) strategic governance and alignment; (2) data and infrastructure stewardship; (3) participatory design, equity, and public engagement; and (4) lifecycle oversight, learning, and decommissioning. All four domains achieved Content Validity Index (CVI) values ≥ 0.85 in the expert panel consultation. The framework is presented as a conceptual, meso-level model that has undergone preliminary expert validation but requires further empirical testing in real-world agency settings. Conclusions: PH-RAIC links these domains to example practices, diagnostic questions, and illustrative measurement indicators to help agencies navigate efficiency-equity trade-offs and strengthen legitimacy and accountability in AI-enabled public health systems. It offers a validated conceptual basis for future empirical testing and operational readiness tools.

PMID:42194456 | DOI:10.3390/healthcare14101364

J Bioeth Inq. 2026 May 27. doi: 10.1007/s11673-026-10570-8. Online ahead of print.

ABSTRACT

Vaccination is both a clinical intervention and a public health tool, creating an inherent tension between individual rights and collective goods in the context of mandatory vaccination policies. There is an additional layer of complexity to this in the context of a significant public health crisis. The law has similarly had to manage the tension between consent and coercion with respect to vaccine mandates. Broadly speaking, "mandatory vaccination" is any policy or directive that makes vaccination a condition of being able to participate in a particular activity or to receive a particular benefit. COVID-19 vaccine mandates were introduced in varying forms in every Australian jurisdiction in 2021. This article explores the extent to which the law grappled with the principles and obligations that stem from the ethical principle of autonomy on an individual level and the countervailing pressure of protecting public health in Australia. Applying the ethical framework set out by the World Health Organization COVID-19 Ethics and Governance Working Group, this article considers synergies between law and ethics and makes the case for a more principled and ethically informed policy approach to vaccine mandates in any future public health emergency in Australia.

PMID:42201631 | DOI:10.1007/s11673-026-10570-8

Annu Rev Public Health. 2026 Apr;47(1):19-39. doi: 10.1146/annurev-publhealth-090924-033158. Epub 2025 Dec 23.

ABSTRACT

Environmental justice (EJ) research is an interdisciplinary field of study concerned with the unequal distribution of environmental burdens and benefits across different sociodemographic identities (e.g., race, class). While considerations of space and time with respect to environmental exposures and health outcomes have always been central to EJ, the state of the science on geospatial methods, measures, and technologies is rapidly advancing, as are their applications in research. We find that geospatial technologies have extended researchers' abilities to more precisely link the spatial extents of environmental exposures to when and where people live, work, and play. Geospatial data are also useful in analyzing systemic oppression and structural racism as root causes of environmental injustice via metrics of segregation and redlining. This review provides an overview of how geospatial methods and technologies are being applied to EJ research for (a) population identification, (b) exposure assessment, (c) outcome ascertainment, and (d) research translation.

PMID:41435136 | DOI:10.1146/annurev-publhealth-090924-033158

Int J Health Geogr. 2026 Mar 2;25(1):23. doi: 10.1186/s12942-026-00460-y.

ABSTRACT

BACKGROUND: The increasing use of geographic data about individuals in health and social research raises ethical challenges that extend beyond existing legal frameworks. While regulations such as data protection laws define boundaries, they rarely provide researchers with sufficient practical guidance for addressing geoprivacy risks.

METHODS: We developed a structured, reflexive ethical framework tailored for research involving human-centered geographic data. The framework was designed using a lifecycle approach and informed by both a review of existing literature and the expertise of the multidisciplinary author team. It organizes ethical considerations into five research phases: data collection, storage, sharing, analysis, and results dissemination. To enhance usability, we translated these considerations into 60 guiding questions, each assigned an importance level (high, moderate, or low). An ethical review applicability matrix was also introduced to help determine the level of ethical scrutiny required, based on study characteristics such as data type, granularity, linkage potential, and participant vulnerability.

RESULTS: The framework offers a practical and scalable tool for embedding ethical reflection into research processes. It supports proportionate ethical review by aligning the sensitivity of specific research practices with the corresponding importance of guiding questions. To demonstrate its adaptability, we provide two case studies in the supplementary materials that apply the framework to different research scenarios with varying levels of geoprivacy sensitivity.

CONCLUSIONS: By encouraging early and context-aware engagement with ethical risks, this framework safeguards participant dignity, fosters transparency, and advances ethically responsible research involving geographic data. It equips both researchers and ethics committees with a systematic approach for addressing geoprivacy challenges across diverse health and social science contexts.

PMID:41772605 | PMC:PMC13092162 | DOI:10.1186/s12942-026-00460-y

Annu Rev Public Health. 2026 Apr;47(1):19-39. doi: 10.1146/annurev-publhealth-090924-033158. Epub 2025 Dec 23.

ABSTRACT

Environmental justice (EJ) research is an interdisciplinary field of study concerned with the unequal distribution of environmental burdens and benefits across different sociodemographic identities (e.g., race, class). While considerations of space and time with respect to environmental exposures and health outcomes have always been central to EJ, the state of the science on geospatial methods, measures, and technologies is rapidly advancing, as are their applications in research. We find that geospatial technologies have extended researchers' abilities to more precisely link the spatial extents of environmental exposures to when and where people live, work, and play. Geospatial data are also useful in analyzing systemic oppression and structural racism as root causes of environmental injustice via metrics of segregation and redlining. This review provides an overview of how geospatial methods and technologies are being applied to EJ research for (a) population identification, (b) exposure assessment, (c) outcome ascertainment, and (d) research translation.

PMID:41435136 | DOI:10.1146/annurev-publhealth-090924-033158

Int J Health Geogr. 2026 Mar 2;25(1):23. doi: 10.1186/s12942-026-00460-y.

ABSTRACT

BACKGROUND: The increasing use of geographic data about individuals in health and social research raises ethical challenges that extend beyond existing legal frameworks. While regulations such as data protection laws define boundaries, they rarely provide researchers with sufficient practical guidance for addressing geoprivacy risks.

METHODS: We developed a structured, reflexive ethical framework tailored for research involving human-centered geographic data. The framework was designed using a lifecycle approach and informed by both a review of existing literature and the expertise of the multidisciplinary author team. It organizes ethical considerations into five research phases: data collection, storage, sharing, analysis, and results dissemination. To enhance usability, we translated these considerations into 60 guiding questions, each assigned an importance level (high, moderate, or low). An ethical review applicability matrix was also introduced to help determine the level of ethical scrutiny required, based on study characteristics such as data type, granularity, linkage potential, and participant vulnerability.

RESULTS: The framework offers a practical and scalable tool for embedding ethical reflection into research processes. It supports proportionate ethical review by aligning the sensitivity of specific research practices with the corresponding importance of guiding questions. To demonstrate its adaptability, we provide two case studies in the supplementary materials that apply the framework to different research scenarios with varying levels of geoprivacy sensitivity.

CONCLUSIONS: By encouraging early and context-aware engagement with ethical risks, this framework safeguards participant dignity, fosters transparency, and advances ethically responsible research involving geographic data. It equips both researchers and ethics committees with a systematic approach for addressing geoprivacy challenges across diverse health and social science contexts.

PMID:41772605 | PMC:PMC13092162 | DOI:10.1186/s12942-026-00460-y

Annu Rev Public Health. 2026 Apr;47(1):19-39. doi: 10.1146/annurev-publhealth-090924-033158. Epub 2025 Dec 23.

ABSTRACT

Environmental justice (EJ) research is an interdisciplinary field of study concerned with the unequal distribution of environmental burdens and benefits across different sociodemographic identities (e.g., race, class). While considerations of space and time with respect to environmental exposures and health outcomes have always been central to EJ, the state of the science on geospatial methods, measures, and technologies is rapidly advancing, as are their applications in research. We find that geospatial technologies have extended researchers' abilities to more precisely link the spatial extents of environmental exposures to when and where people live, work, and play. Geospatial data are also useful in analyzing systemic oppression and structural racism as root causes of environmental injustice via metrics of segregation and redlining. This review provides an overview of how geospatial methods and technologies are being applied to EJ research for (a) population identification, (b) exposure assessment, (c) outcome ascertainment, and (d) research translation.

PMID:41435136 | DOI:10.1146/annurev-publhealth-090924-033158

Int J Health Geogr. 2026 Mar 2;25(1):23. doi: 10.1186/s12942-026-00460-y.

ABSTRACT

BACKGROUND: The increasing use of geographic data about individuals in health and social research raises ethical challenges that extend beyond existing legal frameworks. While regulations such as data protection laws define boundaries, they rarely provide researchers with sufficient practical guidance for addressing geoprivacy risks.

METHODS: We developed a structured, reflexive ethical framework tailored for research involving human-centered geographic data. The framework was designed using a lifecycle approach and informed by both a review of existing literature and the expertise of the multidisciplinary author team. It organizes ethical considerations into five research phases: data collection, storage, sharing, analysis, and results dissemination. To enhance usability, we translated these considerations into 60 guiding questions, each assigned an importance level (high, moderate, or low). An ethical review applicability matrix was also introduced to help determine the level of ethical scrutiny required, based on study characteristics such as data type, granularity, linkage potential, and participant vulnerability.

RESULTS: The framework offers a practical and scalable tool for embedding ethical reflection into research processes. It supports proportionate ethical review by aligning the sensitivity of specific research practices with the corresponding importance of guiding questions. To demonstrate its adaptability, we provide two case studies in the supplementary materials that apply the framework to different research scenarios with varying levels of geoprivacy sensitivity.

CONCLUSIONS: By encouraging early and context-aware engagement with ethical risks, this framework safeguards participant dignity, fosters transparency, and advances ethically responsible research involving geographic data. It equips both researchers and ethics committees with a systematic approach for addressing geoprivacy challenges across diverse health and social science contexts.

PMID:41772605 | PMC:PMC13092162 | DOI:10.1186/s12942-026-00460-y

Front Artif Intell. 2026 Apr 15;9:1800302. doi: 10.3389/frai.2026.1800302. eCollection 2026.

ABSTRACT

INTRODUCTION: Artificial intelligence ethics is often framed as a response to unprecedented technical autonomy, with risks attributed to recent advances in machine learning and scale. This framing overlooks a recurring ethical structure: the delegation of moral authority to artificial agents. Ethical failures associated with AI are best understood as governance failures rooted in human design choices and accountability arrangements, even where opacity and limited control complicate responsibility attribution.

METHODS: A qualitative, interdisciplinary approach integrates historical-thematic analysis, comparative interpretation of technological artifacts, and visual-conceptual synthesis. Mythological figures (Talos, the Golem, Pygmalion), early mechanical automata, and foundational computational systems are analyzed as conceptual models of delegated artificial agency rather than technological precursors.

RESULTS: Across historical contexts, artificial agents exhibit consistent structural features: bounded autonomy, delegated authority, explicit override mechanisms, and dependence on human oversight. These features directly correspond to contemporary AI ethics concerns, including alignment failures, responsibility gaps, human-in-the-loop control, and system interruptibility.

DISCUSSION: The analysis establishes that ethical risk in AI arises from the displacement of human responsibility rather than from machine autonomy. By situating AI within a longer history of artificial agency, the study provides a normative framework that locates moral responsibility unambiguously in human actors and institutions, with direct implications for AI governance and accountability.

PMID:42064034 | PMC:PMC13125054 | DOI:10.3389/frai.2026.1800302

Front Artif Intell. 2026 Apr 15;9:1800302. doi: 10.3389/frai.2026.1800302. eCollection 2026.

ABSTRACT

INTRODUCTION: Artificial intelligence ethics is often framed as a response to unprecedented technical autonomy, with risks attributed to recent advances in machine learning and scale. This framing overlooks a recurring ethical structure: the delegation of moral authority to artificial agents. Ethical failures associated with AI are best understood as governance failures rooted in human design choices and accountability arrangements, even where opacity and limited control complicate responsibility attribution.

METHODS: A qualitative, interdisciplinary approach integrates historical-thematic analysis, comparative interpretation of technological artifacts, and visual-conceptual synthesis. Mythological figures (Talos, the Golem, Pygmalion), early mechanical automata, and foundational computational systems are analyzed as conceptual models of delegated artificial agency rather than technological precursors.

RESULTS: Across historical contexts, artificial agents exhibit consistent structural features: bounded autonomy, delegated authority, explicit override mechanisms, and dependence on human oversight. These features directly correspond to contemporary AI ethics concerns, including alignment failures, responsibility gaps, human-in-the-loop control, and system interruptibility.

DISCUSSION: The analysis establishes that ethical risk in AI arises from the displacement of human responsibility rather than from machine autonomy. By situating AI within a longer history of artificial agency, the study provides a normative framework that locates moral responsibility unambiguously in human actors and institutions, with direct implications for AI governance and accountability.

PMID:42064034 | PMC:PMC13125054 | DOI:10.3389/frai.2026.1800302

Front Artif Intell. 2026 Apr 15;9:1800302. doi: 10.3389/frai.2026.1800302. eCollection 2026.

ABSTRACT

INTRODUCTION: Artificial intelligence ethics is often framed as a response to unprecedented technical autonomy, with risks attributed to recent advances in machine learning and scale. This framing overlooks a recurring ethical structure: the delegation of moral authority to artificial agents. Ethical failures associated with AI are best understood as governance failures rooted in human design choices and accountability arrangements, even where opacity and limited control complicate responsibility attribution.

METHODS: A qualitative, interdisciplinary approach integrates historical-thematic analysis, comparative interpretation of technological artifacts, and visual-conceptual synthesis. Mythological figures (Talos, the Golem, Pygmalion), early mechanical automata, and foundational computational systems are analyzed as conceptual models of delegated artificial agency rather than technological precursors.

RESULTS: Across historical contexts, artificial agents exhibit consistent structural features: bounded autonomy, delegated authority, explicit override mechanisms, and dependence on human oversight. These features directly correspond to contemporary AI ethics concerns, including alignment failures, responsibility gaps, human-in-the-loop control, and system interruptibility.

DISCUSSION: The analysis establishes that ethical risk in AI arises from the displacement of human responsibility rather than from machine autonomy. By situating AI within a longer history of artificial agency, the study provides a normative framework that locates moral responsibility unambiguously in human actors and institutions, with direct implications for AI governance and accountability.

PMID:42064034 | PMC:PMC13125054 | DOI:10.3389/frai.2026.1800302