As generative artificial intelligence (GenAI) increasingly produces literary texts, ethical questions arise about how readers emotionally engage with AI-generated content, particularly when authorship is uncertain. This mixed-method study compares readers' empathy toward human- and AI-translated literary excerpts. Quantitative results showed no significant differences in affective, cognitive or associative empathy, or in perceived quality, between conditions. Qualitative analysis revealed that readers' engagement was driven primarily by textual features rather than authorship assumptions. However, when prompted to consider possible AI involvement, some participants reconsidered their judgments through attributional reasoning about machine capabilities. The findings suggest that authorship disclosure shapes interpretive autonomy and evaluative judgments of machine-generated texts, with important ethical implications.
This study examined relationships between dark/light personality traits and moral dilemma judgment, comparing humans and large language models (LLMs). Using the CNI model, we analyzed 404 Chinese participants and 2,092 LLM-generated responses. In humans, superordinate dark traits negatively predicted moral norm sensitivity, whereas superordinate light traits positively predicted it. At the subordinate level, sadism and Machiavellianism negatively predicted moral norm sensitivity, Kantianism positively predicted it, and faith in humanity predicted stronger general action preference. For LLMs, only the direction of effects on moral norm sensitivity was consistent with humans; substantial differences appeared in consequence sensitivity and general action preference. LLM-generated dark personality showed lower moral norm sensitivity and stronger action preference than LLM-generated light personality, whereas consequence sensitivity showed no stable pattern. The results reveal that LLMs only show a preliminary simulation capacity and fail to reflect the complex features of personality and moral judgment.
Advances in reproductive technologies using preimplantation genetic testing (PGT), particularly polygenic embryo screening (PGT-P), raise social and ethical questions about public acceptance. This factorial survey experiment using experimentally varied scenarios examined how situational conditions, sociodemographics, and personal values shape the moral acceptance and willingness to use PGT-P in a nationwide German sample. Moral acceptance and willingness were higher for reducing the risk of medical conditions than for increasing the chance of higher cognitive functioning. Willingness increased with insurance coverage and was subject to framing effects. Significant interpersonal differences existed. These results inform debates about the individual, social, and ethical implications of reproductive technologies.
Visual consent forms have been identified as a comprehensive and engaging method to obtain informed consent. These forms include imagery to explain concepts and enhance user understanding, meeting the growing need for inclusive consent methods that are lacking in traditional text-based consent forms. This visual consent study investigates the use of a visual consent approach among participants of the Raine Study, exploring their evaluation of both visual and traditional consent methods across conceptual categories of engagement, comprehension, and perception. Findings suggest that both consent methods were similarly effective in supporting participants' comprehension, engagement, and perceptions of the research process and assessments, diverging from outcomes of existing literature. Future comparative research within other longitudinal cohorts is warranted to determine if the results of this study are unique to the Raine Study or are generalizable across similar long-term studies.
Generative artificial intelligence (GenAI) continues to transform education, yet its integration raises ethical concerns such as algorithmic bias, privacy erosion, and diminished autonomy. This integrative review synthesizes literature to clarify how ethical risks emerge and how governance can respond. Using integrative review procedures, the study synthesized theoretical and policy sources from Scopus and Web of Science. Analysis applies three lenses: Critical Data Studies, FATE (fairness, accountability, transparency), and IEEE Ethically Aligned Design, producing a sociotechnical account. Across studies, risks cluster upstream in data and epistemic bias reproducing linguistic, cultural, and socioeconomic hierarchies; midstream in algorithmic failures weakening transparency, accountability, and contestability; and downstream in design and governance deficits eroding consent, recourse, and human-centered implementation. Implications include institutional lifecycle governance and auditing, participatory design, AI literacy, and targeted research priorities, especially intersectional and Global South studies. The review contributes a framework linking structural, operational, and design-level ethics for GenAI in education.
Grounded in Moral Foundations Theory and the Theory of Planned Behavior, this study examined how empathy, Dark Triad traits, and religiosity relate to attitudes toward Physician-Assisted Dying (AID). We surveyed 300 Romanian adults aged 18-60 (M = 27.49; 83.33% women). Results showed that higher religiosity was associated with less favorable attitudes toward AID, supporting a sanctity-based moral perspective. Empathy did not significantly predict attitudes, and religiosity did not moderate the empathy - AID relationship. Machiavellianism was negatively associated with support for AID, while narcissism showed a positive association. Age was negatively related to AID support. Overall, findings emphasize religiosity as a key factor shaping attitudes toward AID in a highly religious cultural context and reveal nuanced links between specific dark personality traits and end-of-life moral judgments. The study adds to the limited Eastern European research and highlights the value of integrating moral, cultural, and personality perspectives when examining public views on AID.
This study examined how moral reasoning, moral competence, and moral disengagement relate to cooperative behavior in a Prisoner's Dilemma Game (PDG) in which counterparts followed an adverse pattern of defections. A total of 163 Mexican university students responded standardized moral questionnaires (Defining Issues Test, Moral Competence Test, and Mechanisms of Moral Disengagement Scale) and participated online in a seven-round PDG in which pre-programmed counterparts initially cooperated and later defected. Furthermore, payoff framing (only gains vs. gains and losses) and information about others were experimentally manipulated. Results show a marked decline in cooperation once defections were introduced, which became stronger under possible loss framing, while initial cooperation was higher under greater uncertainty about others' cooperativeness. More sophisticated moral reasoning predicted continued cooperation despite these adverse conditions. Moral competence and moral disengagement showed no meaningful effects. These findings refine earlier research on "sucker-resistance" in morally sophisticated individuals.
Generative artificial intelligence (GAI) is reshaping peer review by reducing the cost of producing plausible, well-structured evaluative text while leaving the underlying cognitive work of reviewing only weakly observable. This article argues that AI-assisted peer review is, in practice, difficult to reverse because it is driven by convergent incentives-workload, speed, and competition-in a context where both reviewer effort and AI use are difficult to detect. Drawing on a qualitative analysis of recent literature and institutional policies, the article identifies three interrelated risks: effort outsourcing and accountability laundering, the limited detectability of AI-generated review reports, and adversarial vulnerabilities such as prompt injection embedded in manuscripts. In response, it proposes an auditable hybrid governance model centered on confidentiality, reviewer accountability, secure infrastructure, granular disclosure, and evidence-anchored auditing. The article concludes that preserving peer review as a practice of responsible judgment requires governance mechanisms that make AI-assisted workflows more verifiable without relying solely on bans or textual policing.
Authorship malpractice is increasingly normalised in global academia, yet its institutional and behavioural drivers remain underexplored, particularly in resource-constrained systems. This study examines the phenomenon locally termed "You Put My Name, I Put Your Name" within the Nigerian academic context. Using qualitative data from semi-structured interviews with 18 lecturers, the findings identify five patterns: transactional authorship, promotion-driven padding, hierarchical patronage, reciprocal name-exchange, and unauthorised inclusion. These practices are shaped by promotion pressures, structural opportunities, cultural rationalisations, and power asymmetries. Three overarching themes emerge: uneven awareness of authorship standards, systemic institutional and financial drivers, and entrenched hierarchical dynamics. The study introduces the Authorship Misappropriation Diamond (AMD), extending the Fraud Diamond by adding "Normalisation" to explain how repeated misconduct becomes institutionalised, increasing pressure and reducing ethical resistance. The model offers a comprehensive framework for understanding, measuring, and addressing authorship misconduct across academic systems.
This study develops and validates the AI Disclosure Reluctance Scale (ADRS) to measure why academics conceal their use of generative AI despite transparency mandates. Integrating the Technology Acceptance Model, Expectancy-Value Theory, Cognitive Dissonance Theory, and Social Desirability Bias, six dimensions are identified: Stigma Aversion, Reputation Safeguard, Normative Uncertainty, Value Conflict Discomfort, Publication Gatekeeping Anxiety, and Career Jeopardy Concern. A three-stage scale development process reduced 72 items to 30. Exploratory factor analysis (n=435) supported a six-factor structure explaining 75.3% variance (alpha = 0.853-0.881). Confirmatory factor analysis (n=566) showed excellent model fit (RMSEA = 0.014, CFI = 0.995, SRMR = 0.024) and strong validity. The ADRS is a robust tool to diagnose psychological and institutional barriers to AI transparency and inform policy and intervention design.
Recent advances in neuroethical and moral psychological research have largely focused on the cognitive and emotional bases of moral judgments through the use of extreme and artificial moral dilemmas. These studies suffer from three key limitations: (1) overreliance on unrealistic, sacrificial dilemmas; (2) the complete omission of virtue ethics as a distinct moral framework; and (3) a lack of validated instruments that reflect the complexity of moral reasoning in everyday contexts. To address this issue, we developed and tested a 22-moral dilemma set that incorporates moral reasoning in three ethical traditions. Explanatory factor analysis with 349 participants aged 18-65 showed a strong context-dependency. Confirmatory factor analysis including 443 participants for 19 dilemmas with 38 corresponding binary items provided good model fit with RMSEA = 0.062, CFI = 0.987, and SRMR = 0.048. The findings of the present study suggest that efforts to measure moral reasoning through ethical dilemmas must move beyond rigid theoretical opposition and embrace more ecologically valid, context-sensitive conceptual models.
The rapid integration of generative artificial intelligence into research presents a profound paradox for research integrity, simultaneously introducing novel systemic risks and enabling innovative governance solutions. This systematic review examines 36 peer reviewed articles from 2023 to 2025 on generative AI and research integrity. Results show that AI lowers the barrier to misconduct while threatening core scientific values through research homogenization, reduced critical thinking, and authenticity problems. At the same time, AI helps develop detection tools, improve publishing work, and support ethics education. The root causes exist at three levels: technical, individual, and institutional. The literature suggests a governance framework that combines technical, institutional, educational, and team based strategies. However, current evidence is largely descriptive and lacks strong data on what works. Future research should focus on measuring real effects, using better methods, and exploring settings outside academia to support research integrity in the AI era.
Ethical practice is central to audiology and speech therapy (STA), yet ethical decision-making in South African practice management occurs within complex structural constraints. Conceptualising ethics as a situated and relational practice, this study explored ethical challenges encountered by practitioners and how these are negotiated across public and private contexts. A qualitative design was used, drawing on semi-structured interviews conducted in 2025 with 92 practitioners. Data were thematically analysed, with descriptive and exploratory statistical analyses used to examine sectoral patterns for analytical insight. Four interrelated themes emerged: resource-driven ethical dilemmas in the public sector; tensions between business ethics and financial sustainability in private practice; challenges related to culturally sensitive and ethical care; and ethical tensions associated with advocacy and systemic reform. Findings highlight ethics as everyday moral work that is structurally and relationally produced rather than solely individual. Addressing these challenges requires strengthened ethics education, mentorship, institutional support, and contextually grounded ethical guidance.
Ethics remediation assessments play a critical role in determining professional readiness to return to safe practice following disciplinary violations. This study offers a comprehensive psychometric evaluation of the Ethics and Boundaries Assessment Services (EBAS) instrumental, a structured ethics assessment widely used by licensing boards across healthcare. A sample of 562 completed constructed-response items across five core domains: Boundaries, Fraud, Professional Standards, Substance Abuse, and Unprofessional Conduct. Responses were scored using a four-point rubric by trained raters. Reliability, validity, and fairness were examined using multiple approaches, including interrater reliability via intraclass correlation coefficients (ICCs), construct validity through multitrait - multimethod (MTMM) analysis, confirmatory factor analysis (CFA), and item-level functioning through Graded Response IRT modeling. Results supported strong internal consistency, acceptable interrater reliability, and a theoretically coherent factor structure. These findings provide initial empirical support for the EBAS instrument as a defensible and psychometrically sound tool in high-stakes regulatory settings.
The integration of Generative AI (GenAI) raises distinct ethical concerns for second language (L2) writers, including issues of authorship, language development, and authorial voice. However, no validated instrument has specifically measured these concerns. This study develops and initially validates the AI Ethical Awareness in L2 AI-Assisted Academic Writing Scale (AEAL2-AWS). Data from 768 L2 university students in China were collected in two phases. Phase 1 (n = 650) employed Exploratory and Confirmatory Factor Analyses, supporting a 24-item, five-factor structure: Accountability and Authorship; Academic Integrity and Appropriate Use; Algorithmic Bias and Fairness; Transparency and Critical Use; and Impact on Language Learning and Voice. Phase 2 (n = 118) established nomological and criterion validity, showing strong correlations with general AI ethical attitudes. The scale demonstrated excellent model fit and high reliability, providing educators with a robust tool to assess L2 writers' ethical awareness in the GenAI era.
Academic dishonesty is a ubiquitous challenge, yet research often lacks psychological realism. This study develops a situated understanding of moral decision-making under conditions of "trusted autonomy." Using Constructivist Grounded Theory, I conducted in-depth interviews (N=23) with Turkish university students navigating unproctored, honor-code assessments. The resulting substantive theory, "Moral Navigation under Trusted Autonomy," reveals that decision-making is driven by co-acting contextual conditions-trust salience, assessment fairness, performance pressure, and peer norms-rather than stable traits. The theory identifies two primary paths: Affirming Integrity, driven by deontological commitment and the culturally specific motivation of vefa (gratitude-based reciprocity); and Legitimizing Dishonesty, driven by utilitarian calculation and moral disengagement. This research extends existing models by detailing how withdrawing external control acts as a relational moral claim. The findings offer practitioners non-punitive leverage points-focusing on design fairness and mutual trust-to proactively cultivate internal moral commitment and institutional integrity.
This essay presents a comprehensive bioethical analysis of medical gaslighting- the dismissal, minimization, or psychologization of patients' reported symptoms by healthcare professionals. Drawing on the four principles of biomedical ethics and the philosophical framework of epistemic injustice, the paper conceptualizes medical gaslighting as both a moral and epistemic harm that violates autonomy, beneficence, nonmaleficence, and justice. It further examines how disbelief toward patients- particularly women, ethnic minorities, and LGBTQ individuals- reflects systemic biases that erode trust and perpetuate inequality in healthcare. Beyond theoretical analysis, the essay offers practical recommendations for the prevention and repair of medical gaslighting, including integrating epistemic humility, narrative medicine, and testimonial justice into medical education, policy, and institutional practice. By reframing ethical medicine as an epistemically responsible and dialogical practice, this work advances bioethics by linking moral reasoning to actionable strategies for restoring trust, justice, and dignity in healthcare.
This research explores whether utilitarianism and deontology can be understood within the Construal Level Theory framework. We explore whether utilitarianism (vs. deontology), focused on the "greater good for the greatest number" as its objective, aligns with a high (vs. low) level of construal, focused on primary features and the goal of an event. We conducted an experimental study (N = 890) in which the level of construal was manipulated through social distance (high vs. low). Then measured the reported probability of participants taking utilitarian actions in three moral dilemmas and their perception of morality and appropriateness of the act itself. Although our manipulation did not affect the likelihood of taking action, a high construal level led to a more positive evaluation of morality and appropriateness of taking action. These findings add new knowledge to the role of construal level in influencing moral decision-making and moral judgments.
For counselors, the welfare of clients and the protection of the community are grounded in comprehension and implementation of ethical principles in practice. Counselors face increasing ethics complexity as organizational and political influences conflict with client's self-interest. Two thought-experiments involving a Tarasoff-like dilemma were used to explore factors related to ethical decision-making by clinicians in definitive and ambiguous duty-to-warn situations. Outcomes demonstrated that legal, moral, and social factors influenced ethical decision-making in a non-probability sample of 221 U.S. counselors who participated in the thought-experiment study. Increasing ethical uncertainty was related to a decrease in direct action, stronger influence of moral and social factors, and the stronger influence of ethical self-efficacy on decision-making. This study bridges the cognitive model of moral reasoning and social cognitive theory, extending the concept of agency into the ethical domain and suggesting refinements to moral reasoning models. Implications are discussed.
