Explore the vast range of titles available.

Double Exposure examines the role of film in shaping social psychology’s landmark postwar experiments. We are told that most of us will inflict electric shocks on a fellow citizen when ordered to do so. Act as a brutal prison guard when we put on a uniform. Walk on by when we see a stranger in need. But there is more to the story. Documentaries that investigators claimed as evidence were central to capturing the public imagination. Did they provide an alibi for twentieth century humanity? Examining the dramaturgy, staging and filming of these experiments, including Milgram's Obedience Experiments, the Stanford Prison Experiment and many more, Double Exposure recovers a new set of narratives.

Research that involves dental pulp stem cells (DPSCs) is growing rapidly. DPSCs can be used for the treatment of craniofacial bone abnormalities and tooth repair. The procedure requires a donation of sound teeth, which might be associated with ethical and moral issues. The purpose of this study was to understand the attitudes and awareness of patients with respect to the donation of their teeth to research. This study involved 500 patients recruited from Dental Care and Dental Teaching Center in Irbid during May 2017-July 2017. A well-structured questionnaire was administered and prepared using Google forms and filled out using a tablet device. The majority of patients (62.8%) were willing to donate their teeth to research with significant association with educational level. Half of the patients considered that the donated tooth belongs to them even after extraction, whereas 19% believed that the researcher owns it after donation. Almost half (53.6%) of the participants wished to be informed about the type of scientific research that will be carried out on their teeth. The majority (66.5%) preferred to sign a consent document on tooth donation to research during the consultation visit before extraction. Finally, about 61% were worried that their tooth might be extracted for research purposes rather than medical purposes. A good fraction of Jordanian is willing to donate their teeth to research. Educational programs are demanded to enhance the awareness and attitudes of patients on the ownership of extracted teeth, consent process, and donation of teeth.

Responsible AI is concerned with the design, implementation and use of ethical, transparent, and accountable AI technology in order to reduce biases, promote fairness, equality, and to help facilitate interpretability and explainability of outcomes, which are particularly pertinent in a healthcare context. However, the extant literature on health AI reveals significant issues regarding each of the areas of responsible AI, posing moral and ethical consequences. This is particularly concerning in a health context where lives are at stake and where there are significant sensitivities that are not as pertinent in other domains outside of health. This calls for a comprehensive analysis of health AI using responsible AI concepts as a structural lens. A systematic literature review supported our data collection and sampling procedure, the corresponding analysis, and extraction of research themes helped us provide an evidence-based foundation. We contribute with a systematic description and explanation of the intellectual structure of Responsible AI in digital health and develop an agenda for future research.

Artificial Intelligence (AI) holds immense potential for revolutionizing medical education and healthcare. Despite its proven benefits, the full integration of AI faces hurdles, with ethical concerns standing out as a key obstacle. Thus, educators should be equipped to address the ethical issues that arise and ensure the seamless integration and sustainability of AI-based interventions. This article presents twelve essential tips for addressing the major ethical concerns in the use of AI in medical education. These include emphasizing transparency, addressing bias, validating content, prioritizing data protection, obtaining informed consent, fostering collaboration, training educators, empowering students, regularly monitoring, establishing accountability, adhering to standard guidelines, and forming an ethics committee to address the issues that arise in the implementation of AI. By adhering to these tips, medical educators and other stakeholders can foster a responsible and ethical integration of AI in medical education, ensuring its long-term success and positive impact.

PurposeDeepfake information poses more ethical risks than traditional disinformation in terms of fraud, slander, rumors and other malicious uses. However, owing to its high entertainment value, deepfake information with ethical risks has become popular. This study aims to understand the role of ethics and entertainment in the acceptance and regulation of deepfake information.Design/methodology/approachMixed methods were used to qualitatively identify ethical concerns and quantitatively evaluate the influence of ethical concerns and perceived enjoyment on the ethical acceptability and social acceptance of deepfake information.FindingsThe authors confirmed that informed consent, privacy protection, traceability and non-deception had a significantly positive impact on ethical acceptability and indirectly influenced social acceptance, with privacy protection being the most sensitive. Perceived enjoyment impacts the social acceptance of deepfake information and significantly weakens the effect of ethical acceptability on social acceptance.Originality/valueThe ethical concerns affecting acceptance behavior identified in this study provide an entry point for the ethical regulation of deepfake information. The weakening effect of perceived enjoyment on ethics serves as a wake-up call for regulators to guard against pan-entertainment deepfake information.

Tissue engineering is an evolving multi-disciplinary field with cutting-edge technologies and innovative scientific perceptions that promise functional regeneration of damaged tissues/organs. Tissue engineered medical products (TEMPs) are biomaterial-cell products or a cell-drug combination which is injected, implanted or topically applied in the course of a therapeutic or diagnostic procedure. Current tissue engineering strategies aim at 3D printing/bioprinting that uses cells and polymers to construct living tissues/organs in a layer-by-layer fashion with high 3D precision. However, unlike conventional drugs or therapeutics, TEMPs and 3D bioprinted tissues are novel therapeutics and need different regulatory protocols for clinical trials and commercialization processes. Therefore, it is essential to understand the complexity of raw materials, cellular components, and manufacturing procedures to establish standards that can help to translate these products from bench to bedside. These complexities are reflected in the regulations and standards that are globally in practice to prevent any compromise or undue risks to patients. This review comprehensively describes the current legislations, standards for TEMPs with a special emphasis on 3D bioprinted tissues. Based on these overviews, challenges in the clinical translation of TEMPs & 3D bioprinted tissues/organs along with their ethical concerns and future perspectives are discussed.

This study situates Malouf within the field of contemporary international and postcolonial writing, but without losing sight of the author's affiliation with Australian contexts. It presents an original reading of Malouf, finding the unity of his work in the continuity of his ethical concerns: for Malouf, human lives find their value in transformations, specifically in instances of self-overcoming that encounters with difference or otherness provoke. However, the book is fully aware of, and informed by, the quite ample body of criticism on Malouf, and thus provides readers with a broad-based understanding of how his works have been received and assessed. It is an effective companion volume for studies in postcolonial or Australian literature.

Artificial intelligence (AI) refers to the theory and development of computer systems capable of performing tasks that normally require human intelligence. This revolutionary technology holds immense potential in multiple domains, including the development of educational curricula. This article has explored the impact of AI on curriculum development in global higher education institutions, analyzing data from 2,000 faculty and student respondents, across five continents: North America, Europe, Asia, Africa, and Latin America, using a logistic regression model. The study found that frequent use of AI, the extent of the faculty knowledge, institution support to faculty, and the future expectation about AI are promoting curriculum development. Furthermore, the effectiveness of AI-driven tools in personalizing learning experiences, enhancing student engagement, identifying and addressing individual needs, providing real-time feedback, improving the quality of teaching and learning materials, and promoting critical thinking and problem-solving skills is driving curriculum development. Moreover, the challenges limiting AI integration in curriculum development include its ability to personalize learning, adapt content based on student needs, ethical concerns, and hesitations in recommending AI use to other educational institutions. Besides, with respect to cultural and educational contexts in AI-powered tools, the integration of AI in global higher education curriculum development is hindered by its inability to align with and navigate the complexities of these contexts. In addition, educators’ and leaders’ perceptions and attitudes also influence AI’s role in curriculum development. Factors such as AI’s ability to create personalized learning experiences, familiarity with current AI tools, its effectiveness in identifying student learning gaps, willingness to undergo training and professional development, and its capacity to address biases in curriculum content stimulate development yet also present limitations. Importantly, our findings indicate that, while AI has enormous potential to revolutionize curriculum development, strategic approaches and policies are required to overcome the identified issues and improve AI integration in varied educational settings.

Background Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses’ perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration. Method A qualitative research approach was employed, involving semi-structured interviews with 25 nurses and 3 focus group discussions, each consisting of 7–8 participants. The data collected was coded and analyzed using thematic analysis to identify recurring patterns and key themes in the nurses’ views on AI. Results Three major themes emerged from the analysis: (1) AI as an efficiency tool – Nurses recognized AI’s ability to reduce administrative burdens and improve patient monitoring in real-time. (2) Ethical and practical concerns – Nurses raised issues regarding patient privacy, data security, and the fear that AI might replace human decision-making in care. (3) Lack of preparedness and training – There was a consensus on nurses’ inadequate training in AI tools, limiting their ability to integrate AI into their practice fully. Conclusion While AI is seen as a valuable tool to enhance nursing productivity, several challenges still need to be addressed, particularly regarding ethical concerns and insufficient training. To ensure AI complements nursing without compromising the human element, healthcare institutions must address these issues by implementing comprehensive training programs and establishing clear ethical guidelines.

This paper systematically reviews the impact of Generative Artificial Intelligence (GenAI) in education from 2021 to 2024. The objective is to explore key trends, geographical distribution of research, and emerging themes in the educational use of GenAI, while addressing ethical challenges such as algorithmic bias, data privacy, and the digital divide. Using a systematic review methodology guided by four research questions, the study analyzes publications in Scopus to identify dominant research themes and leading countries in the field. Results indicate that the United States, the United Kingdom, and Singapore are the top contributors to GenAI research, with a primary focus on personalized learning and automated assessments. The review highlights a surge in publications, particularly in 2023, driven by advancements in AI tools like ChatGPT. It emphasizes the importance of international collaboration and proposes the need for regulatory frameworks to ensure the ethical integration of AI in education. This review offers valuable insights into the current state of GenAI research in education and provides recommendations for educators, policymakers, and researchers to navigate the challenges and opportunities of AI-driven learning.