This repository contains de-identified evaluation data collected as part of the Ethical Considerations of Data: A Curriculum for Health Sciences Librarians pilot as well as the data collection instrument used.

These files are related to a forthcoming JMLA Case Study titled Engaging Health Sciences Librarians on Data Ethics: Case Study on a Pilot Curriculum.

Paper Abstract:
Three medical librarians developed a pilot curriculum designed to address perceived gaps in librarian training in regards to data ethics. One of the team members had additional academic training in ethics and bioethics, which helped to provide an intellectual foundation for this project. Our three-module class aimed to provide students with an overview of major ethical frameworks, skills to apply those frameworks to data issues, and an exploration of ethical considerations and challenges faced in libraries. Participants from library schools and professional library organizations were invited to apply. Twenty-four LIS professionals and students attended the Zoom-based class and shared their thoughts and attitudes by means of a survey after each session and in a focus group after the conclusion of the class.

A guide to support ethics deliberation and decision-making in the public health response to the COVID-19 pandemic, including the various transition phases that will occur over the course of the pandemic.

Ethical Data ManagementExecutive SummaryIn the age of data and information, it is imperative that the City of Virginia Beach strategically utilize its data assets. Through expanding data access, improving quality, maintaining pace with advanced technologies, and strengthening capabilities, IT will ensure that the city remains at the forefront of digital transformation and innovation. The Data and Information Management team works under the purpose:“To promote a data-driven culture at all levels of the decision making process by supporting and enabling business capabilities with relevant and accurate information that can be accessed securely anytime, anywhere, and from any platform.”To fulfill this mission, IT will implement and utilize new and advanced technologies, enhanced data management and infrastructure, and will expand internal capabilities and regional collaboration.Introduction and JustificationThe Information technology (IT) department’s resources are integral features of the social, political and economic welfare of the City of Virginia Beach residents. In regard to local administration, the IT department makes it possible for the Data and Information Management Team to provide the general public with high-quality services, generate and disseminate knowledge, and facilitate growth through improved productivity.For the Data and Information Management Team, it is important to maximize the quality and security of the City’s data; to develop and apply the coherent management of information resources and management policies that aim to keep the general public constantly informed, protect their rights as subjects, improve the productivity, efficiency, effectiveness and public return of its projects and to promote responsible innovation. Furthermore, as technology evolves, it is important for public institutions to manage their information systems in such a way as to identify and minimize the security and privacy risks associated with the new capacities of those systems.The responsible and ethical use of data strategy is part of the City’s Master Technology Plan 2.0 (MTP), which establishes the roadmap designed by improve data and information accessibility, quality, and capabilities throughout the entire City. The strategy is being put into practice in the shape of a plan that involves various programs. Although these programs was specifically conceived as a conceptual framework for achieving a cultural change in terms of the public perception of data, it basically covers all the aspects of the MTP that concern data, and in particular the open-data and data-commons strategies, data-driven projects, with the aim of providing better urban services and interoperability based on metadata schemes and open-data formats, permanent access and data use and reuse, with the minimum possible legal, economic and technological barriers within current legislation.Fundamental valuesThe City of Virginia Beach’s data is a strategic asset and a valuable resource that enables our local government carry out its mission and its programs effectively. Appropriate access to municipal data significantly improves the value of the information and the return on the investment involved in generating it. In accordance with the Master Technology Plan 2.0 and its emphasis on public innovation, the digital economy and empowering city residents, this data-management strategy is based on the following considerations.Within this context, this new management and use of data has to respect and comply with the essential values applicable to data. For the Data and Information Team, these values are:Shared municipal knowledge. Municipal data, in its broadest sense, has a significant social dimension and provides the general public with past, present and future knowledge concerning the government, the city, society, the economy and the environment.The strategic value of data. The team must manage data as a strategic value, with an innovative vision, in order to turn it into an intellectual asset for the organization.Geared towards results. Municipal data is also a means of ensuring the administration’s accountability and transparency, for managing services and investments and for maintaining and improving the performance of the economy, wealth and the general public’s well-being.Data as a common asset. City residents and the common good have to be the central focus of the City of Virginia Beach’s plans and technological platforms. Data is a source of wealth that empowers people who have access to it. Making it possible for city residents to control the data, minimizing the digital gap and preventing discriminatory or unethical practices is the essence of municipal technological sovereignty.Transparency and interoperability. Public institutions must be open, transparent and responsible towards the general public. Promoting openness and interoperability, subject to technical and legal requirements, increases the efficiency of operations, reduces costs, improves services, supports needs and increases public access to valuable municipal information. In this way, it also promotes public participation in government.Reuse and open-source licenses. Making municipal information accessible, usable by everyone by default, without having to ask for prior permission, and analyzable by anyone who wishes to do so can foster entrepreneurship, social and digital innovation, jobs and excellence in scientific research, as well as improving the lives of Virginia Beach residents and making a significant contribution to the city’s stability and prosperity.Quality and security. The city government must take firm steps to ensure and maximize the quality, objectivity, usefulness, integrity and security of municipal information before disclosing it, and maintain processes to effectuate requests for amendments to the publicly-available information.Responsible organization. Adding value to the data and turning it into an asset, with the aim of promoting accountability and citizens’ rights, requires new actions, new integrated procedures, so that the new platforms can grow in an organic, transparent and cross-departmental way. A comprehensive governance strategy makes it possible to promote this revision and avoid redundancies, increased costs, inefficiency and bad practices.Care throughout the data’s life cycle. Paying attention to the management of municipal registers, from when they are created to when they are destroyed or preserved, is an essential part of data management and of promoting public responsibility. Being careful with the data throughout its life cycle combined with activities that ensure continued access to digital materials for as long as necessary, help with the analytic exploitation of the data, but also with the responsible protection of historic municipal government registers and safeguarding the economic and legal rights of the municipal government and the city’s residents.Privacy “by design”. Protecting privacy is of maximum importance. The Data and Information Management Team has to consider and protect individual and collective privacy during the data life cycle, systematically and verifiably, as specified in the general regulation for data protection.Security. Municipal information is a strategic asset subject to risks, and it has to be managed in such a way as to minimize those risks. This includes privacy, data protection, algorithmic discrimination and cybersecurity risks that must be specifically established, promoting ethical and responsible data architecture, techniques for improving privacy and evaluating the social effects. Although security and privacy are two separate, independent fields, they are closely related, and it is essential for the units to take a coordinated approach in order to identify and manage cybersecurity and risks to privacy with applicable requirements and standards.Open Source. It is obligatory for the Data and Information Management Team to maintain its Open Data- Open Source platform. The platform allows citizens to access open data from multiple cities in a central location, regional universities and colleges to foster continuous education, and aids in the development of data analytics skills for citizens. Continuing to uphold the Open Source platform with allow the City to continually offer citizens the ability to provide valuable input on the structure and availability of its data. Strategic areasIn order to deploy the strategy for the responsible and ethical use of data, the following areas of action have been established, which we will detail below, together with the actions and emblematic projects associated with them.In general, the strategy pivots on the following general principals, which form the basis for the strategic areas described in this section.Data sovereigntyOpen data and transparencyThe exchange and reuse of dataPolitical decision-making informed by dataThe life cycle of data and continual or permanent accessData GovernanceData quality and accessibility are crucial for meaningful data analysis, and must be ensured through the implementation of data governance. IT will establish a Data Governance Board, a collaborative organizational capability made up of the city’s data and analytics champions, who will work together to develop policies and practices to treat and use data as a strategic asset.Data governance is the overall management of the availability, usability, integrity and security of data used in the city. Increased data quality will positively impact overall trust in data, resulting in increased use and adoption. The ownership, accessibility, security, and quality, of the data is defined and maintained by the Data Governance Board.To improve operational efficiency, an enterprise-wide data catalog will be created to inventory data and track metadata from various data sources to allow for rapid data asset discovery. Through the data catalog, the city will

Abstract The challenge of curbing corruption requires public organizations to implement ethics management, deploying a myriad of instruments to reinforce ethical frameworks of public employees. Ethical training is among the most used instruments to achieve this goal, which should provide elements to public officials to face ethical dilemmas effectively. Yet, is that the case? How efficient are ethical training efforts for public servants? Do they have the same effect among different types of employees? In order to answer these questions, this article shows the results of pre and post-test questionnaires applied to participants of ethics training workshops for employees in the central and local government in Chile. The exploratory findings show that after the workshops, it is possible to see an improvement in the ethical frameworks among participants, showing a positive effect for women and those who recently started working in the public sector. More research is required to improve the instrument and strengthen public integrity. The article concludes with proposals to improve these kinds of training activities.

This dataset is about book subjects and is filtered where the books is Evolutions in corporate governance : towards an ethical framework for business conduct, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

BackgroundThe COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.Materials and methodsThe study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.Results and conclusionIn total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

As large language models (LLMs) have become more deeply integrated into various sectors, understanding how they make moral judgements has become crucial, particularly in the realm of autonomous driving. This study used the moral machine framework to investigate the ethical decision-making tendencies of prominent LLMs, including GPT-3.5, GPT-4, PaLM 2 and Llama 2, to compare their responses with human preferences. While LLMs' and humans' preferences such as prioritizing humans over pets and favouring saving more lives are broadly aligned, PaLM 2 and Llama 2, especially, evidence distinct deviations. Additionally, despite the qualitative similarities between the LLM and human preferences, there are significant quantitative disparities, suggesting that LLMs might lean toward more uncompromising decisions, compared with the milder inclinations of humans. These insights elucidate the ethical frameworks of LLMs and their potential implications for autonomous driving., Using the MM methodology detailed in the supplementary information of https://www.nature.com/articles/s41586-018-0637-6, we implemented code for generating Moral Machine scenarios. After generating the MM scenarios, responses from GPT-3.5, GPT-4, PaLM 2, and Llama 2 were collected using the application programming interface (API) and relevant code. We applied the conjoint analysis framework to evaluate the relative importance of the nine preferences., , # Data and Code on the Moral Machine Experiment on Large Language Models

https://doi.org/10.5061/dryad.d7wm37q6v

Requirements

• Python 3.9

pip install -r requirements.txt

NOTE: The script run_chatgpt.py requires an OpenAI API key. Please obtain your API key by following OpenAI's instructions. To run the script run_palm2.py, setup is required. Please refer to the Google Cloud instructions. Specifically, follow these sections in the given order: 1) Set up a project and a development environment and 2) Install the Vertex AI SDK for Python. Before running run_llama2.py, the Llama2 model files must be downloaded. Please follow [the instructi...

Supplemental Figures for JAAD Manuscript "An Ethical Framework for Managing Neglected Skin Tumors in Older Patients."

During health emergencies such as the COVID-19 pandemic, healthcare workers face numerous ethical challenges while catering to the needs of patients in healthcare settings. Although the data recapitulating high-income countries ethics frameworks are available, the challenges faced by clinicians in resource-limited settings of low- and middle-income countries are not discussed widely due to a lack of baseline data or evidence. The Nepali healthcare system, which is chronically understaffed and underequipped, was severely affected by the COVID-19 pandemic in its capacity to manage health services and resources for needy patients, leading to ethical dilemmas and challenges during clinical practice. This study aimed to develop a standard guideline that would address syndemic ethical dilemmas during clinical care of COVID-19 patients who are unable to afford standard-of-care. A mixed method study was conducted between February and June of 2021 in 12 government designated COVID-19 treatment hospitals in central Nepal. The draft guideline was discussed among the key stakeholders in the pandemic response in Nepal. The major ethical dilemmas confronted by the study participants (50 healthcare professionals providing patient care at COVID-19 treatment hospitals) could be grouped into five major pillars of ethical clinical practice: rational allocation of medical resources, updated treatment protocols that guide clinical decisions, standard-of-care regardless of patient's economic status, effective communication among stakeholders for prompt patient care, and external factors such as political and bureaucratic interference affecting ethical practice. This living clinical ethics guideline, which has been developed based on the local evidence and case stories of frontline responders, is expected to inform the policymakers as well as the decision-makers positioned at the concerned government units. These ethics guidelines could be endorsed with revisions by the concerned regulatory authorities for the use during consequent waves of COVID-19 and other epidemics that may occur in the future. Other countries affected by the pandemic could conduct similar studies to explore ethical practices in the local clinical and public health context.

Transcripts of in-depth interviews and group discussions with managers, researchers, ethics committee members, field data collectors and community members on the issues around ethical data sharing in the context of research involving women and children in urban India. We interviewed researchers, managers, and research participants associated with a Mumbai non-governmental organization, as well as researchers from other organizations and members of ethics committees. We conducted 22 individual semi-structured interviews and involved 44 research participants in focus group discussions. We used framework analysis to examine ideas about data and data sharing in general; its potential benefits or harms, barriers, obligations, and governance; and the requirements for consent. Both researchers and participants were generally in favor of data sharing, although limited experience amplified their reservations.

It is increasingly recognized that effective and appropriate data sharing requires the development of models of good data sharing practice capable of taking seriously both the potential benefits to be gained and the importance of ensuring that the rights and interests of participants are respected and that risk of harms is minimized. Calls for the greater sharing of individual level data from biomedical and public health research are receiving support among researchers and research funders. Despite its potential importance, data sharing presents important ethical, social, and institutional challenges in low income settings. This dataset comprises qualitative research conducted in India, exploring the experiences of key research stakeholders and their views about what constitutes good data sharing practice.

BackgroundThe COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.Materials and methodsThe study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.Results and conclusionIn total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

Artificial intelligence is being increasingly utilized in higher education learning environments, including algorithmic writing technologies such as text generation, real time captioning, and machine translation. One aspect of these technologies yet to be considered is their ethical implications with regards to teaching and learning. In this project, we work at the vanguard of artificial intelligence learning technologies with a Universal Design for Learning framework. The primary question that guides this research is: What are the ethical implications of artificial intelligence technologies for teaching, learning, and assessment? Our research a mixed methods study, comprised of a modified Turing-test scenario within a survey as well as qualitative interviews. Having knowledge about the capabilities and ethical implications of artificial intelligence technologies will help educators develop ethical and accessible teaching practices to benefit student learning outcomes.

Social data in digital form—including user-generated content, expressed or implicit relations between people, and behavioral traces—are at the core of popular applications and platforms, driving the research agenda of many researchers. The promises of social data are many, including understanding “what the world thinks” about a social issue, brand, celebrity, or other entity, as well as enabling better decision-making in a variety of fields including public policy, healthcare, and economics. Many academics and practitioners have warned against the naïve usage of social data. There are biases and inaccuracies occurring at the source of the data, but also introduced during processing. There are methodological limitations and pitfalls, as well as ethical boundaries and unexpected consequences that are often overlooked. This paper recognizes the rigor with which these issues are addressed by different researchers varies across a wide range. We identify a variety of menaces in the practices around social data use, and organize them in a framework that helps to identify them.“For your own sanity, you have to remember that not all problems can be solved. Not all problems can be solved, but all problems can be illuminated.” –Ursula Franklin1

Values, ethics, and health care : frameworks for reasoning, reflection, and debate is a book. It was written by Peter Duncan and published by SAGE Publications Ltd in 2009.

Current research ethics frameworks were developed on the footprint of biomedical, experimental research and present several pitfalls when applied to non-experimental social sciences. This work explores how the normative principles underpinning policy and regulatory frameworks of research ethics and the related operational processes work in practice in the context of collaborative health and social care research. The work was organised in three phases. First, UK research ethics policy documents were analysed thematically, with themes further organised under the categories of ‘Principles’ and ‘Processes’. Next, we conducted a scoping review of articles about research ethics in the context of collaborative health and social care research, published in English between 2010 and 2022. We then held an exploratory focus group with ten academic researchers with relevant experience to gather their views on how the research ethics system works in practice in England (UK). The thematic framework developed in the first phase supported the analysis of the articles included in the scoping review and of focus group data. The analysis of policy documents identified twelve themes. All were associated to both a principle and a related operational process. The scoping review identified 31 articles. Across these, some themes were barely acknowledged (e.g., Compliance with legislation). Other themes were extensively covered (e.g., The working of Research Ethics Committees), often to discuss issues and limitations in how, in practice, the research ethics system and its processes deal with collaborative research and to suggest options for improvement. Focus group data were largely consistent with the findings of the scoping review. This work provides evidence of the poor alignment between how the research ethics system is normatively expected to work and how it works in practice and offers options that could make research ethics more fit for purpose when addressing collaborative research in health and social care.

The Artificial Intelligence (AI) Advisory Committee provides expertise, guidance, and advice on ethical considerations required to advance the implementation of AI within the Government of Canada’s HR and Pay modernization project. The Committee's responsibilities include advising on ethical AI implementation, emerging trends, risks, policies, and mitigations. It will contribute to the development of the AI Strategy and Ethics Review Framework within the Human Capital Management (HCM) branch of Public Services and Procurement Canada (PSPC) and offer strategic advice on specific projects and procurement processes. The Committee, chaired by Associate Deputy Minister of HCM-PSPC, is comprised of international and interdisciplinary experts from across industry, academia, civil society and international organizations. Members are selected based on their experience, AI expertise, partnerships, and regional representation. The Committee will meet quarterly.

Market Overview:

United States AI governance market size is projected to exhibit a growth rate (CAGR) of 29.29% during 2024-2032. The growing demand for multifaceted processes, including certification, auditing, impact assessments, among organizations and the integration of public consultation mechanisms are primarily driving the market growth across the country.

Report Attribute	Key Statistics
Base Year	2023
Forecast Years	2024-2032
Historical Years	2018-2023
Market Growth Rate (2024-2032)	29.29%

AI Governance involves the formulation of policies, regulations, and procedures governing the development, deployment, and utilization of artificial intelligence technologies, with a particular emphasis on their societal implications, privacy considerations, fairness, accountability, and safety. This framework is characterized by principles such as transparency and non-discrimination, giving priority to safeguarding personal data and privacy rights. The structure of AI governance encompasses certification processes, auditing mechanisms, impact assessments, and the inclusion of public consultation. These measures can be effectively implemented through collaborative efforts involving governments, regulatory bodies, and civil society organizations. Consequently, AI governance finds application across diverse sectors such as healthcare, finance, and autonomous vehicles, aiming to ensure the ethical deployment of AI and uphold safety and reliability in systems based on artificial intelligence.

United States AI Governance Market Trends:

The United States AI governance market stands at the forefront of shaping responsible and ethical practices in the development and deployment of artificial intelligence technologies. This burgeoning sector is dedicated to formulating policies, regulations, and frameworks that guide the ethical use of AI, with a focal point on societal impact, privacy protection, fairness, accountability, and safety. Additionally, the framework emphasizes principles like transparency and non-discrimination while prioritizing the safeguarding of personal data and privacy rights, thereby augmenting the market growth. Besides this, the collaborative efforts of government entities, regulatory bodies, and civil society organizations drive the implementation of these measures, which is acting as another significant growth-inducing factor. Moreover, the application of AI governance extends across critical sectors such as healthcare, finance, and autonomous vehicles, ensuring that AI technologies are harnessed responsibly to uphold safety and reliability. As the adoption of the technology continues to accelerate, the United States AI governance market will play a pivotal role in establishing a framework that fosters trust, ethical considerations, and accountability over the forecasted period.

United States AI Governance Market Segmentation: -

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for 2024-2032. Our report has categorized the market based on component, deployment mode, enterprise size, and industry vertical.

Component Insights:

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• Solution
• Services
  

The report has provided a detailed breakup and analysis of the market based on the component. This includes solution and services.

Deployment Mode Insights:

• On-premises
• Cloud-based
  

A detailed breakup and analysis of the market based on the deployment mode have also been provided in the report. This includes on-premises and cloud-based.

Enterprise Size Insights:

• Large Enterprises
• Small and Medium-sized Enterprises (SMEs)
  

The report has provided a detailed breakup and analysis of the market based on the enterprise size. This includes large enterprises and small and medium-sized enterprises (SMES).

Industry Vertical Insights:

• BFSI
• Government and Defense
• Healthcare and Life Sciences
• Media and Entertainment
• Retail
• IT and Telecom
• Automotive
• Others
  

A detailed breakup and analysis of the market based on the industry vertical have also been provided in the report. This includes BFSI, government and defense, healthcare and life sciences, media and entertainment, retail, IT and telecom, automotive, and others.

Regional Insights:

https://www.imarcgroup.com/CKEditor/ad6c8c6d-340f-40db-8262-1ff1c9fd003cunited-states-ai-governance-market-regional.webp" style="height:450px; width:800px" />

• Northeast
• Midwest
• South
• West
  

The report has also provided a comprehensive analysis of all the major regional markets, which include Northeast, Midwest, South, and West.

Competitive Landscape:

The market research report has also provided a comprehensive analysis of the competitive landscape in the market. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

United States AI Governance Market Report Coverage:

Report Features	Details
Base Year of the Analysis	2023
Historical Period	2018-2023
Forecast Period	2024-2032
Units	US$ Million
Scope of the Report	Exploration of Historical Trends and Market Outlook, Industry Catalysts and Challenges, Segment-Wise Historical and Future Market Assessment: Component Deployment Mode Enterprise Size Industry Vertical Region
Components Covered	Solution, Services
Deployment Modes Covered	On-premises, Cloud-based
Enterprise Sizes Covered	Large Enterprises, Small and Medium-sized Enterprises (SMEs)
Industry Verticals Covered	BFSI, Government and Defense, Healthcare and Life Sciences, Media and Entertainment, Retail, IT and Telecom, Automotive, Others
Regions Covered	Northeast, Midwest, South, West
Customization Scope	10% Free Customization
Report Price and Purchase Option	Single User License: US$ 3699 Five User License: US$ 4699 Corporate License: US$ 5699
Post-Sale Analyst Support	10-12 Weeks
Delivery Format	PDF

Rachmad, Yoesoep Edhie. 2022. Future Frames: The Intersection of Artifical Intelligence and Cinematic Techniques. Digiworld Professional Yearbook Publishing, Special Issue 2022.

"Future Frames: The Intersection of Artificial Intelligence and Cinematic Techniques" by Yoesoep Edhie Rachmad was published in 2022 by Digiworld Professional Yearbook Publishing, as a special issue. The book aims to explore the transformative impact of artificial intelligence (AI) on the cinematic world, examining how AI technologies are reshaping film production, editing, storytelling, and viewer experiences. Rachmad's deep interest in the fusion of AI and film led him to investigate the potential and challenges of integrating these advanced technologies into the cinematic process. Definition and Basic Concepts: The book begins by introducing readers to the fundamental concepts of AI and its role in cinematography. It discusses how AI has started to revolutionize various aspects of film production, from automating routine tasks to enhancing storytelling techniques. Rachmad explains the basics of AI, its evolution, and its potential to bring about significant changes in the film industry. Underlying Phenomena: Rachmad identifies the phenomena driving the adoption of AI in filmmaking. He highlights AI's ability to enhance creativity, improve efficiency, and offer new storytelling possibilities. The book discusses the rapid advancements in AI technology, such as machine learning and computer vision, which are enabling more sophisticated applications in the film industry. Problem Formulation: The book addresses the challenges and opportunities presented by AI in cinematography. Key problems include the technical complexities of integrating AI into film production, the need for new creative paradigms, and the ethical considerations surrounding AI use in filmmaking. Rachmad formulates these issues to explore how filmmakers can effectively leverage AI while navigating these challenges. Research Objectives: Rachmad's primary objective is to provide a comprehensive guide to the integration of AI in cinematic techniques. He aims to identify the tools and technologies that can enhance the filmmaking process, explore the ethical implications of AI, and predict future trends in AI-driven cinema. The book seeks to equip filmmakers with the knowledge and skills needed to utilize AI for creating innovative and impactful films. Indicators: Key indicators in the book include the effectiveness of AI tools in film production, the quality of films created with AI assistance, the ethical standards maintained in AI applications, and the engagement levels of viewers with AI-enhanced films. These indicators help measure the success and impact of AI integration in cinematography. Operational Variables: The operational variables discussed in the book include the specific AI hardware and software used in film production, the types of cinematic content created with AI, the collaboration between human filmmakers and AI, and the ethical frameworks guiding AI use in filmmaking. These variables are essential for understanding the practical aspects of working with AI in cinema. Determinant Factors of the Theory: Rachmad identifies several factors that determine the successful integration of AI into cinematography. These include advancements in AI technology, the adaptability of filmmakers to new tools and methods, the availability of resources for AI projects, and ongoing research into the ethics and usability of AI in film. Implementation and Strategy: The book outlines strategies for implementing AI in film production. These strategies involve training filmmakers to use AI tools effectively, fostering collaboration between technologists and creatives, and developing ethical guidelines for AI applications in filmmaking. Rachmad emphasizes the importance of staying informed about technological advancements and continuously refining cinematic practices to keep pace with the evolving AI landscape. Supporting and Inhibiting Challenges: Rachmad discusses both the support and obstacles in implementing AI in cinematography. Supportive factors include the rapid advancement of AI technology, the growing interest in AI among filmmakers, and the potential for AI to revolutionize creative practices. However, challenges such as the loss of traditional creative jobs, data privacy concerns, and the potential for bias in AI-generated narratives are also addressed. Research Findings: The book presents research findings that demonstrate the potential of AI to enhance filmmaking. Case studies and examples illustrate how AI can facilitate faster, more efficient film production, improve editing processes, and create personalized viewing experiences. The findings also highlight the importance of addressing ethical considerations to ensure responsible use of AI in cinema. Conclusion and Recommendations: In conclusion, Rachmad argues that AI is not just a supplementary tool but an essential component that can redefine cinema. He encourages filmmakers to embrace AI as a partner in creativity, capable of enhancing narrative quality and production efficiency. The book recommends continuous learning and adaptation as AI technologies evolve. By adopting these practices, filmmakers can harness the full potential of AI to create innovative, impactful films. "Future Frames: The Intersection of Artificial Intelligence and Cinematic Techniques" offers a comprehensive exploration of how AI is transforming the cinematic landscape, providing valuable insights and guidance for filmmakers looking to navigate and utilize these advanced technologies.

Bab 1: AI dalam Dunia Sinematografi Bab pertama ini akan mengenalkan pembaca pada dasar-dasar kecerdasan buatan (AI) dan peranannya dalam industri film. Akan dibahas bagaimana AI telah mulai mengubah proses produksi, pengeditan, dan bahkan penceritaan dalam film. Bab 2: Alat dan Teknologi Berbasis AI Di bab kedua, akan dijelaskan berbagai alat dan teknologi AI yang spesifik digunakan dalam pembuatan film. Dari perangkat lunak yang dapat mengedit film secara otomatis hingga algoritma yang dapat menganimasikan karakter, bab ini akan memberikan wawasan mendalam tentang perkembangan teknologi ini. Bab 3: AI dan Sutradara Bab ini menggali peran AI sebagai asisten sutradara, dengan fokus pada bagaimana AI dapat membantu dalam memilih shot, mengatur pencahayaan, dan bahkan memberikan saran untuk peningkatan naskah. Akan dibahas juga tentang kolaborasi antara sutradara manusia dan AI dalam menciptakan karya film. Bab 4: AI dalam Penyuntingan dan Pasca Produksi Bab keempat ini mengeksplorasi penggunaan AI dalam penyuntingan film, termasuk bagaimana AI dapat secara otomatis memilih take terbaik, menyinkronkan audio dengan video, dan menerapkan efek visual. Teknik-teknik ini akan dijelaskan beserta contoh-contoh spesifik dari industri. Bab 5: AI dan Personalisasi Pengalaman Menonton Di bab ini, akan dibahas inovasi dalam cara film disajikan kepada penonton, dengan menggunakan AI untuk menyesuaikan pengalaman menonton berdasarkan preferensi individu. Ini mencakup variabel seperti mengubah plot berdasarkan reaksi penonton atau memilih akhir cerita yang berbeda. Bab 6: Implikasi Etis dan Sosial Bab ini membahas tantangan etis dan sosial yang muncul dari integrasi AI dalam sinematografi. Isu-isu seperti kehilangan pekerjaan kreatif, privasi penonton, dan potensi bias dalam narasi yang dikembangkan oleh AI akan dijelajahi. Bab 7: Masa Depan Sinematografi dengan AI Bab terakhir ini merenungkan masa depan industri film dengan adanya integrasi AI yang semakin mendalam. Akan dijelajahi bagaimana AI mungkin mengubah peran tradisional dalam pembuatan film dan apa artinya bagi masa depan sinema. Kesimpulan: Meredefinisi Sinema Melalui AI Kesimpulan buku ini menekankan bagaimana AI tidak hanya mengubah cara film dibuat, tetapi juga bagaimana mereka diceritakan dan dialami oleh penonton. Dengan memanfaatkan AI, pembuat film dapat membuka kreativitas baru dan meningkatkan kualitas naratif film. Buku ini mengajak pembaca untuk memahami dan menerima perubahan ini sebagai evolusi alami dari teknologi dalam sinema. Buku "Future Frames: The Intersection of AI and Cinematic Techniques" memberikan pandangan komprehensif terhadap perubahan revolusioner yang dibawa oleh AI dalam dunia sinematografi, menunjukkan potensi dan tantangan yang datang dengan evolusi ini.

A tendency for people to rate themselves as ‘more moral’ than the ‘average person’ – known as the Moral Superiority Bias (MSB) – is a common characteristic of members in extremist political groups, and thus may contribute to political and social hostility. Despite this, the factors underpinning individual differences in MSB are not yet known. Identifying links between MSB and more established bodies of literature in moral psychology, such as individual differences between people who make utilitarian vs. deontologically-guided ethical decisions, may provide further insight into MSB. Eighty-nine (19 male, 70 female) 1st-year Psychology students from [institution name redacted] completed measures of MSB and ethical decision-making style. Correlational analyses revealed that participants whose moral decision making was more strongly guided by utilitarian arguments exhibited lower levels of MSB. Participants who scored highly in deontological moral thinking did not display higher levels of MSB, but did show low self-ratings of moral character. The findings suggest that moral framework is not a relevant factor for understanding the MSB seen in extremist political groups. Other potential avenues of research towards building our understanding of MSB are discussed.

Rachmad, Yoesoep Edhie. 2022. Digital Dominion: Artifical Intelligence Innovations in National Governance. Energy Informatics Book Publishing, Heidelberg Special Issue 2022. https://doi.org/10.17605/osf.io/axtsg

"Digital Dominion: Artificial Intelligence Innovations in National Governance" by Yoesoep Edhie Rachmad was published in 2022 by Energy Informatics Book Publishing in Heidelberg as a special issue. The book explores how artificial intelligence (AI) innovations are transforming national governance, examining the potential and challenges of integrating AI into government operations. Rachmad's interest in the intersection of technology and public administration drives his investigation into how AI can revolutionize national governance. Definition and Basic Concepts: The book begins with an introduction to the basics of artificial intelligence (AI) and its importance in transforming national governance. It provides an overview of the evolution of AI, the technologies involved, and their potential impact on public administration. This foundational knowledge sets the stage for understanding how AI can enhance government operations and citizen engagement. Underlying Phenomena: Rachmad explores the phenomena driving the adoption of AI in national governance. He highlights the increasing need for data-driven decision-making, enhanced operational efficiency, and proactive threat identification. The book discusses how AI can address these needs by automating processes, analyzing large datasets, and providing more accurate and timely insights. Problem Formulation: The book addresses the challenges and opportunities presented by integrating AI into national governance. Key problems include the technical complexities, ethical considerations, and the need for strong regulatory frameworks. Rachmad formulates these issues to explore how governments can effectively incorporate AI while managing these challenges. Research Objectives: Rachmad's primary objective is to provide a comprehensive guide to integrating AI into national governance. He aims to identify the tools and techniques that enhance government operations, explore the ethical implications, and predict future trends. The book seeks to equip public administrators with the knowledge and skills needed to utilize AI for creating more efficient and transparent government services. Indicators: Key indicators in the book include the effectiveness of AI in improving operational efficiency, the quality of AI-driven policy formulation, the enhancement of national security through AI applications, and the transparency and accountability achieved through AI integration. These indicators help measure the success and impact of AI innovations in national governance. Operational Variables: The operational variables discussed in the book include the specific AI hardware and software used in government operations, the types of tasks automated or enhanced by AI, the interaction between AI systems and human decision-makers, and the regulatory frameworks guiding AI use in governance. These variables are essential for understanding the practical aspects of integrating AI into public administration. Determinant Factors of the Theory: Rachmad identifies several factors that determine the successful integration of AI into national governance. These include advancements in AI technology, the adaptability of public administrators to new tools, the availability of resources for AI projects, and ongoing research into the ethics and usability of AI in governance. Implementation and Strategy: The book outlines strategies for implementing AI in national governance. These strategies involve training public administrators to use AI tools effectively, fostering collaboration between technologists and government officials, and developing regulatory guidelines for AI applications. Rachmad emphasizes the importance of staying informed about technological advancements and continuously refining governance practices to keep pace with the evolving AI landscape. Supporting and Inhibiting Challenges: Rachmad discusses both the support and obstacles in implementing AI in national governance. Supportive factors include rapid technological advancements, growing interest in data-driven governance, and the potential for AI to enhance public services. However, challenges such as data privacy concerns, ethical issues, and the need for robust regulatory frameworks are also addressed. Research Findings: The book presents research findings that demonstrate the potential of AI to enhance national governance. Case studies and examples illustrate how AI can improve operational efficiency, policy formulation, and national security. The findings also highlight the importance of addressing ethical and regulatory challenges to ensure responsible use of AI in governance. Conclusion and Recommendations: In conclusion, Rachmad argues that AI offers significant opportunities to improve national governance despite existing challenges. He emphasizes that the successful integration of AI depends not only on the technology itself but also on how governments manage ethical, regulatory, and social aspects. The book recommends continuous learning and collaboration between technologists, policymakers, and civil society to maximize the benefits of AI while minimizing its risks. "Digital Dominion: Artificial Intelligence Innovations in National Governance" provides a comprehensive exploration of how AI is transforming national governance, offering valuable insights and guidance for public administrators looking to navigate and utilize these advanced technologies.

Bab 1: Pengenalan AI dan Tata Kelola Nasional Bab ini membahas dasar-dasar Kecerdasan Buatan (AI) dan pentingnya dalam mengubah tata kelola di tingkat nasional. Bab ini menjelaskan evolusi AI, teknologi yang terlibat, dan dampak potensialnya terhadap administrasi publik. Bab 2: AI dalam Peningkatan Efisiensi Pemerintahan Menguraikan bagaimana AI dapat meningkatkan efisiensi operasional melalui otomatisasi proses dan pengambilan keputusan yang lebih akurat dan cepat. Contoh dari berbagai negara yang telah mengadopsi teknologi ini akan diberikan untuk menunjukkan praktik terbaik. Bab 3: AI dan Kebijakan Publik Bab ini menjelaskan peran AI dalam membentuk kebijakan publik yang lebih responsif dan berbasis data. Dengan menggunakan AI, pemerintah dapat mengidentifikasi tren dan pola dalam data besar untuk membuat kebijakan yang lebih tepat sasaran dan efektif. Bab 4: Keamanan Nasional dan AI Membahas aplikasi AI dalam keamanan nasional, termasuk pengawasan, intelijen, dan pertahanan. Pentingnya AI dalam mengidentifikasi ancaman dan merespons secara proaktif akan ditekankan. Bab 5: AI, Transparansi, dan Akuntabilitas Bab ini menjelaskan bagaimana AI dapat meningkatkan transparansi dan akuntabilitas dalam pemerintahan dengan membuat proses dan keputusan lebih terbuka dan dapat diakses oleh publik. Ini termasuk penggunaan AI untuk memerangi korupsi dan meningkatkan pelayanan publik. Bab 6: Etika, Privasi, dan Regulasi AI Menganalisis tantangan etis dan privasi yang dihadapi dalam implementasi AI di pemerintahan. Bab ini juga akan membahas kebutuhan akan regulasi yang kuat untuk memastikan bahwa penggunaan AI tidak melanggar hak-hak individu. Bab 7: Kasus Studi Internasional Menyajikan studi kasus dari berbagai negara mengenai penerapan AI dalam tata kelola nasional, menyoroti tantangan, keberhasilan, dan pelajaran yang bisa dipetik dari setiap kasus. Bab 8: Masa Depan AI dalam Tata Kelola Nasional Meramalkan masa depan interaksi antara AI dan tata kelola nasional, dengan mempertimbangkan perkembangan teknologi terkini dan tren yang mungkin mempengaruhi penggunaannya dalam administrasi publik. Kesimpulan Bab kesimpulan menegaskan bahwa meskipun tantangan yang ada, AI menawarkan peluang signifikan untuk memperbaiki cara pemerintah beroperasi. Keberhasilan penerapan AI tidak hanya tergantung pada teknologi itu sendiri, tetapi juga pada bagaimana pemerintah mengelola aspek-aspek etis, regulasi, dan sosial yang terkait. Untuk memaksimalkan manfaat AI, dibutuhkan kolaborasi antara teknolog, pembuat kebijakan, dan masyarakat sipil.