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Ethical Practice of Statistics and Data Science
Ethical Practice of Statistics and Data Science is intended to prepare people to fully assume their responsibilities to practice statistics and data science ethically. Aimed at early career professionals, practitioners, and mentors or supervisors of practitioners, the book supports the ethical practice of statistics and data science, with an emphasis on how to earn the designation of, and recognize, “the ethical practitioner”. The book features 47 case studies, each mapped to the Data Science Ethics Checklist (DSEC); Data Ethics Framework (DEFW); the American Statistical Association (ASA) Ethical Guidelines for Statistical Practice; and the Association of Computing Machinery (ACM) Code o...
Ethical Reasoning for a Data-Centered World
The American Statistical Association (ASA) and the Association of Computing Machinery (ACM) have longstanding ethical practice standards that are explicitly intended to be utilized by all who use statistical practices or computing, or both. Since statistics and computing are critical in any data-centered activity, these practice standards are essential to instruction in the uses of statistical practices or computing across disciplines. Ethical Reasoning For A Data-Centered World is aimed at any undergraduate or graduate students utilizing data. Whether the career goal is research, teaching, business, government, or a combination, this book presents a method for understanding and prioritizing...
Ethics in Statistics
Data plays a vital role in different parts of our lives. In the world of big data, and policy determined by a variety of statistical artifacts, discussions around the ethics of data gathering, manipulation and presentation are increasingly important. Ethics in Statistics aims to make a significant contribution to that debate. The processes of gathering data through sampling, summarising of the findings, and extending results to a population, need to be checked via an ethical prospective, as well as a statistical one. Statistical learning without ethics can be harmful for mankind. This edited collection brings together contributors in the field of data science, data analytics and statistics, to share their thoughts about the role of ethics in different aspects of statistical learning.
Neurotechnology in National Security and Defense
Neurotechnology in National Security and Defense: Practical Considerations, Neuroethical Concerns is the second volume in the Advances in Neurotechnology series. It specifically addresses the neuroethical, legal, and social issues arising from the use of neurotechnology in national security and defense agendas and applications. Of particular concer
Medical Informatics in a United and Healthy Europe
This volume contains the proceedings of the twenty-second International Conference on Medical Informatics Europe MIE 2009, that was held in Sarajevo, Bosnia and Herzegovina, from 30 August to 2 September 2009. The scientific topics present in this proceedings range from national and trans-national eHealth roadmaps, health information and electronic health record systems, systems interoperability and communication standards, medical terminology and ontology approaches, and social networks to Web, Web 2.0, nd Semantic Web solutions for patients, health personnel, and researchers. Furthermore, they include quality assurance and usability of medical informatics systems, specific disease management and telemedicine systems, including a section on devices and snsors, drug safety, clinical decision support and medical expert systems, clinical practice guidelines and protocols, as well as issues on privacy and security. Moreover, bioinformatics, biomedical modeling and simulation, medical imaging and visualizatio and, last but not least, learning and education through medical informatics systems are parts of the included topics.
Roundtable on Data Science Postsecondary Education
Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and government gathered with other experts from across the nation to discuss various topics under this charge. The meetings centered on four central themes: foundations of data science; data science across the postsecondary curriculum; data science across society; and ethics and data science. This publication highlights the presentations and discussions of each meeting.
Transparency in Social Media
The volume presents, in a synergistic manner, significant theoretical and practical contributions in the area of social media reputation and authorship measurement, visualization, and modeling. The book justifies and proposes contributions to a future agenda for understanding the requirements for making social media authorship more transparent. Building on work presented in a previous volume of this series, Roles, Trust, and Reputation in Social Media Knowledge Markets, this book discusses new tools, applications, services, and algorithms that are needed for authoring content in a real-time publishing world. These insights may help people who interact and create content through social media ...
Germ Wars
Cover -- Germ Wars -- Title -- Copyright -- Contents -- Introduction: Political Ecologies of Bioterror -- 1. "Smallpox Is Dead": The Public Health Campaign to (Almost) Eradicate a Species -- 2. Microbes for War and Peace: On the Military Origins of Containment -- 3. The Wild Microbiological West: Fighting Ticks and Weighing Risks -- 4. Agents of Care: Bioterrorism Preparedness at the CDC -- 5. Simulation Science: Securing the Future -- 6. Bioterror Borderlands: Of Nature and Nation -- Conclusion: "Freaked Out Yet?"--Acknowledgments -- Notes -- Selected Bibliography -- Index
The Ethics of Biomedical Big Data
This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understanding of the ethical conundrums posed by biomedical Big Data, and shows how practitioners and policy-makers can address these issues going forward.
