Ethical Data Science

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Ethical Data Science

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Author : Anne L. Washington
language : en
Publisher: Oxford University Press
Release Date : 2023

Ethical Data Science written by Anne L. Washington and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Computers categories.

Amidst a growing movement to use science for positive change, Ethical Data Science offers a solution-oriented approach to the ethical challenges of data science. As one of the first books on public interest technology, it provides a starting point for anyone who wants human values to counterbalance the institutional incentives that drive computational prediction.

Ethical Practice Of Statistics And Data Science

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Author : Rochelle Tractenberg
language : en
Publisher: Ethics International Press
Release Date : 2023-11-25

Ethical Practice Of Statistics And Data Science written by Rochelle Tractenberg and has been published by Ethics International Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Language Arts & Disciplines categories.

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 of Ethics. It is necessary reading for students enrolled in any data intensive program, including undergraduate or graduate degrees in (bio-)statistics, business/analytics, or data science. Managers, leaders, supervisors, and mentors who lead data-intensive teams in government, industry, or academia would also benefit greatly from this book. This is a companion volume to Ethical Reasoning For A Data-Centered World, also published by Ethics International Press (2022). These are the first and only books to be based on, and to provide guidance to, the ASA and ACM Ethical Guidelines/Code of Ethics.

Ethics And Data Science

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Author : Mike Loukides
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-07-25

Ethics And Data Science written by Mike Loukides and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-25 with Computers categories.

As the impact of data science continues to grow on society there is an increased need to discuss how data is appropriately used and how to address misuse. Yet, ethical principles for working with data have been available for decades. The real issue today is how to put those principles into action. With this report, authors Mike Loukides, Hilary Mason, and DJ Patil examine practical ways for making ethical data standards part of your work every day. To help you consider all of possible ramifications of your work on data projects, this report includes: A sample checklist that you can adapt for your own procedures Five framing guidelines (the Five C’s) for building data products: consent, clarity, consistency, control, and consequences Suggestions for building ethics into your data-driven culture Now is the time to invest in a deliberate practice of data ethics, for better products, better teams, and better outcomes. Get a copy of this report and learn what it takes to do good data science today.

Data Science Ethics

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Author : David Martens
language : en
Publisher: Oxford University Press
Release Date : 2022-03-24

Data Science Ethics written by David Martens and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-24 with Computers categories.

Data science ethics is all about what is right and wrong when conducting data science. Data science has so far been primarily used for positive outcomes for businesses and society. However, just as with any technology, data science has also come with some negative consequences: an increase of privacy invasion, data-driven discrimination against sensitive groups, and decision making by complex models without explanations. While data scientists and business managers are not inherently unethical, they are not trained to weigh the ethical considerations that come from their work - Data Science Ethics addresses this increasingly significant gap and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques. Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.

Ethical Data

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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2024-12-14

Ethical Data written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-14 with Computers categories.

Discover the transformative power of data while navigating its ethical landscape in "Ethical Data." Whether you're a data enthusiast, a business professional, or someone intrigued by the promises and perils of data science, this comprehensive eBook is your gateway to understanding and implementing ethical data practices. Begin your journey with a thorough exploration of the ethical implications in the rapidly evolving field of data science. Gain clarity on why ethics must be at the forefront of data-driven decision-making. Delve into the vital principles of ethical data collection, learn about informed consent, and understand the significance of protecting privacy while avoiding bias in data sampling. Dive deeper into responsible data management with insights on data anonymization techniques and the development of robust data governance policies. Understand how to mitigate algorithmic bias, ensure fairness, and promote accountability within your data operations. "Ethical Data" sheds light on the critical aspects of data analysis, from ensuring transparency and interpretability in models to addressing ethical concerns in predictive analytics. With clear strategies and real-world case studies, the book provides practical guidance on implementing ethical frameworks in various organizational contexts. Navigate the ethical dimensions of AI and machine learning, explore transparency in data science practices, and discover best practices for responsible data sharing. Engaging case studies highlight both the triumphs and challenges organizations face in the ethical implementation of data science. With its forward-looking perspective, "Ethical Data" prepares you for the future, addressing emerging trends and specialized ethical challenges in fields like healthcare, finance, and government. By promoting a culture of ethics through training, awareness, and stakeholder engagement, this eBook empowers you to foster public trust and spearhead ethical innovations in your field. Step into the future of data science with confidence, equipped with the knowledge to bridge ethics and data effectively.

A Friendly Guide To Data Science

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Author : Kelly P. Vincent
language : en
Publisher: Springer Nature
Release Date : 2025-06-26

A Friendly Guide To Data Science written by Kelly P. Vincent and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-26 with Computers categories.

Unlock the world of data science—no coding required. Curious about data science but not sure where to start? This book is a beginner-friendly guide to what data science is and how people use it. It walks you through the essential topics—what data analysis involves, which skills are useful, and how terms like “data analytics” and “machine learning” connect—without getting too technical too fast. Data science isn’t just about crunching numbers, pulling data from a database, or running fancy algorithms. It’s about asking the right questions, understanding the process from start to finish, and knowing what’s possible (and what’s not). This book teaches you all of that, while also introducing important topics like ethics, privacy, and security—because working with data means thinking about people, too. Whether you're a student exploring new skills, a professional navigating data-driven decisions, or someone considering a career change, this book is your friendly gateway into the world of data science, one of today’s most exciting fields. No coding or programming experience? No problem. You'll build a solid foundation and gain the confidence to engage with data science concepts— just as AI and data become increasingly central to everyday life. What You Will Learn Grasp foundational statistics and how it matters in data analysis and data science Understand the data science project life cycle and how to manage a data science project Examine the ethics of working with data and its use in data analysis and data science Understand the foundations of data security and privacy Collect, store, prepare, visualize, and present data Identify the many types of machine learning and know how to gauge performance Prepare for and find a career in data science Who This Book is for A wide range of readers who are curious about data science and eager to build a strong foundation. Perfect for undergraduates in the early semesters of their data science degrees, as it assumes no prior programming or industry experience. Professionals will find particular value in the real-world insights shared through practitioner interviews. Business leaders can use it to better understand what data science can do for them and how their teams are applying it. And for career changers, this book offers a welcoming entry point into the field—helping them explore the landscape before committing to more intensive learning paths like degrees or boot camps.

Data Science And Business Intelligence For Corporate Decision Making

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Author : Dr. P. S. Aithal
language : en
Publisher: Srinivas Publication, Mangalore
Release Date : 2024-02-09

Data Science And Business Intelligence For Corporate Decision Making written by Dr. P. S. Aithal and has been published by Srinivas Publication, Mangalore this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-09 with Art categories.

About the Book: A comprehensive book plan on "Data Science and Business Intelligence for Corporate Decision-Making" with 15 chapters, each with several sections: Chapter 1: Introduction to Data Science and Business Intelligence Chapter 2: Foundations of Data Science Chapter 3: Business Intelligence Tools and Technologies Chapter 4: Data Visualization for Decision-Making Chapter 5: Machine Learning for Business Intelligence Chapter 6: Big Data Analytics Chapter 7: Data Ethics and Governance Chapter 8: Data-Driven Decision-Making Process Chapter 9: Business Intelligence in Marketing Chapter 10: Financial Analytics and Business Intelligence Chapter 11: Operational Excellence through Data Analytics Chapter 12: Human Resources and People Analytics Chapter 13: Case Studies in Data-Driven Decision-Making Chapter 14: Future Trends in Data Science and Business Intelligence Chapter 15: Implementing Data Science Strategies in Corporations Each chapter dives deep into the concepts, methods, and applications of data science and business intelligence, providing practical insights, real-world examples, and case studies for corporate decision-making processes.

Ethical Data Science

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Author : Anne L. Washington
language : en
Publisher:
Release Date : 2023

Ethical Data Science written by Anne L. Washington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Data mining categories.

Data Science Ethics

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Author : David Martens
language : en
Publisher: Oxford University Press
Release Date : 2022

Data Science Ethics written by David Martens and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Computers categories.

This book examines a variety of different concepts related to data science ethics and techniques that can help with, or lead to, ethical concerns, whilst featuring cautionary tales that illustrate the importance and potential impact of data science ethics.

97 Things About Ethics Everyone In Data Science Should Know

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Author : Bill Franks
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-08-06

97 Things About Ethics Everyone In Data Science Should Know written by Bill Franks and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-06 with Computers categories.

Most of the high-profile cases of real or perceived unethical activity in data science arenâ??t matters of bad intent. Rather, they occur because the ethics simply arenâ??t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Conceptâ??Tim Wilson How to Approach Ethical Transparencyâ??Rado Kotorov Unbiased ≠ Fairâ??Doug Hague Rules and Rationalityâ??Christof Wolf Brenner The Truth About AI Biasâ??Cassie Kozyrkov Cautionary Ethics Talesâ??Sherrill Hayes Fairness in the Age of Algorithmsâ??Anna Jacobson The Ethical Data Storytellerâ??Brent Dykes Introducing Ethicizeâ?¢, the Fully AI-Driven Cloud-Based Ethics Solution!â??Brian Oâ??Neill Be Careful with "Decisions of the Heart"â??Hugh Watson Understanding Passive Versus Proactive Ethicsâ??Bill Schmarzo