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Ethics of Data and Analytics : Concepts and Cases by Kirsten Martin (2022, Trade Paperback)

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About this product

Product Identifiers

PublisherCRC Press LLC

ISBN-101032062932

ISBN-139781032062938

eBay Product ID (ePID)25057239526

Product Key Features

Number of Pages424 Pages

Publication NameEthics of Data and Analytics : concepts and Cases

LanguageEnglish

Publication Year2022

SubjectBusiness Ethics, General, Databases / Data Mining, Information Technology

TypeTextbook

Subject AreaMathematics, Computers, Business & Economics

AuthorKirsten Martin

FormatTrade Paperback

Dimensions

Item Length10 in

Item Width7 in

Additional Product Features

Intended AudienceTrade

LCCN2021-051236

Dewey Edition23

IllustratedYes

Dewey Decimal006.312

SynopsisThe ethics of data and analytics, in many ways, is no different than any endeavor to find the 'right' answer. When a business chooses a supplier, funds a new product, or hires an employee, managers are making decisions with moral implications. The decisions in business, like all decisions, have a moral component in that people can benefit or be harmed, rules are followed or broken, people are treated fairly or not, and rights are enabled or diminished. However, data analytics introduces wrinkles or moral hurdles in how to think about ethics. Questions of accountability, privacy, surveillance, bias, and power stretch standard tools to examine whether a decision is good, ethical, or just. Dealing with these questions requires different frameworks to understand what is wrong and what could be better. The Ethics of Data and Analytics does not search for a definitive answer or to ban all technology in favor of human decision-making. The text takes a more skeptical, ironic approach to current answers and concepts while identifying and having solidarity with others. Applying this to the endeavor to understand the ethics of data and analytics, the text emphasizes finding multiple ethical approaches as ways to engage with current problems to find better solutions rather than prioritizing one set of concepts or theories. The book works through cases to understand those marginalized by data analytics programs as well those empowered by them. Three themes run throughout the book. First, data analytics programs are value-laden in that technologies create moral consequences, reinforce or undercut ethical principles, and enable or diminish rights and dignity. This places an additional focus on the role of developers in their incorporation of values in the design of data analytics programs. Second, design is critical. In the majority of the cases examined the purpose is to improve the design and development of data analytics programs. Third, data analytics, AI, and machine learning is about power. The discussion of power - who has it, who gets to keep it, who is marginalized - weaves throughout the chapters, theories, and cases. The book includes foundational articles and theories in the ethics of data analytics as well as engaging practical cases., The ethics of data and analytics, in many ways, is no different than any endeavor to find the "right" answer. When a business chooses a supplier, funds a new product, or hires an employee, managers are making decisions with moral implications. The decisions in business, like all decisions, have a moral component in that people can benefit or be harmed, rules are followed or broken, people are treated fairly or not, and rights are enabled or diminished. However, data analytics introduces wrinkles or moral hurdles in how to think about ethics. Questions of accountability, privacy, surveillance, bias, and power stretch standard tools to examine whether a decision is good, ethical, or just. Dealing with these questions requires different frameworks to understand what is wrong and what could be better. Ethics of Data and Analytics: Concepts and Cases does not search for a new, different answer or to ban all technology in favor of human decision-making. The text takes a more skeptical, ironic approach to current answers and concepts while identifying and having solidarity with others. Applying this to the endeavor to understand the ethics of data and analytics, the text emphasizes finding multiple ethical approaches as ways to engage with current problems to find better solutions rather than prioritizing one set of concepts or theories. The book works through cases to understand those marginalized by data analytics programs as well as those empowered by them. Three themes run throughout the book. First, data analytics programs are value-laden in that technologies create moral consequences, reinforce or undercut ethical principles, and enable or diminish rights and dignity. This places an additional focus on the role of developers in their incorporation of values in the design of data analytics programs. Second, design is critical. In the majority of the cases examined, the purpose is to improve the design and development of data analytics programs. Third, data analytics, artificial intelligence, and machine learning are about power. The discussion of power-who has it, who gets to keep it, and who is marginalized-weaves throughout the chapters, theories, and cases. In discussing ethical frameworks, the text focuses on critical theories that question power structures and default assumptions and seek to emancipate the marginalized., This textbook provides faculty the major concepts and cases to include in a class on the ethics of data analytics. The book is distinct as it focuses on ethics of data analytics, AI, and data (rather than infrastructure and reliability) and by explicitly linking data analytics to foundational business ethics theory.

LC Classification NumberQA76.9.D343M384 2022