Ethics of Data and Analytics: Concepts and Cases

The ethics of data and analytics is similar to any endeavor to find the right answer, but it introduces wrinkles or moral hurdles in how to think about ethics. Dealing with these questions requires different frameworks to understand what is wrong and what could be better. The book "Ethics of Data and Analytics: Concepts and Cases" emphasizes finding multiple ethical approaches to engage with current problems to find better solutions. Three themes run throughout the book: data analytics programs are value-laden, design is critical, and data analytics, artificial intelligence, and machine learning are about power. The discussion of power weaves throughout the chapters, theories, and cases, and critical theories question power structures and default assumptions and seek to emancipate the marginalized.

Format: Hardback
Length: 474 pages
Publication date: 13 May 2022
Publisher: Taylor & Francis Ltd

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, data analytics programs are complex and multifaceted, with different actors and stakeholders involved in their development, implementation, and use. This requires a nuanced understanding of the ethical implications of data analytics and a willingness to engage with a range of perspectives and stakeholders.

Third, data analytics programs are constantly evolving and changing, with new technologies and techniques emerging all the time. This requires a commitment to ongoing ethical reflection and evaluation to ensure that data analytics programs are used in a responsible and ethical manner.

In conclusion, the ethics of data and analytics is a complex and multifaceted issue that requires a range of ethical approaches to be considered. The book emphasizes the importance of 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 also highlights the role of developers in incorporating values in the design of data analytics programs and the need for a nuanced understanding of the ethical implications of data analytics and a willingness to engage with a range of perspectives and stakeholders. Finally, the book emphasizes the commitment to ongoing ethical reflection and evaluation to ensure that data analytics programs are used in a responsible and ethical manner.

Weight: 1070g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032217314