MARC details
000 -LEADER |
fixed length control field |
03019nmm a2200193Ia 4500 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
220920s9999||||xx |||||||||||||| ||und|| |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781003278290 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.312 |
Item number |
M364E |
100 ## - MAIN ENTRY--PERSONAL NAME |
Personal name |
Martin, Kirsten |
Relator term |
Author |
Language of a work |
English |
9 (RLIN) |
2819 |
245 #0 - TITLE STATEMENT |
Title |
Ethics of Data and Analytics |
Remainder of title |
: Concepts and Cases |
Statement of responsibility, etc. |
/ by Kirsten Martin. |
Medium |
[Electronic Resource] |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
New York |
Name of publisher, distributor, etc. |
: Auerbach Publications, |
Date of publication, distribution, etc. |
2022 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
492p. |
520 ## - SUMMARY, ETC. |
Summary, etc. |
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. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Analytics |
9 (RLIN) |
2820 |
|
Topical term or geographic name entry element |
Computer Science |
9 (RLIN) |
926 |
|
Topical term or geographic name entry element |
Data Ethics |
9 (RLIN) |
2821 |
856 ## - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="https://doi.org/10.1201/9781003278290">https://doi.org/10.1201/9781003278290</a> |
Electronic format type |
PDF |
Link text |
Click to Access the Online Book |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
e-Book |
Suppress in OPAC |
|