Description
Book 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.
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
Table of Contents
Introduction. 1 Value-Laden Biases in Data Analytics. 2 Ethical Theories and Data Analytics. 3 Privacy, Data, and Shared Responsibility. 4 Surveillance and Power. 5 The Purpose of the Corporation and Data Analytics. 6 Fairness and Justice in Data Analytics. 7 Discrimination and Data Analytics. 8 Creating Outcomes and Accuracy in Data Analytics. 9 Gamification, Manipulation, and Data Analytics. 10 Transparency and Accountability in Data Analytics. 11 Ethics, AI, Research, and Corporations. Index.
