Ethics of Big Data: Balancing Risk and Innovation
Kord Davis
Language: English
Pages: 82
ISBN: 1449311792
Format: PDF / Kindle (mobi) / ePub
What are your organization’s policies for generating and using huge datasets full of personal information? This book examines ethical questions raised by the big data phenomenon, and explains why enterprises need to reconsider business decisions concerning privacy and identity. Authors Kord Davis and Doug Patterson provide methods and techniques to help your business engage in a transparent and productive ethical inquiry into your current data practices.
Both individuals and organizations have legitimate interests in understanding how data is handled. Your use of data can directly affect brand quality and revenue—as Target, Apple, Netflix, and dozens of other companies have discovered. With this book, you’ll learn how to align your actions with explicit company values and preserve the trust of customers, partners, and stakeholders.
- Review your data-handling practices and examine whether they reflect core organizational values
- Express coherent and consistent positions on your organization’s use of big data
- Define tactical plans to close gaps between values and practices—and discover how to maintain alignment as conditions change over time
- Maintain a balance between the benefits of innovation and the risks of unintended consequences
In the Name of Profit: Profiles in Corporate Irresponsibility
Evolutionary Ethics and Contemporary Biology (Cambridge Studies in Philosophy and Biology)
Morality Play: Case Studies in Ethics
Opt-out? • What data raises the most organizational risk? What is required to determine the risk-benefit ratio of not collecting that data? • Do data-handling practices generate external influences that specific values de mand not be created? (Examples could be social networks diminishing real-world relationships or music recommendation services reducing the ability to make dis cerning judgments.) 1. As mentioned, it has recently been noted to that reading all the EULA you encounter would take.
Technical issues of a wide variety of aggregation possibilities, paired with the sociological, psychological, and economic factors relevant to understanding their potential actions. For example, third parties with access to customer data may be hesitant to share infor mation about their own practices, citing a variety of constraints such as competitive intelligence, intellectual property, or their own value system. While this hesitation itself is not sufficient cause for concern, a responsible.
The majority of the prod ucts and services it offers. They run a Hadoop cluster of nearly 100 machines, process near real-time analytics reporting with Pentaho, and are experimenting with ways to enhance their customers’ ability to analyze their own datasets using R for statistical analysis and graphics. Their combined customer data sets exceed 100 terabytes and are growing daily. Further, they are especially excited about a powerful new opportunity their data scien tists have uncovered that.
Express, and Gardenburger. Integrating a professional background in telecommunications and an academic background in philosophy, he brings passionate curiosity, the rigor of analysis, and a love of how technology can help us do the things we really want to do better, faster, and easier. A formally trained workgroup facilitator, he holds a BA in Philosophy from Reed College and professional certifications in communication, systems modeling, and enterprise transformation.
Have and where they might not be aligned. And this can be a complex activity with a specialized vocabulary. The following are some useful terms in developing that vocabulary: Rights and interests It is common for people to speak of privacy rights, but talk of rights brings with it the suggestion that such rights are absolute, which presumes to prejudge some of the issues at hand. In order to avoid prejudgment, we will speak of privacy inter ests and other sorts of interests, with the explicit.