Apress Understand Manage and Prevent Algorithmic Bias 1st edition by Tobias Baer- Ebook PDF Instant Download/Delivery: 1484248848, 978-1484248843
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ISBN 10: 1484248848
ISBN 13: 978-1484248843
Author: Tobias Baer
Are algorithms friend or foe?
The human mind is evolutionarily designed to take shortcuts in order to survive. We jump to conclusions because our brains want to keep us safe. A majority of our biases work in our favor, such as when we feel a car speeding in our direction is dangerous and we instantly move, or when we decide not take a bite of food that appears to have gone bad. However, inherent bias negatively affects work environments and the decision-making surrounding our communities. While the creation of algorithms and machine learning attempts to eliminate bias, they are, after all, created by human beings, and thus are susceptible to what we call algorithmic bias.
In Understand, Manage, and Prevent Algorithmic Bias, author Tobias Baer helps you understand where algorithmic bias comes from, how to manage it as a business user or regulator, and how data science can prevent bias from entering statistical algorithms. Baer expertly addresses someof the 100+ varieties of natural bias such as confirmation bias, stability bias, pattern-recognition bias, and many others. Algorithmic bias mirrors—and originates in—these human tendencies. Baer dives into topics as diverse as anomaly detection, hybrid model structures, and self-improving machine learning.
While most writings on algorithmic bias focus on the dangers, the core of this positive, fun book points toward a path where bias is kept at bay and even eliminated. You’ll come away with managerial techniques to develop unbiased algorithms, the ability to detect bias more quickly, and knowledge to create unbiased data. Understand, Manage, and Prevent Algorithmic Bias is an innovative, timely, and important book that belongs on your shelf. Whether you are a seasoned business executive, a data scientist, or simply an enthusiast, now is a crucial time to be educated about the impact of algorithmic bias on society and take an active role in fighting bias.
Apress Understand Manage and Prevent Algorithmic Bias 1st Table of contents:
Part I. An Introduction to Biases and Algorithms
1. Introduction
2. Bias in Human Decision-Making
3. How Algorithms Debias Decisions
4. The Model Development Process
5. Machine Learning in a Nutshell
Part II. Where Does Algorithmic Bias Come From?
6. How Real-World Biases Are Mirrored by Algorithms
7. Data Scientists’ Biases
8. How Data Can Introduce Biases
9. The Stability Bias of Algorithms
10. Biases Introduced by the Algorithm Itself
11. Algorithmic Biases and Social Media
Part III. What to Do About Algorithmic Bias from a User Perspective
12. Options for Decision-Making
13. Assessing the Risk of Algorithmic Bias
14. How to Use Algorithms Safely
15. How to Detect Algorithmic Biases
16. Managerial Strategies for Correcting Algorithmic Bias
17. How to Generate Unbiased Data
Part IV. What to Do About Algorithmic Bias from a Data Scientist’s Perspective
18. The Data Scientist’s Role in Overcoming Algorithmic Bias
19. An X-Ray Exam of Your Data
20. When to Use Machine Learning
21. How to Marry Machine Learning with Traditional Methods
22. How to Prevent Bias in Self-Improving Models
23. How to Institutionalize Debiasing
Back Matter
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