Part 4: Ethical Aspects of Data Management and ML System Development

Since machine learning is based on patterns in the training data, we need to understand how to work with this kind of system from an ethical perspective. Ethics is one of these areas that software engineers are not the most familiar with. In this part of the book, we look into what kind of ethical issues exist in data acquisition and management and how to work with bias in machine learning algorithms. Finally, we finish up this part by exploring how to integrate what we’ve learned in this book into an entire ecosystem of web services and how to deploy them.

This part has the following chapters:

• Chapter 14, Ethics in Data Acquisition and Management
• Chapter 15, Ethics in Machine Learning Systems
• Chapter 16, Integration of ML Systems in Ecosystems
• Chapter 17, Summary and Where to Go Next