Book Image

Artificial Intelligence with Power BI

By : Mary-Jo Diepeveen
Book Image

Artificial Intelligence with Power BI

By: Mary-Jo Diepeveen

Overview of this book

The artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data. This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data. You’ll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you’ll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you’ll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you’ll work through principles such as privacy, fairness, and transparency to use AI responsibly. By the end of this book, you’ll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI.
Table of Contents (18 chapters)
Part 1: AI Fundamentals
Part 2: Out-of-the-Box AI Features
Part 3: Create Your Own Models

Chapter 13: Responsible AI

Throughout this book, we have explored ways to integrate artificial intelligence (AI) with Power BI, whether it is by using out-of-the-box features or by training your models. While AI can help uncover interesting insights from data, it is important to think about how the data and models are created and used. Insights are often used to make decisions and will influence your actions. Therefore, you want to be able to trust those insights and know that you are making responsible decisions.

There are many things to examine when practicing responsible AI. In this chapter, we'll discuss what responsible AI entails and three of the most common considerations. To do this, we will be covering the following topics:

  • Understanding responsible AI
  • Protecting privacy when using personal data
  • Creating transparent models
  • Creating fair models

Putting responsible AI into practice is a complicated endeavor that requires an interdisciplinary...