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Democratizing Artificial Intelligence with UiPath

You're reading from   Democratizing Artificial Intelligence with UiPath Expand automation in your organization to achieve operational efficiency and high performance

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801817653
Length 376 pages
Edition 1st Edition
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Authors (2):
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Fanny Ip Fanny Ip
Author Profile Icon Fanny Ip
Fanny Ip
Jeremiah Crowley Jeremiah Crowley
Author Profile Icon Jeremiah Crowley
Jeremiah Crowley
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Table of Contents (16) Chapters Close

Preface 1. Section 1: The Basics
2. Chapter 1: Understanding Essential Artificial Intelligence Basics for RPA Developers FREE CHAPTER 3. Chapter 2: Bridging the Gap between RPA and Cognitive Automation 4. Chapter 3: Understanding the UiPath Platform in the Cognitive Automation Life Cycle 5. Section 2: The Development Life Cycle with AI Center and Document Understanding
6. Chapter 4: Identifying Cognitive Opportunities 7. Chapter 5: Designing Automation with End User Considerations 8. Chapter 6: Understanding Your Tools 9. Chapter 7: Testing and Refining Development Efforts 10. Section 3: Building with UiPath Document Understanding, AI Center, and Druid
11. Chapter 8: Use Case 1 – Receipt Processing with Document Understanding 12. Chapter 9: Use Case 2 – Email Classification with AI Center 13. Chapter 10: Use Case 3 – Chatbots with Druid 14. Chapter 11: AI Center Advanced Topics 15. Other Books You May Enjoy

Designing human-machine collaboration with cognitive automation

In the previous section, we explored the spectrum of office work and its relative automation potentials. Companies look for a more efficient and effective way to perform office work by leveraging automation. Office work does not comprise a single activity but a sequence of activities that make up a process. Full automation of the end-to-end (E2E) process may be the eventual goal. However, a more realistic goal is good human-machine collaboration to drive efficiency and effectiveness with currently available technology. Therefore, it is important to understand how humans and machines work differently and the best way to think through a human-machine collaboration when designing cognitive automation.

Demonstrating human-machine collaboration with examples

When we look at office work at a process level instead of at an activity level, we find that this is a collection of activities with different automation potentials...

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