Download Applied Artificial Intelligence by Mariya Yao PDF

Applied Artificial Intelligence pdf

Applied Artificial Intelligence – Selected as CES 2018 Top Technology Book of the Year. Artificial intelligence” is the buzz word of the day. You’ve no doubt read your fair share of media hype either proclaiming doom and gloom where robots seize our jobs or prophesying a new utopia where AI cures all our human problems.

But what does it actually mean for your role as a business leader? Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. If you want to drive innovation by combining data, technology, design, and people to solve real problems at an enterprise scale, this is your playbook.

This book does not overload you with details on debugging TensorFlow code nor bore you with generalizations about the future of humanity. Instead, we teach you how to lead successful AI initiatives by prioritizing the right opportunities, building a diverse team of experts, conducting strategic experiments, and consciously designing your solutions to benefit both your organization and society as a whole. This book is focused on helping you drive concrete business decisions through applications of artificial intelligence and machine learning. Written with the combined knowledge of three experts in the field, Applied Artificial Intelligence is the best practical guide for business leaders looking to get true value from the adoption of machine learning technology. If you have questions such as…

…then this handbook provides you with answers.

Review – Applied Artificial Intelligence

“A practical guide for business leaders who aim to leverage machine intelligence. Helps business executives drive innovation by combining data, technology, design and people to solve real problems.”CES (Consumer Electronics Show 2018) “This excellent book provides a practical examination of how to harness disruptive technologies to achieve scalable and sustainable business success.”Steven Kuyan (NYU) “A perfect primer for anyone looking to understand the enterprise implications for emerging AI technology – a must read for any business leader intending to stay ahead.”Alex Stein (Viacom) “This book cuts the fluff and arms business leaders with exactly the right foundational knowledge to lead successful AI initiatives. Hands down the best playbook.”Jack Chua (Expedia)
“This book made me realize how little I actually knew about AI. Which is embarrassing because I live in the Silicon Valley which is AI Central.”Karen Cheng (Amazon Verified Review) “This is a fantastic introduction for people trying to make sense of this emerging field, especially with the goal of applying it to their business endeavors. The authors have made a complex topic accessible, makes for a great reading on a plane flight to your next meeting.”Amit Garg (Amazon Verified Review)

 “Amazing book that gets you excited about applied AI! The book does not overwhelm you with the technicalities of AI but educates you on how to think, be creative and leverage AI in projects. The book is easy to digest, fun to read and really get you excited about AI! MUST READ for anyone new to AI!”Lucy Y (Amazon Verified Review)

TABLE OF CONTENTS – Applied Artificial Intelligence


WHO THIS BOOK IS FOR 1
How to Use This Book 2
WHAT BUSINESS LEADERS NEED TO KNOW 5

  1. BASIC TERMINOLOGY IN ARTIFICIAL INTELLIGENCE 7
    AI vs. AGI 8
    Modern AI Techniques 9
  2. THE MACHINE INTELLIGENCE CONTINUUM 21
    Systems That Act 22
    Systems That Predict 22
    Systems That Learn 23
    Systems That Create 25
    Systems That Relate 27
    Systems That Master 28

Systems That Evolve 29

  1. THE PROMISES OF ARTIFICIAL INTELLIGENCE 31
    Microfinance 31
    Social Justice 32
    Medical Diagnosis 34
  2. THE CHALLENGES OF ARTIFICIAL INTELLIGENCE 37
    The Effects of Discrimination 39
    Malicious AI 40
  3. DESIGNING SAFE AND ETHICAL AI 43
    Ethics and Governance 43
    Education as Remedy 44
    Collaborative Design 46
    HOW TO DEVELOP AN ENTERPRISE AI STRATEGY 51
  4. BUILD AN AI-READY CULTURE 53

Be Honest About Your Readiness 53
Choose the Right Champions 57
Build An Enterprise-Wide Case For AI 66
Why You Need a Multi-Disciplinary “AI SWAT Team” 67
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Get Organizational Buy-In 69
Educate Your Stakeholders 73

  1. INVEST IN TECHNICAL TALENT 75
    Understand Different Job Titles 76
    Seek the Right Characteristics 79
    Optimize Recruiting Strategies 82
    Emphasize Your Company’s Unique Advantages 86
  2. PLAN YOUR IMPLEMENTATION 89
    Rank Business Goals 89
    Perform Opportunity Analysis 90
    AI Strategy Framework 93
    Know Your Data and Analytics 95
    Technical Prerequisites 98
    Build vs. Buy 100
    Calculate ROI and Allocate Budget 112
    Pick the Right “True North” Metric 117
  3. COLLECT AND PREPARE DATA 121
    Data Is Not Reality 121
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    Common Mistakes With Data 122
  4. BUILD MACHINE LEARNING MODELS 129
    AI Is Not a Silver Bullet 129
    Assessing the Performance of Your Models 131
    Common Mistakes With Machine Learning Models 135
    Machine Learning Workflow 136
    Maintain an Experimental Mindset 141
  5. EXPERIMENT AND ITERATE 143
    Agile Development 143
    Technical Debt 144
    Deployment and Scaling 146
    Iteration and Improvement 149
    AI FOR ENTERPRISE FUNCTIONS 151
  6. OBSTACLES AND OPPORTUNITIES 153
    Current Obstacles 155
    What AI Can Do for Enterprise Functions 157
  7. GENERAL AND ADMINISTRATIVE 159
    Finance and Accounting 159

Legal and Compliance 160
Records Maintenance 163
General Operations 163

  1. HUMAN RESOURCES AND TALENT 165
    Matching Candidates to Positions 165
    Managing the Interview Process 166
    Intelligent Scheduling 167
    Career Planning and Retention Risk Analysis 167
    Administrative Functions 168
  2. BUSINESS INTELLIGENCE AND ANALYTICS 169
    Data Wrangling 169
    Data Architecture 171
    Analytics 172
  3. SOFTWARE DEVELOPMENT 175
  4. MARKETING 181
    Digital Ad Optimization 182
    Recommendations and Personalization 184
  5. SALES 187
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    Customer Segmentation 187
    Lead Qualification and Scoring 188
    Sales Development 189
    Sales Analytics 189
  6. CUSTOMER SUPPORT 191
    Conversational Agents 192
    Social Listening 194
    Customer Churn 194
    Lifetime Value 195
  7. THE ETHICS OF ENTERPRISE AI 197
    SUMMARY AND ADDITIONAL RESOURCES 203
    END NOTES 207
    ACKNOWLEDGEMENTS 221
    AUTHOR AND EDITOR BIOGRAPHIES 225

WHO THIS BOOK IS FOR

Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. If you love to drive innovation by combining data, technology, design, and people, and to solve real problems at an enterprise scale, this is your playbook. There are plenty of technical tomes on the market for engineers and researchers who want to master the nittygritty details of modern algorithms and toolsets. You can also find plenty of general interest content for the public about the impact of AI on our society and the future of work. This book is a balance between the two. We won’t overload you with details on how to debug your code, but we also won’t bore you with endless generalizations that don’t help you make concrete business decisions. Instead, we teach you how to lead successful AI initiatives by prioritizing the right opportunities, building a diverse team of experts, conducting strategic experiments, and consciously designing your solutions to benefit both your organization and society as a whole.

How to Use This Book – Applied Artificial Intelligence

The first part of this book, “What Business Leaders Need to Know,” gives executives an essential education in the state of artificial intelligence today. We recommend reading this part in full before pursuing AI projects for your organization. Chapters 1 and 2 provide a non-technical introduction to AI, the techniques used to power modern AI systems, and the functional differences between different levels of machine intelligence. While you do not need to memorize every detail, a passing familiarity with technical definitions will help you separate hype from reality when evaluating a project proposal for your own organization. Chapters 3, 4, and 5 describe promising applications of AI in society as well as challenges that arise from biased or unethical algorithms. You’ll learn how collaborative design is essential to ensuring that we build benevolent AI systems. Applied Artificial Intelligence

In the second part of our book, “How to Develop an Enterprise AI Strategy,” we walk you through the strategic and methodological steps required to implement successful AI projects for your company. These chapters act as a reference guide as you are building your initiatives. Read through them once to familiarize yourself with the content, and then refer back to specific sections as needed during your projects. Chapters 6 and 7 teach you how to prepare your organization to succeed in AI projects. You will learn strategies to manage important stakeholders and attract technical talent. In Chapter 8, we guide you through exercises that will help you to identify opportunities for AI adoption within your organization and develop a business plan for implementation and deployment. Chapters 9, 10, and 11 explain common technical challenges you will encounter in building AI and how to overcome them. The last section of our book, “AI For Enterprise Functions,” highlights popular AI applications for common business functions. Chapter 12 summarizes some of the challenges of adopting AI solutions for enterprises. Chapters 13 and 14 introduce common AI applications in essential administrative functions like finance, legal, and HR, while Chapters 15 and 16 describe how machine learning can dramatically improve business intelligence, analytics, and software development. Chapters 17, 18, and 19 focus on the revenue-generating functions of sales, marketing, and customer service. Finally, Chapter 20 emphasizes the ethical responsibility that you, as business and technology leaders, have Preview Only. Not For Distribution 4 APPLIED ARTIFICIAL INTELLIGENCE towards your workforce as well as towards ensuring that any technologies that you build have a benevolent impact on your customers, employees, and society as a whole. Because AI technologies evolve very quickly, we created an educational website, appliedaibook.com, where we offer updated content and detailed case studies for specific industries. Supplemental content for this book can be found in our resources section at appliedaibook. com/resources. We also created social communities and discussion forums for our readers to connect with us and each other, which you can join by visiting appliedaibook. com/community

1. BASIC TERMINOLOGY IN ARTIFICIAL INTELLIGENCE

Think about the most intelligent person you know. What about this person leads you to describe him or her this way? Is she a quick thinker, able to internalize and apply new knowledge immediately? Is he highly creative, able to endlessly generate novel ideas that you’d never think of? Perhaps she’s highly perceptive and hones in on the tiniest details of the world around her. Or maybe he’s deeply empathetic and understands how you’re feeling even before you do. Human intelligence spans a wide spectrum of modalities, exhibiting abilities such as logical, spatial, and emotional cognition. Whether we are math geniuses or charismatic salesmen, we must utilize cognitive abilities like working memory, sustained attention, category formation, and pattern recognition to understand and succeed in the world every day. Though computers trounce humans at large-scale computational tasks, their expertise is narrow, and Preview Only. Not For Distribution 8 APPLIED ARTIFICIAL INTELLIGENCE machine capability lags behind human intelligence in other areas. The rest of this chapter will help you to understand the state of artificial intelligence today.

AI vs. AGI – Applied Artificial Intelligence

Artificial intelligence, also known as AI, has been misused in pop culture to describe almost any kind of computerized analysis or automation. To avoid confusion, technical experts in the field of AI prefer to use the term Artificial General Intelligence (AGI) to refer to machines with human-level or higher intelligence, capable of abstracting concepts from limited experience and transferring knowledge between domains. AGI is also called “Strong AI” to differentiate from “Weak AI” or “Narrow AI,” which refers to systems designed for one specific task and whose capabilities are not easily transferable to other systems. We go into more detail about the distinction between AI and AGI in our Machine Intelligence Continuum in Chapter 2. Though Deep Blue, which beat the world champion in chess in 1997, and AlphaGo, which did the same for the game of Go in 2016, have achieved impressive results, all of the AI systems we have today are “Weak AI.” Narrowly intelligent programs can defeat humans in specific tasks, but they can’t apply that expertise to other tasks, such as driving cars or creating art. Solving tasks outside of the program’s original parameters requires building additional programs that are similarly narrow.

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