-About this book
Would you travel to a different country without knowing some of its fundamental laws?
A whole new digital world exists side-by-side with our physical world – a world housing an emerging AI Nation. Should you enter this nation without a basic idea of how it functions? To say humanity is on the edge of its most important turning point in a century is an understatement. We are right in the middle of it. Across public and private parastatals, Al and mass automation are changing how we interact with the world around us. A new digital economy is evolving and the onus rests on executives and industry leaders to keep up. Imagine for a moment that you need to attend your daughter’s baseball game but you also need to be at an important meeting scheduled for the same time. What would you do?
What if this decision didn’t have to be challenging because you have an Al twin of yourself?
This is an idea of how just how much more different an Al-centered world would be. You or your Al twin would be able to interact with digital doctors, lawyers, etc. The steps towards that future are being taken even as you read these lines. Many global corporations are repositioning themselves towards being at the forefront of this revolution. Organizations failing to do so will find themselves ill-equipped to navigate this future. Worse yet, they will watch their competitors blitz past them. The economic loss would be devastating.In THE AI CITIZEN, I draw on over a decade’s worth of industry experience to explore the dynamic and enigmatic world of Artificial Intelligence. Business professionals, industry leaders, policymakers, and just about anyone with a remote or keen interest in AI will find this book tailored to their need for a relatable exploration of AI. THE AI CITIZEN presents AI as a global nation that cuts across international borders and one which everyone will – directly or indirectly – interact with. In simple and non-technical terms, THE AI CITIZEN deconstructs the world of AI and Industry 4.0. From examining the origins of AI, the book takes a critical look at its present state and further reflects on the ethical and moral issues to be contended with as the AI nation grows.
The book goes on to explain how to put together all of its content to create a winning AI strategy.This knowledge, however, is not only meant for the corporate world. Even children need to learn about Al, so they grow up understanding and stepping into roles that ensure the continuous development of Al for the benefit of humanity. This book was written with the vision of grooming business and government leaders to become “Responsible Al Citizen Leaders”. Contained within this book are the requisite knowledge and tool essentials needed to achieve this. This book’s content will be constantly updated by the author whose ambition is to groom 10 million citizen leaders globally. In THE AI CITIZEN, the reader holds in their hands the constitution of the AI nation and all the knowledge they need to have a sense of identity and thrive in this new world.
–Table of Contents
- Preface
- Who is this Book for?
- Introduction
1.1 Background
1.2 What is Artificial Intelligence (AI)?
1.3 AI is not a Robot
1.4 The AI Race
1.5 AI & The Global Economy
1.6 Why Should You Care?
1.7 What AI Cannot Do Now?
- Industry 4.0
2.1 The 4th Industrial Revolution
2.2 What is the 4th Industrial Revolution ?
2.3 Robotic Process Automation (RPA)
2.4 Blockchain Technology
2.5 Internet of Things
2.6 Robotics
2.7 Smart City
2.8 Cyber Security
2.9 Cloud Computing
2.10 Cognitive Computing
2.11 Quantum Computation
2.12 Digital Reality (DR)
- AI 101
3.1 History: The Evolution of AI
3.2 Enablers: Why AI is Booming Now?
3.3 Types of Artificial Intelligence
3.3.1 Stages of development
1.3.2 Functionality-based AI Types
1.3.3 The 4 AI Applications
1.3.4 Technique-based AI
3.4 How it Works?
3.5 Why You need AI?
3.6 Social Robots
3.7 The AI Debate
- Data
4.1 What is Data?
4.2 Types of Data
4.3 Why Data is the Fuel?
4.4 What is Big Data?
4.5 The 5Vs
4.6 Big Data Life Cycle
4.7 Data Collection
4.8 Data Management & Analytics
4.9 Hadoop Framework
4.10 AI & Data: Common Misconceptions
4.11 Additional Key Concepts
4.12 Big Data : Risks and Ethics
- Introduction to Machine Learning
5.1 What is Machine Learning
5.2 Basic Concepts
5.3 How Machines Learn ?
5.4 Types of Machine Learning
6.Supervised Learning
6.1 What is Supervised Learning?
6.2 Types of Machine Learning
6.3 What is Classification ?
6.4 Classification Algorithms
6.4.1 The K-Nearest Neighbor Classifier
6.4.2 Support Vector Machines
6.4.3 Linear Classifiers: Logistic Regression & Naïve Bayes
6.4.4 Decision Tree
6.4.5 Random Forest
6.4.6 Neural Network
6.5 Examples of Classification
6.6 What is Regression?
6.6.1 Understanding Linear Regression
6.6.2 Learning Linear Regression
6.6.3 Visualizing Linear Regression
6.6.4 Applying Regression to Label Predictions
6.7 Regression Algorithms
6.7.1 Simple Linear Regression Model
6.7.2 Lasso Regression
6.7.3 Support Vector Machines
6.8 Examples of Regression
- Unsupervised Learning
7.1 What is Unsupervised Learning?
7.1.2 Types of Unsupervised Learning
7.2 What is Clustering ?
7.3 Types of Clustering
7.3.1 Methods of Clustering
7.3.2 Types of Clustering
7.4 Dimensionality Reduction
7.4.1 What is Dimensionality Reduction?
7.4.2 Methods of Dimensionality Reduction
7.4.3 Pros and Cons of Dimensionality Reduction
7.5 Examples of Dimensionality Reduction
- Reinforcement Leaning
8.1 What is Reinforcement Learning?
8.1.1 Difference between Reinforcement Learning and Supervised Learning
8.1.2 How Reinforcement Learning Works
8.2 Reinforcement Learning Algorithms
8.2.1 Classification of Reinforcement Learning Algorithms
8.2.2 Types of Reinforcement Learning
8.2.3 Learning Models of Reinforcement Learning
8.3 Applications of Reinforcement Learning
8.3.1 Self-Driving Cars
8.3.2 Traffic Control
8.3.3 Robotics
8.3.4 Web System Configuration
8.3.5 Chemistry
8.3.6 Personalized Recommendations
8.3.7 Games
- Deep Learning
9.1 The Fundamentals of Artificial Neural Networks
9.2 The Construction of Artificial Neural Networks
9.2.1 Weights and Inputs
9.2.2 Activations and Outputs
9.2.3 Neuron Activation
9.2.4 The Perceptron
9.2.5 Networking Neurons
9.2.6 Comparing the AI Brain and the Human Brain
9.3 What is Deep Learning ?
9.4 Deep Learning vs Machine Learning
9.5 Types of Deep Learning
9.5.1 Feedforward Neural Networks
9.5.2 Backpropagation
9.6 Convolutional Neural Networks
9.7 Recurrent Neural Networks (RNN)
9.8 Generative Adversarial Networks (GAN)
- The Machine Learning Process Framework
10.2 Problem Formulation
10.3 Data Preprocessing
10.4 Feature Engineering
10.5 Data Splitting
10.6 ML Algorithm Selection
10.7 Model Training
10.8 Model Evaluation
10.9 Model Improvement
10.10 Model Deployment
- AI Capabilities
11.1 Speech Recognition
11.2 Natural Language Processing
11.2.1 Example
11.3 Computer Vision
11.3.1 What is it?
11.3.2 How Does it Work?
11.3.3 Industry Applications
11.4 Drones, Autonomous Vehicles & Intelligent Robotics
11.4.1 What is it?
11.4.2 How does it work?
11.2.3 The DARPA Challenge
11.2.4 Valkyrie
11.5 Predictive Analytics
11.5.1 What is it?
11.5.2 How does it work?
11.5.3 Example
- Industry-Based AI Applications
12.1 AI in Education
12.1.1 Student Universal Access
12.1.2 Automate Administrative Tasks
12.1.3 Out-of-School Tutoring and Support
12.2 AI in Healthcare
12.2.1 Staying Healthy
12.2.2 Early Detection
12.2.3 Diagnosis
12.2.4 Improve Decision-Making
12.2.5 Treatment
12.2.6 End-of-Life Care
12.2.7 Research
12.2.8 Training
12.3 AI in Meteorology
12.4 AI in Business Analysis
12.5 AI in Communication
12.6 AI in Industrial Operations
12.7 AI in Pharmaceuticals
12.8 AI in Property Management
12.8.1 Automated Property Management
12.8.2 The Recommendation System
12.8.3 Virtual Assistants
12.9 AI in Financial Services
12.10 AI in Security
12.10.1 AI and Security Applications
12.11 AI in Marketing & Retail
12.12 AI in E-Commerce
12.12.1 Chatbots & Virtual Assistants
12.12.2 Intelligent Product Recommendations
12.12.3 Personalization Services
12.13 AI in Oil & Gas
12.14 AI in Space
12.14.1 Space Exploration
12.14.2 Astronaut Assistants
12.14.3 Applications of AI in Space
12.15 AI in Agriculture
12.16 AI in Politics & Economics
12.17 AI in Logistics & Transportation
12.17.1 Autonomous Vehicles
- Responsible AI
13.1 AI Governance
13.2 AI Ethics
13.3 Human-AI Collaboration
13.4 AI & Society
13.5 Society-Related AI Projects
13.6 Singularity
13.7 Our Responsibility to Our Children
- The Future of Jobs
14.1 AI and Job Markets
14.2 What Jobs AI Will Replace
14.3 What Jobs AI Won’t Replace
14.5 The Most In-Demand Future Jobs
- The AI Economy
15.1 Latest Trends in AI
15.1.1 Computer Vision
15.1.2 Generative Adversarial Networks
15.1.3 Natural Language Processing
15.1.4 Training & Deployment of Powerful Models
15.2 AI: Economic Potential
15.3 The AI Patent Race
15.4 AI & Policy Implications
15.4.1 Policy Implications
15.5 Economic and Societal Cost
15.6 Taxing Robots & Universal Basic Income (UBI)
15.6.1 Taxing Robots
15.6.2 Universal Basic Income (UBI)
15.7 Maximizing the AI Benefits
15.8 Private vs. Government Sector
15.9 The AI Start-Up Economy
- Business AI
16.1 What Is In It For Enterprises?
16.2 Why You Need to Adopt AI Fast?
16.3 How to Build Your AI Strategy ?
16.4 The Agile Approach
16.5 Methodologies & Tools
16.6 Best Practices in Developing AI
- Conclusion
Bibliography
Index
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