AI for Social Good : Using Artificial Intelligence to Save the World.

Format:

Book

Author/Creator:

Dodhia, Rahul.

Language:

English

Subjects (All):

Artificial intelligence--Moral and ethical aspects.

Artificial intelligence.

Physical Description:

1 online resource (227 pages)

Edition:

1st ed.

Place of Publication:

Newark : John Wiley & Sons, Incorporated, 2024.

Summary:

"Understand the real power of AI and embrace this new technology to shape the future for the better AI For Social Good bridges the gap between the current state of reality and the incredible potential of AI to change the world. From humanitarian and environmental concerns to advances in art and science, every area of life stands poised to make a quantum leap into the future. The problem? Too few of us really understand how AI works and how to integrate it into our policies and projects. In this book, Rahul Dodhia, Deputy Director of Microsoft's AI for Good Research Lab, offers a nontechnical exploration of artificial intelligence tools--how they're built, what they can and can't do, and the raw material that teaches them what they "know." Readers will also find an inventory of common challenges they might face when integrating AI into their work. Written for policymakers, project managers, and nontechnical leaders who work alongside AI scientists, AI For Social Good provides an overview of how AI became such an important phenomenon, how AI scientists create artificially intelligent systems, and how AI can be used ethically (or unethically) to transform society. You'll also find a discussion of how governments can become more flexible, helping regulations keep up with the fast pace of change in technology."-- Provided by publisher.

Contents:

Cover

Title Page

Copyright Page

Contents

Acknowledgments

About the Author

Introduction

Chapter 1 A Brief History of Artificial Intelligence

How Innovators Throughout History Paved the Way for Modern AI: From Babbage to Turing

Charles Babbage

Ada Lovelace

John von Neumann

Alan Turing

The Emergence of Modern AI

The Dartmouth Conference: A Turning Point

From Optimism to Pessimism: The Story of the AI Winter

The Rise of Expert Systems

AI Revival: A Fitful Resurgence

The Birth of Modern AI

AI Today

Driver of the 21st Century Economy

Final Thoughts

References

Chapter 2 AI Explained: A Non-Technical Guide

Definition of AI

Machine Learning

How Machines Learn

Supervised Learning

Unsupervised Learning

Reinforcement Learning

Neural Networks

Structure of a Neuron

Layers in a Neural Network

Training a Neural Network

Backpropagation: Learning from Mistakes

Beyond Backpropagation

Common Deep Learning Models

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

Transformers

Foundational Models

Handle with Caution

Vision and Sound

Explainable AI

Chapter 3 AI for Good

Responding to Natural Disasters

Floods

SEEDS

Earthquake in Syria and Turkey

Role of AI in Disaster Resiliency

Data for Environment Monitoring

Food and Water Security

Emerging Uses of AI to Combat Food and Water Insecurity

Medicine

Medical Imaging

Pathology

Education

Chapter 4 AI for Good: Pursuit of Scientific Knowledge

Biodiversity

Beluga Whales

Rainforests

Satellites

Bioacoustics

Camera Traps

Proteomics

Astronomy

Chapter 5 When Good AI Goes Bad

The Surveillance Society.

The Dual Nature of AI Drones: Saving Lives or Restricting Freedom?

The Quandary of Facial Recognition

Predictive Policing: Safeguarding Society or Violating Rights?

Surveillance Capitalism

Magnifying Societal Ills

Deepfakes and Disinformation

Image Deepfakes

Automated Misinformation

Checks on Disinformation

Evolution of Cybercrime

Amplifying Discrimination and Social Biases

Gender Bias

Racial Bias

Economic Bias

Chapter 6 Putting Safeguards Around AI

The Need for Ethical Development

Safety and Security

Accountability and Transparency

Data Protection and Privacy

Balancing Innovation and Regulation

Economic and Social Impact

Teachers and Educators

Healthcare Professionals

Office Workers

Manufacturers and Factory Workers

Transportation

Farmers

Creative Professionals

AI Governance

Military Weapons

Finance

Chapter 7 Getting the Best Out of Your AI Team

Roles in an AI Team

A Three-Way Conversation

The Project Manager

The Domain Expert

The AI Expert

Setting Expectations About AI

Case Study: Breast Cancer Example

Project Scoping

The Reality of Running AI: Cost, Connectivity, and Context

Understanding the Role of Environmental Context in AI Deployment

Technology Resources

Data: Quantity and Quality, Annotations, Biases

Type of Data: Format and Relevance

Quality of Data

Quantity of Data

Real-World Examples

Modeling

Accuracy

Accuracy: Balancing Precision and Sensitivity

Human-in-the-loop

Consequences for Wrong Outcomes Are More Severe

Chapter 8 The Future

New Technologies

Quantum Computing

DNA Storage

AI Teams in the Near Future

AI-Specific Jobs

Societal Change

References.

Index

EULA.

Notes:

Includes index.

Description based on publisher supplied metadata and other sources.

Other Format:

Print version: Dodhia, Rahul AI for Social Good

ISBN:

9781394205837

OCLC:

1408383256