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Working with AI

Real Stories of Human-Machine Collaboration

Part of Management on the Cutting Edge

Author Thomas H. Davenport, Steven M. Miller
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Hardcover
$34.95 US
The MIT Press
On sale Sep 27, 2022 | 312 Pages | 978-0-262-04724-1
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Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings.

This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. 
 
These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.
Series Foreword ix
Introduction xi
I Case Studies
Morgan Stanley: Financial Advisors and the Next Best Action System 3
ChowNow: Growth Operations and RingDNA 9
Stitch Fix: AI-Assisted Clothing Stylists 15
Arkansas State University: Fundraising with Gravyty 21
Shopee: The Product Manager's Role in AI-Driven E-Commerce 27
Haven Life and MassMutual: The Digital Life Underwriter 35
Radius Financial Group: Intelligent Mortgage Processing 41
DBS Bank: AI-Driven Transaction Surveillance 47
Medical Diagnosis and Treatment Record Coding with AI 53
Dentsu: RPA for Citizen Automation Developers 59
84.51° and Kroger: AutoML to Improve Data Science Productivity 67
Mandiant: AI Support for Cyberthreat Attribution 75
DBS Digibank India: Customer Science for Customer Service 83
Intuit: AI-Assisted Writing with Writer.com 89
Lilt: The Computer-Assisted Translator 95
Salesforce: Architects of Ethical AI Practices 101
The Dermatologist: AI-Assisted Skin Imaging 109
Good Doctor Technology: Intelligent Telemedicine in Southeast Asia 115
Osler Works: The Transformation of Legal Services Delivery 125
PBC Linear: AI-Enabled Virtual Reality for Employee Training 131
Seagate: Improving Automated Visual Inspection of Wafers and Fab Tooling with AI 137
Stanford Health Care: Robotic Pharmacy Operations 141
Fast Food Hamburger Outlets: Flippy--Robotic Assistants for Fast Food Preparation 147
FarmWise: Digital Weeders for Robotic Weeding of Farm Fields 151
Wilmington, North Carolina, Police Department: AI-Driven Policing 155
Certis: AI Support for the Multifaceted Security Guard at Jewel Changi Airport 161
Southern California Edison: Machine Learning Safety Data Analytics for Front-Line Accident Prevention 169
Massachusetts Bay Transportation Authority: AI-Assisted Diesel Oil Analysis for Train Maintenance 175
Singapore Land Transport Authority: Rail Network Management in a Smart City 179
II Insights
It Takes a Village to Change a Job with AI 187
Everybody's a Techie--Or at Least Has a Hybrid Job Role 201
The Platforms That Make AI Work 209
Intelligent Case Management Systems 217
Opportunities for Entry-Level Workers: Diminishing or Not? 225
Remote and Independent Work 239
What Machines Can't Do (Yet) 249
III Conclusions 
Looking Ahead to the Future of Work with Smart Machines 259
Notes 267
Index 279
Thomas H. Davenport is Distinguished Professor of Information Technology and Management at Babson College, Visiting Professor at Oxford’s Saïd Business School, Fellow of the MIT Initiative on the Digital Economy, and Senior Advisor to Deloitte’s AI practice. He is the author of The AI Advantage (MIT Press) and coauthor of Only Humans Need Apply and other books.
 
Steven M. Miller is Professor Emeritus of Information Systems at Singapore Management University, where he previously served as Founding Dean of the School of Computing and Information System Vice Provost for Research. He is coauthor of Robotics Applications and Social Implications.
 
 
Thomas H. Davenport View titles by Thomas H. Davenport
Steven M. Miller View titles by Steven M. Miller

About

Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings.

This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers. 
 
These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.

Table of Contents

Series Foreword ix
Introduction xi
I Case Studies
Morgan Stanley: Financial Advisors and the Next Best Action System 3
ChowNow: Growth Operations and RingDNA 9
Stitch Fix: AI-Assisted Clothing Stylists 15
Arkansas State University: Fundraising with Gravyty 21
Shopee: The Product Manager's Role in AI-Driven E-Commerce 27
Haven Life and MassMutual: The Digital Life Underwriter 35
Radius Financial Group: Intelligent Mortgage Processing 41
DBS Bank: AI-Driven Transaction Surveillance 47
Medical Diagnosis and Treatment Record Coding with AI 53
Dentsu: RPA for Citizen Automation Developers 59
84.51° and Kroger: AutoML to Improve Data Science Productivity 67
Mandiant: AI Support for Cyberthreat Attribution 75
DBS Digibank India: Customer Science for Customer Service 83
Intuit: AI-Assisted Writing with Writer.com 89
Lilt: The Computer-Assisted Translator 95
Salesforce: Architects of Ethical AI Practices 101
The Dermatologist: AI-Assisted Skin Imaging 109
Good Doctor Technology: Intelligent Telemedicine in Southeast Asia 115
Osler Works: The Transformation of Legal Services Delivery 125
PBC Linear: AI-Enabled Virtual Reality for Employee Training 131
Seagate: Improving Automated Visual Inspection of Wafers and Fab Tooling with AI 137
Stanford Health Care: Robotic Pharmacy Operations 141
Fast Food Hamburger Outlets: Flippy--Robotic Assistants for Fast Food Preparation 147
FarmWise: Digital Weeders for Robotic Weeding of Farm Fields 151
Wilmington, North Carolina, Police Department: AI-Driven Policing 155
Certis: AI Support for the Multifaceted Security Guard at Jewel Changi Airport 161
Southern California Edison: Machine Learning Safety Data Analytics for Front-Line Accident Prevention 169
Massachusetts Bay Transportation Authority: AI-Assisted Diesel Oil Analysis for Train Maintenance 175
Singapore Land Transport Authority: Rail Network Management in a Smart City 179
II Insights
It Takes a Village to Change a Job with AI 187
Everybody's a Techie--Or at Least Has a Hybrid Job Role 201
The Platforms That Make AI Work 209
Intelligent Case Management Systems 217
Opportunities for Entry-Level Workers: Diminishing or Not? 225
Remote and Independent Work 239
What Machines Can't Do (Yet) 249
III Conclusions 
Looking Ahead to the Future of Work with Smart Machines 259
Notes 267
Index 279

Author

Thomas H. Davenport is Distinguished Professor of Information Technology and Management at Babson College, Visiting Professor at Oxford’s Saïd Business School, Fellow of the MIT Initiative on the Digital Economy, and Senior Advisor to Deloitte’s AI practice. He is the author of The AI Advantage (MIT Press) and coauthor of Only Humans Need Apply and other books.
 
Steven M. Miller is Professor Emeritus of Information Systems at Singapore Management University, where he previously served as Founding Dean of the School of Computing and Information System Vice Provost for Research. He is coauthor of Robotics Applications and Social Implications.
 
 
Thomas H. Davenport View titles by Thomas H. Davenport
Steven M. Miller View titles by Steven M. Miller

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