Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values
Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve.

When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place.

 

Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values.

 

As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies.

 

This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.
1139026665
Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values
Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve.

When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place.

 

Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values.

 

As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies.

 

This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.
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Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values

Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values

Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values

Doing AI: A Business-Centric Examination of AI Culture, Goals, and Values

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Overview

Artificial intelligence (AI) has captured our imaginations—and become a distraction. Too many leaders embrace the oversized narratives of artificial minds outpacing human intelligence and lose sight of the original problems they were meant to solve.

When businesses try to “do AI,” they place an abstract solution before problems and customers without fully considering whether it is wise, whether the hype is true, or how AI will impact their organization in the long term. Often absent is sound reasoning for why they should go down this path in the first place.

 

Doing AI explores AI for what it actually is—and what it is not— and the problems it can truly solve. In these pages, author Richard Heimann unravels the tricky relationship between problems and high-tech solutions, exploring the pitfalls in solution-centric thinking and explaining how businesses should rethink AI in a way that aligns with their cultures, goals, and values.

 

As the Chief AI Officer at Cybraics Inc., Richard Heimann knows from experience that AI-specific strategies are often bad for business. Doing AI is his comprehensive guide that will help readers understand AI, avoid common pitfalls, and identify beneficial applications for their companies.

 

This book is a must-read for anyone looking for clarity and practical guidance for identifying problems and effectively solving them, rather than getting sidetracked by a shiny new “solution” that doesn’t solve anything.

Product Details

ISBN-13: 9781637740071
Publisher: BenBella Books, Inc.
Publication date: 12/14/2021
Sold by: SIMON & SCHUSTER
Format: eBook
Pages: 272
File size: 1 MB

About the Author

Richard Heimann is Chief AI Officer at Cybraics Inc. A fully managed cybersecurity company focusing on advanced threat detection, Cybraics was founded in 2014 and operationalized many years of machine learning research conducted at the Defense Advanced Research Projects Agency (DARPA).

Heimann is a former chief data scientist and technical fellow at L-3 National Security Solutions; former adjunct faculty at the University of Maryland, Baltimore County, where he taught graduate-level spatial econometrics and statistical reasoning; and an instructor at George Mason University, where he taught computational social science. He continues to be an advisor at George Mason University’s DataLab and several early-stage artificial intelligence ventures. Heimann has also performed on DARPA’s Nexus 7 program supporting ISAF and 82nd Airborne Division in Kandahar Afghanistan, the Naval Research Laboratory, and also consulted at the Pentagon on various AI projects and AI strategy.

Richard Heimann is Chief AI Officer at Cybraics Inc. A fully managed cybersecurity company focusing on advanced threat detection, Cybraics was founded in 2014 and operationalized many years of machine learning research conducted at the Defense Advanced Research Projects Agency (DARPA).

Heimann is a former chief data scientist and technical fellow at L-3 National Security Solutions; former adjunct faculty at the University of Maryland, Baltimore County, where he taught graduate-level spatial econometrics and statistical reasoning; and an instructor at George Mason University, where he taught computational social science. He continues to be an advisor at George Mason University’s DataLab and several early-stage artificial intelligence ventures. Heimann has also performed on DARPA’s Nexus 7 program supporting ISAF and 82nd Airborne Division in Kandahar Afghanistan, the Naval Research Laboratory, and also consulted at the Pentagon on various AI projects and AI strategy.

Table of Contents

Foreword xi

Introduction 1

Part 1 Understanding AI

Chapter 1 So, What Is Al? Seeing Al Through a Business Lens 7

Chapter 2 Isn't There More Than One Kind of Al? 35

Chapter 3 When All You Have is Silver-Bullet Thinking 49

Chapter 4 All We Need Is More Time 95

Chapter 5 Solution Arguing: A Lesson in Culture, Conflict, and Spillovers 119

Chapter 6 Human Measuring Sticks 139

Chapter 7 Al Theater and Chilly Winters 157

Part 2 Problems and Problem Solving with AI

Chapter 8 Not All Problems Are Created Equally 167

Conclusion 237

Acknowledgments 243

Index 245

About the Author 259

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