Table Of ContentMODELING HUMAN–SYSTEM
INTERACTION
StevenS InStItute SerIeS on Complex SyStemS
and enterprISeS
William B. rouse, Series editor
WILLIAM B. ROUSE
modeling and visualization of Complex Systems and enterprises
ELISABETH PATE‐CORNELL, WILLIAM B. ROUSE, AND CHARLES M. VEST
perspectives on Complex Global Challenges: education, energy, Healthcare,
Security, and resilience
WILLIAM B. ROUSE
universities as Complex enterprises: How academia Works, Why It Works
these Ways, and Where the university enterprise Is Headed
THOMAS B. SHERIDAN
modeling Human–System Interaction: philosophical and methodological
Considerations, with examples
MODELING
HUMAN–SYSTEM
INTERACTION
Philosophical and Methodological Considerations,
with Examples
THOMAS B. SHERIDAN
Copyright © 2017 by John Wiley & Sons, Inc. All rights reserved
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Library of Congress Cataloging‐in‐Publication Data:
Names: Sheridan, Thomas B., author.
Title: Modeling human-system interaction : philosophical and
methodological considerations, with examples / Thomas B. Sheridan.
Description: Hoboken, New Jersey : John Wiley & Sons, [2017] |
Series: Stevens Iinstitute series on complex systems and enterprises |
Includes bibliographical references and index.
Identifiers: LCCN 2016038455 (print) | LCCN 2016051718 (ebook) |
ISBN 9781119275268 (cloth) | ISBN 9781119275299 (pdf) |
ISBN 9781119275282 (epub)
Subjects: LCSH: Human-computer interaction. |
User-centered system design.
Classification: LCC QA76.9.H85 S515 2017 (print) |
LCC QA76.9.H85 (ebook) | DDC 004.01/9–dc23
LC record available at https://lccn.loc.gov/2016038455
Cover Image: Andrey Prokhorov/Gettyimages
Set in 11/13pt Times by SPi Global, Pondicherry, India
Printed in the United States of America
10 9 8 7 6 5 4 3 2 1
cONTeNTS
Preface xi
Introduction 1
1 Knowledge 5
Gaining New Knowledge, 5
Scientific Method: What Is It?, 7
Further Observations on the Scientific Method, 8
Reasoning Logically, 10
Public (Objective) and Private (Subjective) Knowledge, 11
The Role of Doubt in Doing Science, 11
Evidence: Its use and Avoidance, 12
Metaphysics and its Relation to Science, 12
Objectivity, Advocacy, and Bias, 13
Analogy and Metaphor, 14
2 What is a Model? 17
Defining “Model”, 17
Model Attributes: A New Taxonomy, 20
Examples of Models in Terms of the Attributes, 25
Why Make the Effort to Model?, 27
Attribute Considerations in Making Models Useful, 27
vi CONTENTS
Social Choice, 30
What Models are Not, 31
3 Important Distinctions in Modeling 33
Objective and Subjective Models, 33
Simple and Complex Models, 35
Descriptive and Prescriptive (Normative) Models, 36
Static and Dynamic Models, 36
Deterministic and Probabilistic Models, 36
Hierarchy of Abstraction, 37
Some Philosophical Perspectives, 38
4 forms of representation 41
Verbal Models, 41
Graphs, 42
Maps, 44
Schematic Diagrams, 45
Logic Diagrams, 46
Crisp Versus Fuzzy Logic (see also Appendix, Section “Mathematics
of Fuzzy Logic”), 48
Symbolic Statements and Statistical Inference (see also Appendix,
Section “Mathematics of Statistical Inference
From Evidence”), 50
5 acquiring Information 51
Information Communication (see also Appendix, Section
“Mathematics of Information Communication”), 51
Information Value (see also Appendix, Section “Mathematics
of Information Value”), 53
Logarithmic‐Like Psychophysical Scales, 54
Perception Process (see also Appendix, Section “Mathematics
of the Brunswik/Kirlik Perception Model”), 54
Attention, 55
Visual Sampling (see also Appendix, Section “Mathematics of How
Often to Sample”), 56
Signal Detection (see also Appendix, Section “Mathematics of Signal
Detection”), 58
Situation Awareness, 59
Mental Workload (see also Appendix, Section “Research Questions
Concerning Mental Workload”), 60
CONTENTS vii
Experiencing What is Virtual: New Demands for Human–System
Modeling (see also Appendix, Section “Behavior Research Issues
in Virtual Reality”), 64
6 analyzing the Information 69
Task Analysis, 69
Judgment Calibration, 70
Valuation/Utility (see also Appendix, Section “Mathematics
of Human Judgment of Utility”), 72
Risk and Resilience, 73
Definition of Risk, 73
Meaning of Resilience, 73
Trust, 75
7 Deciding on action 77
What is Achievable, 77
Decision Under Condition of Certainty
(see also Appendix, Section “Mathematics of Decisions Under
Certainty”), 78
Decision Under Condition of Uncertainty
(see also Appendix, Section “Mathematics of Decisions Under
Uncertainty”), 79
Competitive Decisions: Game Models (see also Appendix
“Mathematics of Game Models”), 79
Order of Subtask Execution, 80
8 Implementing and evaluating the action 83
Time to Make a Selection, 83
Time to Make an Accurate Movement, 84
Continuous Feedback Control (see also Appendix, Section
“Mathematics of Continuous Feedback Control”), 85
Looking Ahead (Preview Control) (see also Appendix, Section
“Mathematics of Preview Control”), 87
Delayed Feedback, 88
Control by Continuously Updating an Internal Model (see also
Appendix, Section “Stepping Through the Kalman Filter
System”), 88
Expectation of Team Response Time, 90
Human Error, 91
viii CONTENTS
9 Human–automation Interaction 95
Human–Automation Allocation, 95
Supervisory Control, 96
Trading and Sharing, 98
Adaptive/Adaptable Control, 101
Model‐Based Failure Detection, 102
10 Mental Models 105
What is a Mental Model?, 105
Background of Research on Mental Models, 106
ACT‐R, 108
Lattice Characterization of a Mental Model, 110
Neuronal Packet Network as a Model of Understanding, 112
Modeling of Aircraft Pilot Decision‐Making Under Time Stress, 113
Mutual Compatibility of Mental, Display, Control, and Computer
Models, 114
11 can cognitive engineering Modeling
contribute to Modeling Large‐Scale
Socio‐Technical Systems? 115
Basic Questions, 115
What Large‐Scale Social Systems are we Talking About?, 116
What Models?, 120
Potential of Feedback Control Modeling of Large‐Scale Societal
Systems, 122
The STAMP Model for Assessing Errors in Large‐Scale Systems, 122
Past World Modeling Efforts, 123
Toward Broader Participation, 124
aPPeNDIX 129
Mathematics of Fuzzy Logic, 129
Mathematics of Statistical Inference from Evidence, 131
Mathematics of Information Communication, 132
Mathematics of Information Value, 134
Mathematics of the Brunswik/Kirlik Perception Model, 135
Mathematics of How Often to Sample, 136
Mathematics of Signal Detection, 138
Research Questions Concerning Mental Workload, 141
Behavior Research Issues in Virtual Reality, 144
CONTENTS ix
Mathematics of Human Judgment of Utility, 146
Mathematics of Decisions Under Certainty, 147
Mathematics of Decisions Under Uncertainty, 149
Mathematics of Game Models, 150
Mathematics of Continuous Feedback Control, 152
Mathematics of Preview Control, 153
Stepping Through the Kalman Filter System, 154
refereNceS 159
INDeX 167
PREFACE
This book has evolved from a professional lifetime of thinking about models
and, more generally, thinking about thinking. I have previously written seven
books over a span of 42 years, and they all have all talked about models,
except for one privately published as a memoir for my family. One even dealt
with the concept of God and whether God is amenable to modeling (mostly
no). So what is new or different in the present book?
The book includes quite a bit of the philosophy of science and the scientific
method as a precursor to discussing human–system models. Many aspects of
modeling are discussed: the purpose and uses of models for doing science
and thinking about the world and examples of different kinds of models in what
has come to be called human–system interaction or cognitive engineering.
Along with new material, the book also includes many modeling ideas previ-
ously discussed by the author. When not otherwise cited, illustrations were
drawn by the author for the book or were original works under the author’s
copyright or previously declared by the author to be in public domain prior to
publication.
I gratefully acknowledge contributions to these ideas from many c olleagues
I have worked with, especially Neville Moray, who has been my friend and
invaluable critic over the years, and Bill Rouse, who shepherded the book as
Wiley series editor. Modeling contributions of past coauthors Russ Ferrell,
Bill Verplank, Gunnar Johannsen, Toshi Inagaki, Raja Parasuraman, Chris
