People Are Like Plutonium

Abstract

An analogy is drawn between the study of human behavior and the study of plutonium to demonstrate that "soft" and "hard" sciences are more similar than different, making the distinction moot and unproductive. We provide evidence for this proposition by showing that the study of human behavior, which is typically perceived as a soft science, mirrors research conducted in other scientific fields such as engineering, physics, and chemistry commonly considered hard sciences. The essence of the argument centers around efforts during the U.S. Manhattan Project to understand plutonium well enough for use in an atomic weapon that would end World War II. Initially, the element seemed very perplexing and unknowable, with no consistency in density measurements across time or samples. Eventually, Manhattan Project scientists learned the variability in density was due to the different phases the plutonium element assumes, depending on environmental temperature. Suddenly, the behavior of plutonium became less perplexing and more predictable. Like plutonium, human behavior can seem perplexing, random, and wholly unpredictable on the surface, particularly to lay persons outside the field. However, like plutonium, the predictability in human behavior can be uncovered through extensive study and rigorous experimentation. The primary implication from this analogy is that scientists in all disciplines should eradicate the distinction between soft and hard sciences altogether because it only hinders the collaboration necessary to promote high-quality interdisciplinary research for tackling the difficult sociotechnical problems of the future.

Full text

Sandia National Laboratories is a multimission laboratory
managed and operated by National Technology and Engineering
Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell
International Inc., for the U.S. Department of Energy’s National
Nuclear Security Administration under contract DE-NA0003525.
People Are Like Plutonium
Judi E. See, Robert B. Rosenfeld, Sylvester Taylor, and K. M. Wedic
August 2022

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ABSTRACT
An analogy is drawn between the study of human behavior and the study of plutonium to
demonstrate that “soft” and “hard” sciences are more similar than different, making the distinction
moot and unproductive. We provide evidence for this proposition by showing that the study of
human behavior, which is typically perceived as a soft science, mirrors research conducted in other
scientific fields such as engineering, physics, and chemistry commonly considered hard sciences. The
essence of the argument centers around efforts during the U.S. Manhattan Project to understand
plutonium well enough for use in an atomic weapon that would end World War II. Initially, the
element seemed very perplexing and unknowable, with no consistency in density measurements
across time or samples. Eventually, Manhattan Project scientists learned the variability in density was
due to the different phases the plutonium element assumes, depending on environmental
temperature. Suddenly, the behavior of plutonium became less perplexing and more predictable.
Like plutonium, human behavior can seem perplexing, random, and wholly unpredictable on the
surface, particularly to lay persons outside the field. However, like plutonium, the predictability in
human behavior can be uncovered through extensive study and rigorous experimentation. The
primary implication from this analogy is that scientists in all disciplines should eradicate the
distinction between soft and hard sciences altogether because it only hinders the collaboration
necessary to promote high-quality interdisciplinary research for tackling the difficult sociotechnical
problems of the future.

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ACKNOWLEDGEMENTS
This paper was a collaboration between Sandia National Laboratories and Idea Connection Systems,
Inc. Sandia National Laboratories (SNL) is one of 17 national laboratories under the Department of
Energy (DOE). For more than 70 years, SNL has been a premier science and engineering laboratory
for national security and technology innovation. SNL has two principal locations in Albuquerque,
New Mexico, and Livermore, California.
Idea Connection Systems, Inc. (ICS) is a management consulting firm founded by Robert Rosenfeld
in 1988. ICS specializes in the human dynamics of innovation and educating organizations how to
leverage individual potential to foster change and innovation. ICS is located in Rochester, New
York.
The authors would like to acknowledge the following individuals who peer reviewed drafts of this
paper and took the time to explain their feedback:
 Mark Ackermann, Sandia National Laboratories
 Richard Craft, Sandia National Laboratories
 Peter Engstrom, Air Force Colonel (Retired), Government Consultant
 Mary Margaret Evans, Parallax Research
 Andrew Harrison, Idea Connection Systems, Inc.
 Marty Harrison, Independent Thinker and Problem Solver
 Richard Joseph, Former Chief Scientist of the Air Force (2018 – 2021) (Retired)
 Gerry Yonas, Sandia National Laboratories (Retired)
Correspondence concerning this paper should be addressed to:
Judi E. See https://orcid.org/0000-0002-4089-5609
Sandia National Laboratories, P.O. Box 5800, MS 0151, Albuquerque, NM 87185-0151
E-mail: jesee@sandia.gov
Phone: 505-844-4567

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CONTENTS

Abstract ............................................................................................................................................................... 3
Acknowledgements ............................................................................................................................................ 4
Executive Summary ........................................................................................................................................... 7
Acronyms and Definitions ............................................................................................................................... 9
1.Introduction ............................................................................................................................................... 13
2.Understanding Plutonium ........................................................................................................................ 15
2.1.Chaos ................................................................................................................................................ 16
2.2.Initial Clarity .................................................................................................................................... 16
2.3.Continued Clarity ............................................................................................................................ 17
2.4.New Frontiers in the Study of Plutonium ................................................................................... 17
3.Understanding Human Behavior ............................................................................................................ 21
3.1.Phases of Human Growth and Development ............................................................................ 21
3.2.Properties of Human Beings ......................................................................................................... 21
3.3.Human Behavior Handbooks ....................................................................................................... 24
3.4.Human Aging .................................................................................................................................. 24
3.5.Compatibilities in Human Interactions ....................................................................................... 25
3.6.Human Substitutes for Experimentation .................................................................................... 27
3.7.Role of Luck in Psychological Research ...................................................................................... 28
3.8.New Frontiers in the Study of Human Behavior ....................................................................... 29
4.Implications Of The Analogy .................................................................................................................. 31
4.1.Recognize the Growing Interdisciplinarity of Scientific Research .......................................... 31
4.2.Embrace the Role of Judgment in All Scientific Endeavors .................................................... 32
4.3.Acknowledge the Importance of Human Behavior for All Scientific Disciplines ................ 34
4.4.Eliminate the Soft vs. Hard Distinction ...................................................................................... 35
5.Conclusion ................................................................................................................................................. 37
References ......................................................................................................................................................... 39


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LIST OF FIGURES
Figure 1. Current and Alternative Views of Scientific Disciplines ............................................................. 8 
Figure 2. Traditional Ranking of Scientific Disciplines on the Hard-to-Soft Continuum .................... 13
Figure 3. Plutonium—Element 94 in the Periodic Table .......................................................................... 15
Figure 4. Properties of Plutonium Studied During World War II ............................................................ 16
Figure 5. Six Phases of Plutonium ................................................................................................................. 18
Figure 6. Phases of Human Development Over the Lifespan .................................................................. 21
Figure 7. Properties of Human Beings ......................................................................................................... 22
Figure 8. Visible and Invisible Human Properties ...................................................................................... 22
Figure 9. Visible Light in the Electromagnetic Spectrum .......................................................................... 23
Figure 10. Three Aspects of Mental Functioning ....................................................................................... 25
Figure 11. Three Basic Approaches to Innovation ..................................................................................... 26
Figure 12. PERMA Model of Positive Psychology ..................................................................................... 29
Figure 13. Alternative View of Relationships Among Scientific Disciplines .......................................... 36
LIST OF TABLES
Table 1. Parallels Between Plutonium and Human Behavior ..................................................................... 7
Table 2. Human Behavior Handbooks ......................................................................................................... 24
Table 3. Partial ISPITM Totem for Extreme Pioneer with Revolutionary Approach to Innovation.... 26

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EXECUTIVE SUMMARY
Proposition
The “soft” and “hard” sciences are more similar than different. Scientists in all disciplines should
eradicate this distinction altogether because it only hinders the collaboration necessary to promote
high-quality interdisciplinary research for tackling the difficult sociotechnical problems of the future.
Evidence
Evidence for this proposition is provided via an analogy between the study of human behavior and
the study of plutonium, which demonstrates the parallels between these two ostensibly unrelated
scientific disciplines (see Table 1). The materials differ, but thought processes and methodologies
used to study them are comparable. During the initial World War II studies of plutonium, the
element seemed perplexing and unknowable, with no consistency in density measurements across
time or samples. Yet, with rigorous study and experimentation, the initial chaos and variability
became manageable and predictable. In much the same way, the predictability in seemingly random
human behavior can be understood through rigorous study and experimentation.
Table 1. Parallels Between Plutonium and Human Behavior
Feature Understandin
g
Plutonium Understandin
g
Human Behavio
r
Scientific Research Cycle
Initial Chaos Wide range of values in density
measurements was bafflin
g
Behavior appears random and
unpredictable to la
y
persons
Rigorous Study
Variability in density measurements
becomes predictable when linked to
temperature variations
Bounds on human behavior and
properties become understood over time
Mastery Original two-volume plutonium handbook
expanded into seven volumes
Multiple handbooks characterize a vast
and
g
rowin
g
bod
y
of knowled
g
e
New Frontiers Seventh phase of plutonium was
demonstrated in 1970
New knowledge and new domains of
stud
y
routinel
y
emer
g
e
Other Parallels
Phases Variability in density and other properties
is due to different phases
Humans exhibit phase changes such as
variations in hei
g
ht over the lifespan
Compatibilities Combining plutonium with select
elements enhances its stabilit
y
The right combination of people for a
g
iven ob
j
ective must often be identified
Substitutes Testing was conducted first on more
widel
y
available materials like uranium
Animal studies have been instrumental in
understandin
g
human behavior
Role of Luck “Lucky” choices for plutonium stabilizers
came from knowin
g
the periodic table
Serendipitous findings attributed to luck
stem from a prior wealth of knowled
g
e
Aging Plutonium aging depends partially on
phase
Mental and physical aging differ,
dependin
g
on
g
enetics and environmen
t
Implications
The analogy between the study of plutonium and the study of human behavior has four important
implications.

Interdisciplinarity of Scientific Research:
the growing interdisciplinarity of scientific
research requires effective collaboration across disciplines. A focus on similarities rather than
differences among researchers from different disciplines is necessary.

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
Role of Judgment in Science:
judgment and subjectivity are inherent in all scientific
endeavors and are not confined to the social and behavioral sciences, as commonly
perceived. However, subjectivity does not necessarily imply a lack of scientific rigor. It
should be embraced and leveraged because it can contribute to novel hypotheses,
progression of ideas, and serendipitous findings.

Importance of Human Behavior for All Scientific Disciplines:
human behavior is a
significant driver in many areas and is not confined to the social and behavioral sciences.
Most critical problems of the future represent “wicked” sociotechnical problems that cannot
be solved by approaching them from only a technical perspective. They require increased
focus on the people in the system. Further, scientists in all disciplines must understand and
apply key principles from the social and behavioral sciences to succeed in today’s
collaborative workplace and support a range of innovation approaches.

Soft vs. Hard Distinction:
the soft vs. hard distinction should be eradicated altogether
because it no longer serves a purpose and creates unnecessary barriers that cause more harm
than good. Eliminating the soft vs. hard distinction opens the door for more robust and
inclusive collaboration that leverages the strengths of multiple disciplines.
Recommendation
Ultimately, we propose replacing the current segregated view of science, with its ranking of scientific
disciplines on the hard-to-soft continuum, with an alternative view (see Figure 1). This alternative
view emphasizes the existence of fuzzy rather than distinct boundaries among the various disciplines
as well as their overlaps and interconnections, in something akin to a neural network. This
alternative view highlights the interconnections that permeate science rather than focusing on
stringent black-and-white distinctions and narrow definitions that may be used to erect barriers
among disciplines and hinder interdisciplinary collaboration.
Figure 1. Current and Alternative Views of Scientific Disciplines

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ACRONYMS AND DEFINITIONS
Abbreviation Definition
A
AAS
A
merican Association for the
A
dvancement of Science
A
M
A
mplitude Modulation
DN
A
Deox
y
ribonucleic Acid
DOE Department of Ener
gy
FM Frequenc
y
Modulation
ICS Idea Connection S
y
stems, Inc.
ISPITM Innovation Stren
g
ths Preference Indicator
®
n.d. No Date
PERM
A
Positive emotions, En
g
a
g
ement, Relationships, Meanin
g
, Accomplishment
Pu Plutonium
SNL Sandia National Laboratories
TV Television
UV Ultraviole
t

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“
Good writing does not succeed or fail on the strength of its ability to
persuade…It succeeds or fails on the strength of its ability to engage you and
to make you think.
”
Malcolm Gladwell, 2009, p. xv

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1. INTRODUCTION
At its most basic level, science may be viewed as the pursuit of knowledge regarding the universe
and its constituent elements. Given the vastness of the universe, specialized scientific disciplines
have emerged to focus research efforts on particular aspects of the universe. In general, modern
scientific disciplines can be divided into three branches: (1) natural (e.g., biology, chemistry, and
physics), (2) social (e.g., psychology, sociology, and economics), and (3) formal (logic, mathematics,
and theoretical computer science) (Cohen, 2021). Colloquially, scientists have created their own caste
system in which the various scientific disciplines are categorized as either “soft” or “hard” (see
Figure 2). Disciplines in the natural sciences such as engineering, physics, chemistry, and astronomy
are considered hard sciences because they are perceived to have greater methodological rigor,
precision, and objectivity. Although not shown in Figure 2, disciplines in the formal sciences such as
mathematics are viewed as belonging at the hard end of the spectrum for the same reason.
Disciplines in the social and behavioral sciences such as psychology, sociology, and anthropology are
considered soft sciences because they are perceived to be deficient with respect to methodological
rigor, precision, and objectivity. Sometimes, a third category of “medium” sciences is used to
represent disciplines within the natural sciences like the biological sciences that do not fit neatly at
either end of the spectrum shown in Figure 2 (Shermer, 2007).
Figure 2. Traditional Ranking of Scientific Disciplines on the Hard-to-Soft Continuum
This informal differentiation between soft and hard sciences has become part of everyday parlance
in scientific circles, used primarily by those who perceive themselves to be on the hard side of the
fence (VanLandingham, 2014). The terminology is typically used pejoratively, often resulting in a
demeaning and dismissive attitude toward the soft sciences. Many hard scientists tend to view the
study of human behavior as too “soft and squishy” to be taken as seriously as the study of hard
sciences (VanLandingham, 2014, p. 124). The end result is that so-called soft sciences may be
implicitly considered less legitimate scientific disciplines or not part of science at all (Emeagwali,
2013).
Such pervasive perceptions can have undesirable impacts of many types. As just one example,
engineering teams responsible for the design and development of a new product are typically
comprised of subject matter experts who are comfortable managing the technological components
but loathe to deal with the human component of the system (Schatz, 2016). This imbalance is due in
part to differences in the ways in which the various components of a system—technologies, people,
processes—are frequently perceived. Namely, there is a tendency to think that the technological

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components belong in the realm of an objective reality that is known, knowable, and quantifiable,
independent of the mind; whereas human behavior is viewed as unpredictable and impossible to
characterize quantitatively, with interpretation subject to the whims of the observer. The result, in
many cases, is that engineering teams neglect the human component of a system and devote
relatively less attention to it until after fielding when human error begins to occur (Pew & Mavor,
2007; Schatz, 2016). A common perception is that people can then be trained to overcome any
engineering deficiencies that arose from designing equipment for technical excellence but not giving
much thought to facilitating human use by accommodating known human limitations and
capabilities. In this case, as in many others, the reluctance to incorporate critical information from
the soft sciences can be detrimental to overall progress.
We contend that the study of human behavior mirrors research conducted in other scientific fields
such as engineering, physics, and chemistry commonly thought to constitute hard sciences. In
particular, we draw an analogy between the study of human behavior and the study of the chemical
element plutonium to illustrate our proposition. Our purpose is to demonstrate that the soft and
hard sciences are, in fact, more similar than different.

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2. UNDERSTANDING PLUTONIUM
The United States launched the Manhattan Project in 1942 with the intent of developing an atomic
weapon that would bring World War II to an end. At that time, very little was known about
plutonium, aside from basic nuclear properties such as the number of protons and neutrons inside
the nucleus of the plutonium atom and the resulting atomic and mass numbers of naturally
occurring plutonium (see Figure 3). Plutonium was the chemical element that had been identified as
the most viable candidate for use as a fissile fuel in the atomic bomb. At that time, however, “the
incredible, confounding complexity of plutonium—something well recognized today—was
completely unknown to the pioneers of the Manhattan Project” (Martz, Freibert, & Clark, 2021, p.
S267). As Los Alamos National Laboratory metallurgist Siegfried Hecker (2000) would later describe
it, “plutonium is an element at odds with itself—with little provocation, it can change its density by
as much as 25 percent; it can be as brittle as glass or as malleable as aluminum; it expands when it
solidifies; and its freshly-machined silvery surface will tarnish in minutes” (p. 291). Nothing was
known about these properties prior to World War II. Basic knowledge about plutonium not only
had to be acquired rapidly but also applied at an equally feverish pace in order to develop a practical
air-dropped munition that could be deployed successfully in wartime to defeat Axis powers, with
Germany as the initial envisioned target and Japan as the eventual target.
Figure 3. Plutonium—Element 94 in the Periodic Table

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2.1. Chaos
As the Manhattan Project scientists endeavored to learn more about plutonium, they were
thoroughly baffled by the wide range of values found in initial measurements of the element’s
density and other properties (Martz, Freibert, & Clark, 2021). There seemed to be no consistency in
measurements across time or across multiple samples, and metal samples that underwent similar
treatments yielded vastly different densities. Similar treatments yielded vastly different densities,
ranging from approximately 13 g/cm
3
to more than 22 g/cm
3
(Martz, Freibert, & Clark, 2021).
Scientists could not predict in advance the density that a particular sample at a given point in time
would exhibit, as the values appeared to be random and inexplicable.
2.2. Initial Clarity
After a concerted program of research, experimentation, and analysis; the Manhattan Project
scientists came to understand that the variance in density measurements and other properties was
due to the different phases of the plutonium element. By early 1945, Manhattan Project work had
clearly demonstrated the presence of five phases of pure, unalloyed plutonium (designated as α, β, γ,
δ, and ε phases) based on variations in temperature. The various phases were distinguishable in their
structure and properties such as hardness.
When the decision was made in 1944 to focus further effort exclusively on development of an
implosion design for the nuclear weapon, Manhattan Project scientists devoted their time to more
systematic measurement of the physical properties of plutonium metal. Besides density, other
important chemical and metallurgical properties that characterize plutonium were identified and
examined (see Figure 4). It was discovered that samples of plutonium that differed in terms of
density also differed with respect to mechanical properties. For example, high-density samples were
hard and brittle, whereas low-density samples were softer and more malleable. Knowing the unique
temperature ranges for each phase of plutonium facilitated elucidation of these other physical
properties.
Figure 4. Properties of Plutonium Studied During World War II

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The Manhattan Project scientists followed a program of rigorous experimentation during their study
of plutonium. For example, one technique used to better understand plutonium’s physical properties
was the use of uranium as a substitute, given the scarcity of plutonium at the time. Techniques were
tested and perfected on the more widely available uranium and then transferred for use with
plutonium when it became available and adapted accordingly. Despite such rigor, the scientists also
acknowledged the role of “good old-fashioned luck” throughout their efforts (Martz, Freibert, &
Clark, 2021, p. S267). However, as pointed out in the same article, what seems like luck on the
surface may have had more to do with “excellent preparation and insight intersecting with critical
opportunity” (Martz, Freibert, & Clark, 2021, p. S279). In the case of plutonium, the Manhattan
Project scientists seemed to get several lucky breaks that expedited their ability to understand
plutonium’s intricacies and to incorporate that knowledge into a practical weapon design. For
example, the scientists claimed they “were incredibly lucky in the choices made” when selecting
which elements to study for possible use as a plutonium stabilizer (Martz, Freibert, & Clark, 2021, p.
S276) (see next section). In reality, their selections were not the result of randomly throwing darts at
the periodic table of elements. They narrowed down their choices based on knowledge of the
structure of the periodic table and the properties of elements located in close proximity to one
another within the table, which meant they did not have to work their way through the entire
periodic table before finding a solution.
2.3. Continued Clarity
After understanding plutonium’s basic properties and phases, the Manhattan Project scientists began
focusing on selection of the most appropriate phase of plutonium for use in the atomic bomb. The
plutonium metal had to retain its fabricated shape long enough for deployment to the Pacific theater
of war. The difficulty is that plutonium changes state very readily such that a particular phase might
spontaneously transition to a different phase if the temperature changes, causing warping and
cracking and degrading the implosion process. Scientists soon determined that δ-phase plutonium
would have to be combined with small amounts of other elements to create a more stable alloy and
embarked on a search for the perfect elements. In other words, plutonium alone could not be readily
fabricated into a form that would remain stable enough for approximately six weeks, the estimated
time period needed to produce, transport, assemble, and deploy the weapon. It would have to be
combined with other compatible elements that would enhance stability at room temperature and
prevent transformation to the more brittle α-phase. After considerable testing of various elements,
guided logically by the structure of the periodic table, it was determined that gallium was the
preferred stabilizer for δ-phase plutonium. The plutonium-gallium alloy did not transform, even
after storage at temperatures as low as -75°C for three days (Martz, Freibert, & Clark, 2021).
Additional investigation indicated the alloy was even more stable if subjected to an
“homogenization” treatment wherein it was annealed at 410°C for 16 hours (Martz, Freibert, &
Clark, 2021).
2.4. New Frontiers in the Study of Plutonium
The study of plutonium continues to this day, and new knowledge and understanding routinely
emerge, partially due to continued use of surrogate materials such as tungsten, lead, copper, and gold
to advance our understanding of plutonium behavior (Kramer, 2020). As evidence of the immense
growth in knowledge that has occurred since World War II, the original two-volume handbook for
plutonium produced in 1944 (Thomas & Warner, 1944) has expanded into the seven-volume edition
produced in 2019 (Clark, Geeson, & Hanrahan, Jr., 2019). The new seven-volume handbook
provides a vast amount of information, as compared to what was known about plutonium during

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World War II. Topics covered in the handbook include the discovery of plutonium; properties of
plutonium isotopes; chemistry and properties of plutonium metal and alloys; plutonium aging;
thermodynamic trends of plutonium; plutonium in nuclear fuels; plutonium packaging, storage, and
transportation; nuclear security and safeguards; and techniques for working with plutonium.
Shortly after World War II, the structure of α-phase plutonium and the impacts of this structure on
its properties were determined. The sixth recognized phase of plutonium, the δ’ phase, was not
discovered until well after World War II in 1954 (Martz, Freibert, & Clark, 2021). Figure 5 shows the
now well-recognized densities for six solid phases of plutonium at ambient pressure as a function of
temperature—more phases than any other element in the periodic table. The existence of a seventh
phase of plutonium, designated the ζ-phase, was demonstrated at high temperature and high
pressure in 1970 (Martz, Freibert, & Clark, 2021). Scientists are still working to this day to
understand its structure.
Figure 5. Six Phases of Plutonium
Concerns about the aging of plutonium had their roots in the Manhattan Project. At that time,
however, aging was considered primarily within a very limited timeframe of a few weeks, driven by
the need to keep the plutonium intact only long enough to transport and deploy the weapon
overseas. During the Manhattan Project, it was quickly discovered that aging differs in plutonium,
depending on which phase is involved. For instance, unalloyed α-phase plutonium warped and
cracked after only one day at room temperature. By comparison, unalloyed δ-phase plutonium
remained relatively stable in temperatures ranging from 300°C to 470°C and even more stable for
longer durations when combined with gallium.
Today, aging concerns extend well beyond a few weeks to upwards of 100 years for the plutonium in
stockpiled weapons. Plutonium ages both from the outside in and from the inside out, and reactions
with elements in the environment like oxygen, hydrogen, and water can cause degradations in its
properties from the surface to the interior over time (Hecker, 2000). Additional research has
revealed that plutonium rusts even more than iron when exposed to the atmosphere over time

19
(Hecker & Martz, 2000). In addition to such macroscopic changes, microscopic changes at the
nuclear level also occur in plutonium due to its radioactive nature and interactions with other
components in the weapon (Kramer, 2020). Plutonium’s continuous radioactive decay causes self-
irradiation damage that alters its properties. For example, the alpha decay that occurs over time
produces transmutation products that can affect the bulk properties of plutonium and impact its
phase stability. An increase in americium over time tends to further stabilize δ-phase plutonium
alloys, whereas uranium and neptunium reduce stability.
Despite such advances in knowledge, a great deal remains unknown about aging in plutonium. For
example, there has been little research into plutonium irradiation at ambient temperature. There is
also very little theoretical or experimental knowledge regarding the absorption of oxygen or
hydrogen on the surfaces of the element (Hecker & Martz, 2000). Further, the potential impacts
from electronic effects are poorly understood. As such knowledge gaps are filled, the plutonium
handbook may be updated and perhaps expanded to include an eighth volume.

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3. UNDERSTANDING HUMAN BEHAVIOR
On the surface, human behavior, like plutonium, can seem perplexing and wholly random and
unpredictable. However, as will be described here, human behavior can be variable, but humans are
not random and chaotic organisms. Like plutonium, the predictability in human behavior—the
consistencies and stabilities—can be demonstrated and uncovered through extensive study and
rigorous experimentation.
3.1. Phases of Human Growth and Development
Like plutonium, humans have multiple phases that can be distinguished by physical properties such
as height, weight, and mobility. Figure 6 illustrates just one example of human phase changes over
the lifespan, showing variations in height from infancy through late adulthood. During this time
period, people change in height from approximately 20 inches at birth to an average adult height of
64 inches for females and 69 inches for males. Growth occurs rapidly from infancy through early
childhood. In fact, by the age of five, height has approximately doubled since birth (Graber, 2021).
Growth occurs more gradually throughout childhood until puberty, when both boys and girls
experience growth spurts. People continue to grow in height until about the age of 20. After about
the age of 30, adults may then lose one to two inches in height due to deteriorating joint cartilage
and osteoporosis.
Figure 6. Phases of Human Development Over the Lifespan
3.2. Properties of Human Beings
Like plutonium, people have multiple properties that can be studied to understand both variability
and stabilities in human behavior and characterize human beings (see Figure 7). For many scientists
outside the social and behavioral sciences, one of the most troubling aspects of human behavior is
the widespread variability that seems to characterize humans. However, this variability is no different
from the highly diverse measurements of plutonium density that initially perplexed Manhattan
Project scientists. As with plutonium, human behavior that seems inexplicable and idiosyncratic, or
peculiar to an individual, can also be understood and predicted. For humans, idiosyncratic behavior
can be understood in part based on genetics and in part based on differences in past history (Tatham
& Wanchisen, 1998). Namely, past exposure to different types of reinforcement or pharmaceuticals
can have short-term or permanent impacts on future behavior under a wide range of circumstances.
Behavioral history research is one of the key mechanisms in psychology for understanding and

22
addressing issues of individual differences contributing to variability that appears random, chaotic,
and unpredictable to casual observers.
Figure 7. Properties of Human Beings
Properties of human beings can be arranged along a spectrum ranging from the visible to the
invisible (Rosenfeld, Wilhelmi, & Harrison, 2011) (see Figure 8). For example, people can be
characterized in terms of visible and observable physical properties like height, weight, arm length,
and head circumference. People can also be characterized in terms of invisible cognitive abilities
such as intelligence, problem solving, attention, and learning. Other invisible properties comprise
what is known as human personality and can be characterized by patterns in thinking, feeling, and
behaving. One prominent personality model, the Big Five personality model, identifies five core
elements of personality—extraversion, agreeableness, openness, conscientiousness, and neuroticism
(De Raad, 2000).
Figure 8. Visible and Invisible Human Properties
Note. Adapted from The Invisible Element: A Practical Guide for the Human Dynamics of Innovation (p. 55), by R. B. Rosenfeld,
G. J. Wilhelmi, & A. Harrison, 2011, Innovatus Press. Copyright 2011 by Idea Connection Systems, Inc. Adapted with
permission.

23
For each human property, there are bounds that constrain human behavior, making it knowable and
predictable, in much the same way that temperature bounds constraining the phases of plutonium
made the chemical element understandable after a period of study. For example, with respect to the
human visual sense, people are able to perceive light comprised of wavelengths in the visible portion
of the electromagnetic spectrum (see Figure 9). No human is able to sense wavelengths in the
infrared portion of the spectrum unless the eye is aided with a device like night vision goggles. Such
knowledge provides perfect predictability when it comes to human vision. The human visual system
does not operate randomly, sometimes detecting infrared light and sometimes not. It operates within
parameters that became known after extensive research and analysis. Similarly, humans can hear
sounds within the range of 20 Hz to 20,000 Hz. No human is able to hear sounds in the 60,000 Hz
range that dogs can hear.
Figure 9. Visible Light in the Electromagnetic Spectrum
In people, properties take the form of what are known as traits and states. Traits are stable and
enduring characteristics and patterns of behavior that are manifested consistently across a wide
range of circumstances. For example, with respect to personality, the trait of extraversion represents
a stable and enduring way of behaving and interacting with the world that generally characterizes an
individual throughout the lifespan and across multiple circumstances. That is, an extraverted
individual who is outgoing at work is also likely to be outgoing at home, at the grocery store, and in
restaurants. While some Big Five personality traits like agreeableness and conscientiousness may
exhibit changes later in life, people who begin life as extraverts are likely to remain extraverted as
they age (Allemand, Zimprich, & Hendriks, 2008). Unlike traits, states are temporary conditions
experienced for a short period of time, depending on circumstances (e.g., anxiety before taking a test
required to pass a training course). With respect to emotion, for example, some emotional states take
the form of transitory moods such as anger or sadness that dissipate over time and are replaced by
other emotions.
As with plutonium, human traits and states can be changed with various types of interventions. As
described earlier, the stability of an alloy of δ-phase plutonium and gallium can be enhanced even
further if the alloy undergoes an homogenization treatment. Treatments to change undesirable
human traits and states consist of pharmacological and therapeutic interventions. For instance,
people who consume caffeine can enhance their cognitive abilities by becoming temporarily more
alert. Therapeutic interventions can be used to alter emotional or personality states or traits that
interfere with everyday living; e.g., to treat anger issues or obsessive-compulsive personality traits.

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3.3. Human Behavior Handbooks
Initially, as with plutonium, knowledge of the human body and its properties was scarce. Large
databases of even very basic information about people such as their height and weight did not exist.
Englishman Sir Francis Galton was one of the first psychologists to collect large quantities of human
data. In his case, he capitalized on the 1884 International Health Exhibition in London to set up an
anthropometric laboratory for an orderly and systematic measurement of physical characteristics
such as height, weight, strength, and eyesight. Altogether, he collected data from over 9000
participants in a very short period of time and was able to create a fairly comprehensive statistical
database, paving the way for the collection of more sophisticated data about human behavior and
less visible human properties like motivation and emotion. Today, in a growth trajectory reminiscent
of the expansion of the plutonium handbook from two to seven volumes, there is a vast body of
research on human behavior that is readily available in multiple compendiums (see Table 2).
Table 2. Human Behavior Handbooks
3.4. Human Aging
Like plutonium, whose aging depends on which phase is involved, people age differently depending
on both genetics and environment. Akin to the rusting that occurs in plutonium in moist air,
“rusting” in the human body occurs both physically and mentally. Many physical changes occur over

25
time, some of which are readily observable at a macroscopic level. Other less-observable changes
occur at microscopic levels. Hair loses its color. Skin wrinkles and sags. Muscle loss increases. Bones
become more brittle. Battle scars from living increase—physical scars and disfigurements as a result
of injuries and surgical procedures. Deterioration in once-limber joints hinders mobility and
dexterity. Reduced elasticity in the lens of the eye distorts near vision. Whereas most teenagers can
hear sounds at 17,400 Hz, older adults may no longer be able to detect any frequencies above 12,000
Hz. Reaction times slow. Reductions in brain mass occur, with cerebrospinal fluid filling gaps left by
thinning gray matter. Memory deteriorates, making it more difficult to retrieve facts and names.
Degradations in short-term memory become more common as people age, and older adults are less
capable of successfully dividing their attention among multiple tasks.
3.5. Compatibilities in Human Interactions
A key problem that had to be solved for plutonium was to identify the appropriate materials to
combine with it in order to enhance stability for use in nuclear weapons. Similarly, in human
endeavors, we frequently must determine the right combination of people to achieve a given
objective. One such method is to select people based on their innovation orientation, or the
preferred manner in which they approach and solve problems, think, and decide (Rosenfeld, 2006;
Rosenfeld, 2014; Rosenfeld, Wilhelmi, & Harrison, 2011). Innovation orientation can be measured
via the 64-item Innovation Strengths Preference Indicator
®
(ISPI
TM
), a reliable and valid
measurement that makes visible the invisible elements comprising all three aspects of human mental
functioning (Rosenfeld, Wilhelmi, & Harrison, 2011) (see Figure 10). When these elements are
combined, they result in compounds that become visible in human behavior, comparable to the way
in which the invisible elements of hydrogen and oxygen combine to form a very tangible and visible
compound—water. Under the ISPI
TM
model, three types of innovation approaches are represented
on a continuum that ranges from evolutionary (incremental improvement) to revolutionary
(breakthrough) (see Figure 11). As shown in Figure 11, the terms builder, connector, and pioneer are
used when describing individual innovation orientations, or the types of people who perform
evolutionary, expansionary, and revolutionary innovation. Builders prefer to make incremental
improvements within existing paradigms. Connectors do things differently and serve as a bridge for
others. Pioneers tend to break out of the current paradigm and create something entirely new.
Figure 10. Three Aspects of Mental Functioning
Note. Adapted from The Invisible Element: A Practical Guide for the Human Dynamics of Innovation (p. 56), by R. B. Rosenfeld,
G. J. Wilhelmi, & A. Harrison, 2011, Innovatus Press. Copyright 2011 by Idea Connection Systems, Inc. Adapted with
permission.

26
Figure 11. Three Basic Approaches to Innovation
Note. Adapted from The Invisible Element: A Practical Guide for the Human Dynamics of Innovation (p. 62), by R. B. Rosenfeld,
G. J. Wilhelmi, & A. Harrison, 2011, Innovatus Press. Copyright 2011 by Idea Connection Systems, Inc. Adapted with
permission.
In much the same way that chemical elements are organized in the periodic table of elements
according to invisible characteristics such as atomic number and atomic mass, invisible elements of
human mental functioning measured by the ISPI
TM
can be organized in a table called a totem. The
totem is a visual representation of ISPI
TM
results, illustrating strengths and preferences and
summarizing an individual’s unique innovation orientation. Table 3 shows a portion of a totem for
elements comprising the cognitive aspect of human mental functioning that influence how an
individual thinks and decides (see Rosenfeld, Wilhelmi, & Harrison, 2011, for a complete totem).
The partial totem in Table 3 represents a notional profile for a revolutionary thinker like Nikola
Tesla, whose preferences for ideation, risk, and process would all lie at the extreme end of the region
of the innovation continuum representing revolutionary thinkers. Extreme pioneers like Tesla are
out-of-the-box thinkers who like to challenge the status quo and are willing to take risks in order to
pursue novel ideas. They thrive on disruption and change. Their behavior often appears
spontaneous and unconventional and may deviate from established rules and norms.
Table 3. Partial ISPI
TM
Totem for Extreme Pioneer with Revolutionary Approach to Innovation
Note. Adapted from The Invisible Element: A Practical Guide for the Human Dynamics of Innovation (p. 67), by R. B. Rosenfeld,
G. J. Wilhelmi, & A. Harrison, 2011, Innovatus Press. Copyright 2011 by Idea Connection Systems, Inc. Adapted with
permission.
The ISPI
TM
model makes it possible to leverage invisible human elements in the workplace. For
example, if the task at hand is well delineated on the innovation continuum, then the best
combination of people consists of those whose orientations match the demands of the task; e.g., if

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the task is to tweak an existing procedure, people with evolutionary orientations are ideal. In other
cases like engineering design where the task may be more ambiguous, it is often beneficial to have a
diversity of innovation orientations on the team to incorporate a variety of perspectives. In still
other cases, the right combination of people for a task may change over time. Early in the project if
a team must brainstorm potential approaches, revolutionary orientations may be beneficial. As the
project evolves and narrows toward a particular solution, it may be more beneficial to include
individuals with evolutionary orientations who can further refine and deliver the proposed solution.
3.6. Human Substitutes for Experimentation
Just as numerous surrogate materials have been used as substitutes to study plutonium, many
experiments on human behavior use animal surrogates to help uncover the fundamentals before
extending the research to human subjects. Animal studies have been instrumental in our
understanding of key elements of human behavior such as learning and motivation. According to
the American Psychological Association (n.d.), approximately 7% of psychological research involves
the use of animals, primarily rats, mice and pigeons. Only about 5% of research animals are monkeys
and other primates (American Psychological Association, n.d.).
Animals are commonly used as human surrogates in psychological research for multiple reasons.
First, humans have a common ancestry and share a percentage of their DNA with animals like rats
and monkeys. This common ancestry means that many structural and functional processes are
similar between humans and nonhumans. Humans are most similar to chimpanzees and bonobos,
sharing almost 99% of their DNA (Prüfer, et al., 2012). Although rats and mice do not think and act
like humans, some of their brain structures resemble the more primitive components of the human
brain; as a result, rodents can be used to model some human behaviors. Second, animal research
affords greater control over environmental and extraneous variables than is often possible with
human subjects. Third, animals may be used as substitutes for humans in the interest of the greater
good for people; i.e., humans may actually be harmed if the research is not performed or takes too
long to complete. Fourth, animals typically have much shorter lifespans than humans, making them
a more logical choice in order to study various aspects of aging. Rats live an average of 2 years, while
monkeys live about 15 to 20 years.
Several well-known seminal research findings in psychology were made possible by studying animals.
In the late 1800s, Ivan Pavlov discovered the concept of classical conditioning serendipitously while
studying the physiological process of salivation in dogs. Namely, the dogs began to salivate after they
learned that certain objects (the appearance of the lab assistant) or events (the sounds of the lab
assistant’s approaching footsteps) were associated with the arrival of food. As with Pavlov’s dogs,
the principles by which learning occurs during operant conditioning were first demonstrated in rats
by behaviorist B. F. Skinner in the 1940s. Harry Harlow developed his concepts regarding the role
of social relationships in early development by first studying the impact of contact comfort in rhesus
monkeys in the 1950s and 1960s. Finally, the father of positive psychology, Martin Seligman,
developed the theory of learned helplessness based on early studies with dogs. Dogs exposed to an
uncontrollable stressor in the form of electric shocks soon gave up and passively accepted the
shocks, even when they eventually became controllable. All of these research findings, although
initially studied in animals, were subsequently applied to advance our understanding of human
behavior.

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3.7. Role of Luck in Psychological Research
In much the same way that Manhattan Project scientists ascribed some of their plutonium findings
to good luck, breakthroughs in psychology are occasionally attributed to chance or luck. However,
just as with plutonium research, what looks like luck on the surface in psychology actually stems
from a prior wealth of knowledge and careful implementation of rigorous, controlled research. For
example, psychological researchers who leverage an unexpected result to make a novel discovery are
able to capitalize on the supposed “error” for a number of reasons. First, they are astute enough to
detect the anomaly and recognize its value. They do not merely dismiss it as a problem to be covered
up. Second, because they designed an experiment to control the effects from multiple independent
variables, they are able to trace back to the potential source of the anomaly. Third, they are able to
think outside the confines within which they were working to envision other possibilities and
opportunities that may not have been on their radar at all when they began the work. Thus,
according to Dunbar and Fugelsang (2005), scientific discoveries that seem lucky tend to be the
result of both carefully prepared experiments and thoroughly prepared minds.
Pavlov’s research on salivation in dogs represents one example of a serendipitous finding in
psychology that might be ascribed to chance or luck. As described earlier, Pavlov intended to study
the physiological process of salivation, but he ultimately developed one of psychology’s most
famous models of learning by accident when his dogs began salivating before the food arrived.
Pavlov could have grown annoyed because the dogs salivated before they even ate the food. He
might have tried to devise ways to prevent the dogs from salivating until they started eating. He
might have stopped the experiments altogether if he felt he could not figure out what was causing
the “errors.” Instead, he thought more deeply about the unexpected occurrence and used it to
redirect his research and probe the so-called anomalies more fully.
Another example of the role of serendipity in psychological research can be seen in the discovery of
the well-known Hawthorne effect. As Jex and Britt (2014) put it, “what made the Hawthorne studies
so important to the field of organizational psychology were the unexpected, serendipitous findings
that came out of the series of investigations” (p. 13). The Western Electric Company and Harvard
University jointly conducted the Hawthorne studies between 1927 and 1932 at the Hawthorne
Works Western Electric Company plant near Chicago, Illinois. The original purpose was to
investigate the effects of environmental factors such as lighting and rest breaks on worker
productivity. Contrary to expectations, researchers found that productivity increased regardless of
how they altered the illumination. In other words, when they increased lighting levels, productivity
improved. When they decreased lighting levels, productivity also improved. This inexplicable
outcome led to additional research and became the basis for what is now known as the Hawthorne
effect—the notion that people respond positively to any novel change in the work environment,
ostensibly due to the motivational impacts from the extra attention they receive in the process. The
Hawthorne studies had lasting impacts on psychological research by highlighting the significance of
social factors for human behavior in organizational settings; i.e., productivity is not simply a result of
processes and procedures. In addition, the Hawthorne studies generated greater awareness of the
impact of observation itself on human behavior—people may behave differently simply because
they are being watched. As a result, there is now widespread recognition that any research involving
observation must be designed with careful controls in place, and multiple data collection techniques
may be needed to supplement the evidence provided by observation.

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3.8. New Frontiers in the Study of Human Behavior
Just like plutonium, new knowledge about human behavior continues to be acquired over time. For
example, a completely new domain of psychology—positive psychology—emerged in the late 1990s
with the goal of focusing on individual and societal wellbeing in order to improve the quality of life
(Seligman, 2012). The founder of positive psychology, Martin Seligman, sought to do more than
continue to study and treat mental illness, as was common practice in the field of psychology at the
time. His goal was to promote mental health and understand how people can flourish and thrive
throughout the lifespan. He developed the PERMA model to illustrate the five elements essential to
human wellbeing and flourishing, which form the foundation for positive psychology (see Figure
12). With the advent of positive psychology, the scientific study of behavior expanded from
researching human conditions like mental illness that we do not want to see in people to analyzing
desirable human conditions and characteristics that allow people to experience good mental health
and wellbeing. As Seligman asserts, positive means more than the simple absence of negative
conditions.
Figure 12. PERMA Model of Positive Psychology
As another example, a fifth taste sensation called umami was recently added to the traditional four
basic tastes (sweet, sour, salty, bitter) to better characterize the variety of taste sensations that
humans experience (Nelson, 2002). Umami is the taste of glutamate, an amino acid that forms one
of the building blocks of protein. It has been described as a meaty or savory taste distinct from the
core sweet, sour, salty, and bitter tastes. The tongue has specific receptors to receive each type of
taste and transmit the information to the brain for processing. For years, it had been accepted as
common knowledge that humans have only four basic taste receptors. Umami was first identified in
1908 in Japan (Ikeda, 2002). It was recognized as a distinct fifth tase at the International Symposium
on Glutamate in 1990. Receptors on the tongue responsible for umami were located in the 2000s,
further validating the existence of the fifth taste. A 2009 review concluded that multiple studies in
molecular biology have provided strong evidence for the existence of specific umami receptors
(Roper & Chaudhari, 2009).
Finally, virtual learning represents a relatively new area for research and application in the domain of
training. When modern psychology began in 1879, scholars learned primarily by reading hard copy

30
books and papers and by absorbing knowledge conveyed real-time by a well-respected and
knowledgeable teacher. Apprentices learned a trade by working under the supervision of a skilled
master craftsman to acquire the necessary skills. Virtual learning did not become a possibility until
advances in computing and simulation occurred in the 20th century. Virtual learning can take several
different forms in which students access resources and interact in ways that differ from those in the
traditional physical classroom. In virtual learning, an instructor need not be physically present, and
the learning need not occur inside a traditional classroom. For example, students may access a pre-
recorded video lecture and watch it from home on their own time. Students may read a chapter in an
electronic copy of the course textbook or review information on the Internet from their personal
computers. More sophisticated forms of virtual learning occur via virtual and augmented reality. For
example, military and commercial airline pilots now routinely use simulators to acquire and practice
flight skills. Innovations like these that have been designed to facilitate learning could not even be
conceptualized until the late 20th century after computing resources became widely available.

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4. IMPLICATIONS OF THE ANALOGY
The analogy presented in this paper demonstrates that the thought processes and the methodologies
required for success are the same in the so-called soft and hard sciences. In the end, endeavors in
both realms represent science—a systematic and disciplined search for knowledge. The materials that
are studied in various disciplines differ, but the processes to study them are parallel. Plutonium is
complex, and people are equally complex. On the surface, both plutonium and people can appear
perplexing and unknowable. However, the study of plutonium and the study of human behavior
both demonstrate that predictability is achievable, given time, research, rigor, experimentation, and
an openness to opportunities that may present themselves. We have been able to determine how to
manufacture, harness, transport, and use plutonium for multiple purposes. Similarly, we have been
able to understand a multitude of human characteristics and behaviors such as aging, personality,
and why person A works well with person B but not person C. The initial trials to understand
plutonium and continued efforts to unravel its complexities may provide insights that can help
scientists further crack the code of human behavior. Ultimately, we propose that the analogy
between the study of plutonium and the study of human behavior has four important implications
for scientists in all disciplines.
4.1. Recognize the Growing Interdisciplinarity of Scientific Research
First, the most impactful research requires effective collaboration across disciplines, and such
interdisciplinary collaboration will proceed more easily if the collaborators have some knowledge of
other scientific fields beyond the soft vs. hard distinction (VanLandingham, 2014). In other words,
forgetting about whether a discipline is categorized as soft or hard will help expedite “collective
progress toward good science” (VanLandingham, 2014, p. 125). Interdisciplinary research has indeed
been increasing since the 1980s (Feng & Kirkley, 2020; Lakhani, Benzies, & Hayden, 2012; Morillo,
Bordons, & Gómez, 2003; Porter & Rafols, 2009). For example, the number of authors per paper
has grown over time by an average of 75%, while the number of single-authored papers has dropped
to less than about 10% (Porter & Rafols, 2009). At the same time, the diversity of research domains
cited within an article has increased, suggesting that researchers are becoming more likely to draw
upon knowledge from multiple scientific disciplines to support their own field (Porter & Rafols,
2009).
This growth in interdisciplinary work means that scientists of all types are increasingly collaborating,
which in turn implies that a focus on similarities rather than differences among researchers from
different disciplines is necessary. Rather than creating artificial barriers like the soft vs. hard
distinction that divide researchers, it is important to emphasize how to establish effective
collaboration in order to effectively leverage the cross-fertilization to advance science (Morillo,
Bordons, & Gómez, 2003). Toward that end, a review of research papers in medicine, nursing, and
psychology published between 1990 and 2010 revealed that two key attributes for effective
interdisciplinary research teams are cohesion and mutual respect (Lakhani, Benzies, & Hayden,
2012). Cohesion, or the camaraderie among team members who have become familiar with one
another, fosters collaboration by promoting good relationships, insights, and risk taking (Lakhani,
Benzies, & Hayden, 2012). Mutual respect is characterized by an openness to the talents and unique
perspectives of all members of the team (i.e., the invisible human elements), regardless of their area
of specialty, and a willingness to explore alternative approaches. Mutual respect is crucial for
effective integration of member contributions and expertise in an interdisciplinary environment,
promoting information sharing and problem solving (Lakhani, Benzies, & Hayden, 2012). Both

32
cohesion and mutual respect can be difficult, if not impossible, to cultivate in the context of a
culture that abides by the soft vs. hard distinction.
4.2. Embrace the Role of Judgment in All Scientific Endeavors
Second, scientists in all disciplines must come to terms with the realization that judgment and
subjectivity are not confined to the social and behavioral sciences. They are a part of all scientific
endeavors (Baron, 2019; Mannan, 2016). Baron (2019) points out an “important but poorly
understood fact about science and engineering—it’s all done by humans, and humans are not
objective creatures” (p. 1). In other words, the apparent subjectivity in psychological research that
often seems obvious to people outside the field because of the material being studied (humans) is
also inherent in scientific disciplines like physics and engineering. Scientific knowledge is derived
from decisions influenced by an individual’s interests, attitudes, background knowledge, and
conceptual framework, which imparts “one kind of subtle subjectivity” during any type of scientific
endeavor (Mannan, 2016, p. 44). In essence, no scientist simply crunches objective numbers in a
vacuum because that number crunching itself is influenced by numerous factors that make one
scientist’s views of the world different from another scientist’s views. Decisions based on judgment
and skill are made throughout the entire process—identifying a question for research, generating
hypotheses, selecting research methods, interpreting data, and determining when to conclude the
research.
An excellent example illustrating the influence of individual perspectives and conceptual frameworks
in the physical sciences can be seen in the divergent views of plutonium’s phases that persisted until
the end of the 20th century (Hecker & Timofeeva, 2000). Namely, U.S. researchers disagreed with
Russian researchers regarding the stability of the δ-phase plutonium-gallium alloys used in nuclear
weapons. Two very different versions of the phase diagrams existed for decades, resulting in
significantly different predictions of δ-phase stability. U.S. researchers predicted δ-phase plutonium-
gallium alloys would remain in that phase at ambient temperatures and above. Russian researchers,
on the other hand, produced phase diagrams illustrating decomposition at ambient temperatures
into a mixture of phases. This difference is not trivial since such a decomposition implies
concomitant volume, dimension, and property changes impacting weapon performance. When U.S.
and Russian scientists were able to collaborate after the Cold War ended, the 40-year disagreement
was finally resolved. It was discovered that the differences in the phase diagrams stemmed from
differences in the experimental approaches used in the two countries, based on the researchers’
differing views of the plutonium world. Specifically, Russian researchers used a preconditioning
treatment that U.S. researchers had never considered and therefore never attempted because the
expectations they had formed from existing U.S. phase diagrams led them to concentrate on
transformations below ambient temperature. In other words, U.S. scientists could not even begin to
replicate the Russian results because of the very way in which they viewed the problem. In the end,
the Russian phase diagrams depicting thermodynamic instability were determined to be correct.
Given the pervasive influence of subjectivity throughout all of science, it follows that the soft and
hard sciences are more similar than different. Hedges (1987) reached exactly this conclusion when
he conducted a direct empirical comparison of the degree of agreement among replicated
experiments in the social and physical sciences, using 13 exemplary reviews from each domain. He
noted that the methods used to synthesize research and evaluate the consistency of results across

33
multiple experiments are essentially identical in the social and physical sciences. In fact, procedures
to calculate weighted means and weighted least squares are perfectly congruent. Moreover, the
results from such reviews are not more consistent for the physical sciences as compared to the social
sciences, as commonly assumed. Namely, statistical analyses of experimental results expressed via
numerical estimations such as mass, energy, and correlation do not differ—approximately 46% of
the reviews in both physics and the social sciences showed statistically significant disagreement
among studies. Hedges (1987) concluded that “the ‘obvious’ conclusion that the results of physical
science experiments are more cumulative than those of social science experiments does not have
much empirical support” (p. 443).
In fact, recent experiments in the field of quantum mechanics now question the very existence of an
objective reality, which has long been considered a hallmark feature differentiating the soft and hard
sciences. The physical sciences are based on the fundamental assumption that universal truths exist,
which can be determined and accurately predicted through experimentation, observation, and
analysis. Yet, studies in quantum mechanics suggest the universe is much more probabilistic and
chaotic when viewed at the scale of atoms and subatomic particles. One of the implications of
quantum mechanics research is that objective reality cannot be fully known because the act of
observation itself influences what is observed—in much the same way that observations can change
human behavior. Specifically, experiments led by researchers in the United Kingdom in 2019 have
demonstrated that objective reality is directly relative to individual perceptions, making it impossible
to agree on the objective facts about an experiment (Proietti, Pickston, Graffitti, Barrow, Kundys,
Branciard, Ringbauer, & Fedrizzi, 2019). Developments such as these only serve to further blur the
distinction between the soft and hard sciences and highlight the subjectivity inherent in all scientific
endeavors.
As another example, it is commonly thought that the field of mathematics is a completely black-and-
white objective discipline in which individual preferences and beliefs have no place. In reality, much
of mathematics is actually subject to interpretation, even for foundational concepts like set theory.
Namely, there is still controversy over whether to include the tenth axiom, the axiom of choice,
within set theory. Historically, some mathematicians rejected the axiom completely; others accepted
it but avoided its use whenever possible; and some changed their minds about it over time as new
information emerged. The decision whether to use the axiom of choice depends on the preferences
of each mathematician—it is more or less a question of “taste” or “belief” (Axiom of choice, n.d.,
Independence and Controversy section). Today, the majority of mathematicians accept the axiom of
choice because it is natural and intuitive as well as convenient, given that the proofs of multiple
significant mathematical theorems depend on it. Again, as with quantum mechanics, it seems that
subjectivity is woven into the very fabric of seemingly matter-of-fact disciplines like mathematics.
Ultimately, then, all scientific endeavors represent a “subjective understanding of an objective
world” (Manna, 2016, p. 70). However, according to Curtis (2012, p. 96), “the existence of
subjectivity…does not necessarily imply a lack of scientific rigor.” Accordingly, it may be more
fruitful to embrace the benefits of subjectivity in science, for it is this very subjectivity that can
contribute to novel hypotheses, progression of ideas, and serendipitous findings (Curtis, 2012;
Gough & Madill, 2012). Gough and Madill (2012) call this fresh perspective of recognizing and
working positively with the subjectivity present in the research process a reflexive scientific attitude.

34
4.3. Acknowledge the Importance of Human Behavior for All Scientific
Disciplines
Third, human behavior is a significant driver in many areas and is not confined just to the social and
behavioral sciences (“In Praise,” 2005). The work of social and behavioral scientists can potentially
make valuable contributions to the study of a range of important societal problems (“In Praise,”
2005). For example, research into environmental problems such as climate change and declines in
biodiversity tends to focus strictly on the physical nature of such phenomena. Underlying behavioral
factors are likely to be neglected because they are regarded as belonging to the realm of soft science.
Yet, as Breckler (2005) points out, psychology represents the future of science. He estimates that
fully 10% of the major scientific challenges for the 21st century, as identified by the American
Association for the Advancement of Science (AAAS), lie in the psychological domain. In his words,
the AAAS list is a “strong indication that the true frontier of science puts psychology and the
behavioral and cognitive sciences at center stage. The past has paved the way for science to turn its
attention to the truly challenging, difficult and hard questions” (Breckler, 2005, pp. 62-63). Other
researchers have drawn similar conclusions. Johnson and Yonas (2006), for example, indicate that
the critical problems of the future can be described as wicked sociotechnical problems. Their causes
and effects are elusive due to nonlinearities and interdependencies among numerous variables. They
do not have definitive descriptions or optimal end states. Johnson and Yonas (2006) point out that
trying to “tame” wicked problems results in defining issues too narrowly from only a technical
perspective, which unconsciously eliminates many potential solutions. A better approach is to create
a diverse team of people from different professions and academic backgrounds who will have
different perspectives on the system. Ultimately, their advice is to address wicked sociotechnical
problems by focusing more attention on the people in the system than the technologies—the exact
opposite of the current typical approach to design and development for engineered systems.
In addition, scientists in all disciplines are increasingly expected to bring more than the technical
skills associated with their particular specialty to the workplace. They also need interpersonal skills
like emotional intelligence that will help them communicate and collaborate with colleagues from
many different disciplines. According to author and motivational speaker John C. Maxwell, the
greatest single obstacle to success in the workplace is poor people skills, not poor technical skills
(Maxwell, 2000). He maintains that strengthening interpersonal skills will take an individual farther
than developing any other skill. In general, there is growing recognition that job skills for the 21st
century include transferrable interpersonal skills such as creativity, innovation, critical thinking,
problem solving, and decision making (Bersin, 2020; Denney, Haley, Rivera, & Watkins, 2020). In
fact, it has been estimated that as much as 85% of success on the job is attributable to interpersonal
skills rather than technical skills (Denney, Haley, Rivera, & Watkins, 2020). As Bersin (2020) puts it,
these “power skills” have been identified by executives as the skills most critical for today’s
workforce and the “key to the future” (p. 1). Along these lines, interpersonal skills such as conflict
resolution, empathy, and communication have been shown to be particularly critical for research
involving large and interdisciplinary teams (Cheruvelil, et al., 2014; Farrell, et al., 2021).
The implication is that even scientists in the physical sciences must be able to understand and apply
key principles from behavioral sciences such as psychology and sociology to succeed in the
workplace. Toward that end, scientists in all disciplines must have training in not only technical skills
but also interpersonal skills. Such training may best be provided through formal coursework at the

35
university level before students enter the workforce, though formal teamwork training is currently
nonexistent in most graduate programs (Cheruvelil, et al., 2014). To compensate for this lack of
formal training, Cheruvelil, et al. (2014) suggest that various teamwork exercises can be intentionally
built into a workplace project itself to improve interpersonal skills in collaborative research teams,
potentially leading to the creation of explicit standards and best practices for interpersonal behavior.
In addition, they suggest it is beneficial for an interdisciplinary team to assess periodically its status
with respect to interpersonal skills.
4.4. Eliminate the Soft vs. Hard Distinction
Finally, the most critical implication to draw from the analogy presented in this paper is an
imperative to eradicate the soft vs. hard distinction altogether. It no longer serves a purpose and
creates unnecessary barriers, causing more harm than good. This position is not new, yet the
distinction continues to persist. In the domain of public health, VanLandingham argued in 2014 that
the terminology should be removed entirely, claiming that “the hard/soft moniker is vacuous, vapid,
complacent, and ultimately counterproductive” (p. 125). A 2005 article in Nature agrees, urging hard
scientists to “get over their disdain for their ‘soft’ colleagues” and “stop looking down their noses at
social scientists” (“In Praise,” 2005, p. 1003). This denigration of soft sciences is problematic
because ignorance of state-of-the-art methods used in the social and behavioral sciences can be a
“serious impediment to scientific progress” (VanLandingham, 2014, p. 125). To this point, Frost
(2009) indicates that the soft science label negatively impacts the perceived value of a scientific
discipline as well as the amount of funding allocated to that discipline. During the recessions of the
late 2000s, for example, funding cuts were predominately imposed on the social sciences as
compared to mathematics and the natural sciences (Richardson, 2010).
For these reasons, we suggest replacing the traditional ranking of scientific disciplines on the hard-
to-soft continuum with the depiction shown in Figure 13. In this alternative view, the various
scientific disciplines have fuzzy rather than distinct boundaries. Each has a central core that
represents the essence of that discipline, but it may not always be possible to clearly define what is
and is not included within its boundaries. Further, as Figure 13 illustrates, the various disciplines
represent interconnected nodes existing in something akin to a neural network. They overlap to
some degree and have branches that extend into other disciplines, both proximal and distal. These
overlaps and branches mean the various scientific disciplines influence and interact with one
another. They do not exist as separate and isolated entities unto themselves. A view such as this
emphasizes the interconnections that permeate science rather than focusing on stringent black-and-
white distinctions and narrow definitions that may be used to erect barriers among disciplines and
hinder interdisciplinary collaboration. Eliminating the soft vs. hard distinction does not detract from
the hard sciences in any way. Instead, it opens the door for more robust and inclusive collaboration
that leverages the strengths of multiple disciplines.

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Figure 13. Alternative View of Relationships Among Scientific Disciplines

37
5. CONCLUSION
To summarize, we reiterate the key message readers should take away from this paper. The popular
distinction between soft and hard sciences needs to be eradicated from the lexicon in all scientific
disciplines. As the analogy between plutonium and people illustrates, the soft and hard sciences are
more similar than different. For both plutonium and human behavior, the mere fact that properties
are invisible does not imply they are random, unknowable, and unpredictable. In the end, the soft vs.
hard distinction no longer serves any purpose and ultimately hinders the collaboration necessary to
promote high-quality interdisciplinary research that leverages diversity of thought and will further
advance scientific knowledge for the challenging sociotechnical problems of the future.

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