Systems, Man & Cybernetics - April 2015 - 37

pect of our daily lives and ultimately
yet to be fully addressed or underdetermine the future of our society
stood in extant research. In essence,
in how it changes and grows. The procan we teach computers to think outliferation of these centers is aimed at
side the box?
successfully nurturing, realizing, and
I believe one of the keys to achievtranslating innovations. While sucing this is a simple concept I call
cesses abound and
perspectives. This
can be measured
concept treats each
by things, such as
piece of data and inIts a real joy to
the number of patformation intuitively
help students to
ent s generated,
as a point of view
licensing income,
for one or more enexplore new ideas
and return on intities described by
and to discover
vestment, success
the piece but does
other new
is still very much a
not require a preproblems.
hit or miss proposidefined dictionary
tion. Understanding
or ontology that exand driving indiplicitly relates the
vidual innovation is
pieces together. It
already a tough proposition. Many
is the latter that has been an open
more complex world problems require
problem in areas such as big data,
fostering team innovation, which is
where attributes in data must have
likely even more difficult.
predefined mappings and relationThere are numerous case studies
ships before any analyses can hapabout team innovation. Unfortunatepen. Instead, as points of view we
ly, they are mainly either descriptive
can consider the various relationships
or anecdotal and conclusions drawn
dynamically and combine them tohave mainly been correlational in
gether to define a rich space of many
nature. Understanding the causality
different possible models and then alis central to understanding individual
gorithmically optimize the collection
innovation and even more with comto arrive at a canonical answer model.
plex team innovation, without which
What is most interesting is that
is the reason for the trial and error
the nonlinearity naturally arises out
nature inherent in the existing innoof this merging since the canonivation centers.
cal model is itself the mechanism
I think the time is ripe for developfor inferring decisions. My research
ing a network science of team innovagroup has been studying this phetion. Why a network? It is a network
nomenon in different domains, such
not just between the innovators but
as emergent behavior in social intent,
also by the people and entities that
opinion change, social resiliency, and
provide support (the centers) as well
hidden source behavior modeling.
as the outside world. I believe that
we have the elements to provide an
SMCM: A re there any future
answer to this problem-say startresearch projects that you would
ing from the basics of understanding
like to discuss?
the causal factors in human social
Santos: I think one research
behavior, decision making, and influproject that needs to be pursued is
ence to developing formal matheexploring the question of what is the
matical behavior models for analysis
underlying science behind team innoand simulation to conducting human
vation. What makes a team innovative?
subject studies, so we can discover
The X Innovation Center, The Y
and validate the principles behind
Innovation Center, and The Z Innovainnovation and innovative activities.
tive Ideas Institute are all over the
Of course, this is going to be a major
place and are charged with some
effort, especially its large interdisvariation of fostering novel concepts
ciplinary nature-this requires new
and technologies to drive every asAp ri l 2015

research cutting across the social,
computational, cognitive, and organizational sciences and disciplines.
I have been fortunate to work
with like-minded colleagues from
such disciplines. The successes we
have had in our cross-cutting collaborations in problems, such as
computational social decision making, networked intent inferencing,
and opinion perception and cognitive styles, lead me to believe that we
are ready to start tackling this new
research area for the network science of team innovation.
SMCM: What motivates you to do
research, teach, and volunteer?
Santos: "What is the underlying
science?" is the question that motivates me to do research. Achieving
an understanding of the why and how
then triggers the desire to communicate that insight to others; that is why
I teach. My goal in teaching is to not
just help students comprehend the
science but spur them to think about,
"Where can this insight lead to?" It is
a real joy to help students to explore
new ideas and to discover other new
problems. Finally, what insights my
students and I have learned should
then ultimately change our society for
the better. What better way to achieve
this than in volunteering to spread the
latest science and technology?
SMCM: Who are your role models
and why?
Santos: My role models, to start
off, would have to be my parents. My
father, Eugene, Sr., studied computer
science and mathematics early in the
1960s. His research in probabilistic
and fuzzy Turing machines in the
late 1960s and the early 1970s shaped
much of my mathematical foundations. My mother, Evelyn, who was an
electrical engineer, taught me about
the balance between theory and practice. And all that, of course, molded
my world view. Together, my parents
gave me a perspective in terms of having a passion for science and technology. They encouraged me and gave
me all the support I needed in my

IEEE SyStEmS, man, & CybErnEtICS magazInE

37



Table of Contents for the Digital Edition of Systems, Man & Cybernetics - April 2015

Systems, Man & Cybernetics - April 2015 - Cover1
Systems, Man & Cybernetics - April 2015 - Cover2
Systems, Man & Cybernetics - April 2015 - 1
Systems, Man & Cybernetics - April 2015 - 2
Systems, Man & Cybernetics - April 2015 - 3
Systems, Man & Cybernetics - April 2015 - 4
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Systems, Man & Cybernetics - April 2015 - 6
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Systems, Man & Cybernetics - April 2015 - 13
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Systems, Man & Cybernetics - April 2015 - 19
Systems, Man & Cybernetics - April 2015 - 20
Systems, Man & Cybernetics - April 2015 - 21
Systems, Man & Cybernetics - April 2015 - 22
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Systems, Man & Cybernetics - April 2015 - 30
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Systems, Man & Cybernetics - April 2015 - 37
Systems, Man & Cybernetics - April 2015 - 38
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Systems, Man & Cybernetics - April 2015 - 40
Systems, Man & Cybernetics - April 2015 - 41
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Systems, Man & Cybernetics - April 2015 - 47
Systems, Man & Cybernetics - April 2015 - 48
Systems, Man & Cybernetics - April 2015 - Cover3
Systems, Man & Cybernetics - April 2015 - Cover4
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