Physical Social Life computing
implemented by mechanical,
optical, electronic,
quantum,
and chemical
computing
Wizard of oz,
mechanical turks,
human cognition
genomic, neural,
immunological,
dNA transcription,
evolutionary
computing
compilers, oS,
emulation,
reflection,
abstractions,
procedures,
architectures,
languages
implements modeling,
simulation,
databases, data
systems, digital
physics, quantum
cryptography
artificial
intelligence,
cognitive
modeling,
virtual humans,
autonomic
systems
artificial life,
biomimetics,
systems biology
influenced by sensors,
scanners,
computer vision,
optical character
recognition,
localization
mouse, keyboard,
learning,
programming,
user modeling,
authorization,
speech
understanding
eye, gesture,
expression,
and movement
tracking,
biosensors
influences locomotion,
fabrication,
manipulation,
open-loop control
screens, printers,
graphics, speech
generation,
network science,
cognitive
augmentation
bioeffectors,
haptics, sensory
immersion
Bidirectional
influence
robots, closed-loop
control
human-computer
interaction, full
immersion, games
brain-computer
interfaces
It might be asked whether mathematics is a great domain of science. Although mathematics is clearly a great
domain, it has traditionally not been
considered a science.
networking,
security, parallel
computing,
distributed
systems, grids
Computing does not seem to fit nicely into any of the traditional domains.
Computation is realized in physical
media and is even part of some physical processes (for example, quantum
mechanical waves). More recently computation has been found in living systems (for example, DNA transcription)
and social systems (for example, evolution of scale-free networks). Although
computational methods are used extensively in all the domains, none studies computation per se—computation
is not a physical effect, a living entity,
or a social entity.
What if computing is a separate domain? It satisfies the three criteria. It
computing interacts
not only with people
and other living
systems, but with
the physical world.
has a distinctive focus—computation
and information processes. Its constituent fields—computer science,
informatics, information technology,
computer engineering, software engineering, and information systems—
and its structures and processes are in
constant interaction. Its influence is
pervasive, reaching deep into people’s
lives and work.
The core phenomena of the computing sciences domain—
computation, communication, coordination,
recollection, automation, evaluation,
and design2, 6—apply universally,
whether in the artificial information
processes generated by computers or
in the natural information processes
found in the other domains. Thus,
information processes in quantum
physics, materials science, chemistry,
biology, genetics, business, organizations, economics, psychology, and
mind are all subject to the same space
and time limitations predicted by
universal Turing machines. That fact
underpins many of the interactions
between computing and the other
fields and underlies the recent claim
that computing is a science of both
the natural and the artificial. 3–5
The Nature of interactions
Two out of the three criteria listed earlier involve interactions, either among
structures and processes or among
domains. These interactions generate
the essential richness of science. They
also complicate how we observe and
understand science.
Hierarchical taxonomies are the
usual ways of observing a domain of
science. It is easy to craft a tree hierarchy representing all the parent and
child relationships among fields in
the domain. For example, the physical
sciences are partitioned into chemistry, physics, astronomy, geology, etc.,
and each of those may be partitioned
further, for example, regular and organic chemistry. Each field has its
own “body of knowledge,” often represented with a taxonomy or a tree.
Computing is likewise divided into
constituent fields and subfields, each
with a body of knowledge.
Hierarchical structures are very
good for understanding static aspects
of a field, but not its dynamics. Within
a field, the interesting phenomena are
not simply the properties of “things”;
they are interactions among multiple
things. Chemistry is not simply chemicals; it is the reactions among elements. Mechanics is not simply gears
and levers; it is the forces among these
parts. Psychology is not simply emotions, urges, and mental states; it is
transactions and relationships. Similarly, computing is not just algorithms
and data structures; it is transformations of representations.
The interactions are the real action
of a field. Their complexities and uncertainties demand constant experimentation and validation in science and
engineering. They make things messy
and unpredictable. They are sources of
innovation.
Scientific phenomena can affect each
other in one of two ways: implementation
and interaction. A combination of existing things implements a phenomenon
by generating the intended behaviors
of the phenomenon. Digital hardware
physically implements computation.