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.