Perspectives on computing
Annamaria Carusi
Oxford e-Research Centre and Computing Laboratory
A philosophical / Science and Technology Studies perspective on computing. The
following are some of the questions that have arisen in my research on computational
technologies for science and research.
The relation between the formal and the informal
The relation between the formal and the ‘informal’: computers require formalisation in
order to function. But the world is not formal. Every formalisation leaves something out
and by the very fact of picking out some features and relations and concretising them in a
technology, intervenes in the environment or domain. This process introduces if not a
bias, then at least a difference in that environment or domain. This difference is often
reinforced by virtue of the functions that computing enables us to carry out in terms of
the formalisation. Like a self-fulfilling prophecy, this reinforcement results in a
diminished ability to see the environment except in the terms of the formalizations in
question.
What is lost in this process? How to formalise more flexibly? How to formalise more
(self-) reflexively?
Computational thinking
Computational thinking as a topic of discussion among computer scientists is perhaps one
way in which this reflexivity is coming to the fore in computer science. I have recently
been to several events where the virtues and benefits of ‘computational thinking’ have
been expounded. Much of what is mentioned under computational thinking seems simply
to be the core skills of 1) classical rhetoric and 2) philosophy, only much more naively
stated, with much less reflection and consideration. This is not a point of criticism as
computer science is a young discipline, and rhetoric and philosophy are very old, and so
have a head start in addressing general questions about the general shape of reasoning,
thought and how to these are rendered in communication. Some questions I have in this
regard are:
1) what is specifically computational thinking?
2) why is a mode of thinking singled out, as opposed to other processes, capacities,
activities: being, feeling, speaking, acting, doing, etc.
3) is computational thinking becoming a hegemonic discourse?
Visualisation technologies
Visualisation technologies for scientific research are presented as being enormously
significant for contemporary science and research of all types, as they provide the means
for dealing with massive quantities of data: for organising, analysing, interpreting and
generally acquiring knowledge from it. The place of visualisation in research which is,
for example, conducted through modeling and simulation, raises several interesting
questions. A network of inter-disciplinary relations is required for this kind of research,
and computer science is central to it. All other disciplines need to ‘go through’ computer
science. These technologies need to be seen against the background of the history of
scientific instrumentation. What is the impact of computer science on the epistemologies
of other disciplines? What is its impact of the understandings of knowledge and on the
epistemic practices of scientists and researchers?
Data and information are central concepts in this domain. However, the meanings of
these terms tends to shift across the different epistemic practices involved in designing
developing and using visualisation and other computational technologies. In addition,
there are computing and philosophical accounts of information. What are the relations
between these different attitudes and approaches to data and information, ranging from
the only loosely theoretical, to the highly theorized?
Visualisation technologies create an interesting dynamic between the quantitative and
qualitative aspects of science. Visualisations are the outputs of numerical, algorithmic
and mathematical processes. However, these outputs are in visual form, and therefore
depend upon perception, representation and a host of other qualitative factors. The
problematic aspects of this dynamic are generally placed under the rubric of HCI studies,
or are seen as the remit of cognitive psychology. However, these do not deal with
interpretive and conceptual aspects of perception and representation. There is a (possibly
Foucauldian) disciplinary question to be asked: why does computer science align itself
with certain other disciplines and not with others in attempting to bridge the gap between
the quantitative and qualitative? What means can be used in order to bring these other
aspects to the fore in such a way that they make a difference to the design and use of
these instruments?
Computer ethics
Computer ethics is often viewed as external to the practice of computer science or to the
artifacts of information technology. On one hand there are the computing applications or
information technologies, and on the other are the ethical questions that arise from them.
Thus for example the data base technologies are seen as an entirely separate issue from
the threats to privacy that they give rise to when they are repositories for data about
human subjects. The job of the ethicist or the ethically inspired IT specialist is to ensure
that such data bases are used in accordance with ethical norms.
A different view of computer ethics is to see ethics – in the sense of moral values – as
inherent to this practice and these artifacts, in that values are designed or built into them
from the outset. For example, some technologies or developments or improvements are
seen as meaningful, significant, desirable within an overarching configuration of values.
Trust technologies are a good example: building trusted technologies is meaningful and
significant because of the social context in which trust is an issue. However, the way in
which trust is addressed in the technology makes enormous value assumptions about
trust, with consequences that are undesirable not just in a functional or epistemic sense,
but in an ethical sense in that they make it harder to actualize or even to express the
values of some people or groups. Computer ethics scholars have responded to this
challenge by adopting a course of disclosive ethics. In essence they see themselves as
undertaking a critique of technologies to reveal the value assumptions that were made in
their design. What, if any, is the role of this sort of critique in computer science, and is
there a way in which it can be instated in anything but a post hoc way?