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It is
becoming more and more apparent that the knowledge and expertise of many
differing disciplines is required in order to better understand the
highly complex, multi-layered relationships inherent within design and
decision-making processes. Although the quantification of multiple
variable parameters, objectives and constraints may allow a high degree
of automation in some cases many others require a degree of human-based
subjective evaluation of solutions. Such people-centred activity is most
apparent during the conceptual phases of a design or decision-making
process where uncertainty and associated risk are prime characteristics.
Generally, people are also significantly affected by identified
solutions and in most cases are the targeted audience. This introduces a
requirement for a relatively complete understanding (both quantitative
and qualitative) of the impact our decisions / designs have upon
ourselves and others and the manner in which we are likely to react.
Computational
systems poorly support the formative stages of a decision-making process
in that they do not possess generative capabilities in terms of concepts
and hypotheses. These are fundamentally human-based activities but the
comparative assessment of possible alternatives rapidly moves beyond our
cognitive capabilities with even small increases in problem complexity.
Advanced computational environments are therefore required that support
such comparative assessment whilst the user maintains an integral role.
The Institute is therefore investigating, via a number of collaborative
research projects, the development of generic computational environments
that support human-centric activities through an enhancement of
practitioner’s skills. Such systems will achieve the on-line capture and
utilisation of human knowledge and experience to better define
machine-based problem
representation whilst avoiding over-automation, human exclusion and the
consequen
tial
loss of valuable and essential
information. We need to identify the relative strengths
and weaknesses of people and machines and allocate function
appropriately. Such human-centric systems must also be able to
qualitatively and quantitatively estimate
end-user requirement. In an increasingly competitive global environment,
such advanced people-centred computational environments successfully
operating in crucial
highly complex domains will contribute significantly to economic
success.
In
order to move towards the integration of such systems with current
practice the Institute brings together a diverse set of disciplines to
better understand generic issues and peculiarities relating to design
and
decision-making processes. For example, a software engineer must cope
with the intangible nature of software where problem represent
ation
is difficult and performance criteria hard to define. Are there
similarities here to the product designer struggling with the formation
of initial concepts or the engineering designer establishing trade-offs
between alternative initial design directions? Can processes and
methodologies utilised in these areas benefit the chemist faced with
massive reagent libraries from which ‘drug like’ products need to be
selected for in-vitro testing or perhaps those working in organisational
or financial product design? What can these disciplines offer each other
in terms of current practice and established methodologies? It is
apparent from current work that cross-disciplinary identification of
common requirements, both human and machine-based, and current
methodologies can result in a rapid transfer of technology that can
bring significant benefit in a seemingly differing domain. The use of
design analogy and metaphor can rapidly open up potential pathways to
generic processes.
Researchers within the Institute are intent upon the identification of
common languages, methodologies and practices that allow us to cease
working in isolation and to realise mutual benefit from our collective
experiences
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