Since I work at the intersection of several disciplines, the grouping of research topics is not easy. On this page I have tried to put them together in four major groups, in no particular order. In due time this will be complemented by a listing based on domains, as well as a chronology.
Accidents
Over the years, a number of
disciplines have appeared to deal with issues of safety and risk, for instance accident
analysis, "human error", Probabilistic Safety Assessment (PSA), Human
Reliability Analysis (HRA), risk analysis, safety management, safety culture,
and so on. Some of these have had an engineering or technical background, some a
more behavioural or psychological background. This may have contributed to the relatively
sparse interaction between different disciplines, despite
the fact that they are all concerned with the same problem: how to understand and
prevent the occurrence of untoward events.
The
variability of Human Performance
We
seem rapidly to be approaching a time when the concept of "human
error" has ceased to be meaningful (although this may just be wishful
thinking on my part). In its place is the realisation that human performance is
variable, and that this variability is behind successes as well as failures. Another way of saying that is to point out that accidents (incidents,
etc.) are due to usual actions under unusual conditions, rather than unusual
actions under usual conditions. We therefore need theories and models of human
performance variability, rather than of "human error".
Modelling
of Cognition
One
of the hard problems in the study of cognitive systems is how cognition should be
modelled. While it is taken for granted that models are necessary in the study
of cognition, just as in every other field of science, there are two issues of
the model problem that need to be addressed. One concerns what
should be modelled; this is the issue of the substance of modelling. The
other concerns how the models should
be expressed, i.e., the language of modelling, or the technical issue.
Cognitive
Systems Engineering (CSE)
In the beginning of the 1980s, David
Woods and I formulated CSE to provide a
consistent conceptual and methodological basis for research on human-machine
systems, with design and evaluation as the two main foci. In the 1990s, the
interest for CSE began to grow significantly, as researchers gradually changed
their focus from cognition in the mind to cognition in the world - or in the
wild.