There is common, rather empirically supported knowledge within the
body of the System Analysis that complex interfaces (for example “man - machirie” interface within the hybrid system, or synapse in the human brain) susceptibly react both on the dimension of the task (i.e.: the number / type / domain of interface parameters / markers), and the level of uncertainty. In order to quantitatively evaluate this effect, the overview of the different concepts of interface is done first. Then the problem is analyzed on the background of geometrical considerations.
The results of the study indicate that even a low degree of uncertainty has significantly adverse eífect on the interface regularity (consequently the reliability of systems processes, as well) if the dimension of the pertinent task is sufficiently high.
Practical implication of this result for systém analytics is straightforward - keeping the dimension of the task as low as possible. The interface dimension higher than 5 is in the majority of tasks with moderate uncertainty considerably unfavorable. This result imposes serious constrain to the systems identification.