Two problems concerning anticipation effort as an important cognitive resource for improved avionics safety are addressed: (1) assessment of the probability that the random actual ('subjective') anticipation time is below the (also random) available ('objective') time and (2) evaluation of the likelihood of success of the random shortterm anticipation from the predetermined (non-random) long-term anticipation. Unlike the traditional statistical approach, when experimentations are done first and are followed by statistical analyses, our novel concept suggests that probabilistic predictive modelling is done first and is followed by experimentation. The concept proceeds from the fundamental understanding that nobody and nothing is perfect and that the difference between a success and a failure in a particular effort, a situation, or a mission is, in effect, 'merely' the difference in the level of the never-zero probability of failure.

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For a long time, literature has identified some psychophysiological metrics that proved reliable to assess cognitive states in controlled conditions. Smaller, more reliable and more affordable sensors made the industrial community plan to design systems that would adapt themselves to the ability of their users to operate them. Thus an important human factors question must be asked: what is the impact of such a feedback on users' performance and cognitive workload? Does the display format of this feedback have an influence over subjects? What if the feedback provides erroneous data? We designed a protocol to compare the influence of providing a cognitive load assessment gauge versus raw data versus no feedback in a Multiple Objects Tracking task. Reliability of this feedback was also evaluated. Performance in a dual task paradigm, pupil dilation and questionnaire were used to assess cognitive load. Trials duration and learning effect were used as control results. Raw feedback showed a negative effect while low reliability showed inconsistent results.