Hey,
Originally Posted by
Zionstrat2
However considering the wide variety of 'lack of hands on experience' vs. 'not using available data and automation' incidents (AF447, OZ214, Dreamlifter)...
Firstly, it could be argued that such interpretations are false dichotomies - e.g. the PF who pulled AF447 up into an unrecoverable state arguably had more general "hands-on" experience than most of his peers, but the experience he lacked was of manual handling at high altitude.
In terms of raw stats, there is no "debate" - advances in flight control technology and automation have improved flight safety. What tempers that conclusion is that those advances have changed the nature of incidents and accidents, such that when they do happen the question is frequently raised over whether a crew may have been able to better resolve the problem if they were more rehearsed in manual flying skills.
And AB is often criticized when automation takes control.
Which is in itself a fallacy. Brand A is no more involved in pushing automation than brand B or others.
Big data makes a big difference in other industries- For example, retailers use data mining algorithms to sift thru tons and tons of seemingly unrelated data looking for the potential for cause and effect.
That data is largely numerical in nature though. Data mining algorithms are becoming increasingly impressive at determining correllation in a quantitative sense, but doing so in an qualitative sense is considerably more difficult.
The idea would be to collect all flight data and outcomes over a long period and let the software look for potential relationships and make future recommendations based on those relationships
The problem with that is the requirement for natural language understanding to separate the technical issues from the operational ones. Unless the data has some kind of way to distinguish these things, there would be no way of distinguishing, say, a runway overrun caused by brake failure from one caused by a problematic approach.
Even if one brings in incident reports as an attempt to distinguish the differences, the ability to distinguish relies on the impartiality and wording of those reports.
This may be entirely unrealistic, but it will be interesting to see if anyone is already thinking in this direction.
The FAA are already using technology capable of performing "big data" operations, even if not in the way you're suggesting:
Customer Interview: FAA, Will Lawrence | MarkLogic