Could data mining help with the automation vs. hand flying debate?
Although I am an aviation fanatic and with GA experience, I am a technology strategist by trade and rarely post on aviation forums- However considering the wide variety of 'lack of hands on experience' vs. 'not using available data and automation' incidents (AF447, OZ214, Dreamlifter), I'm wondering if this would be a good time to consider database systems that learn and advise in unusual situations?
I'm aware of point specific systems like TCAS and GPWS that address very specific problems where unsafe parameters were defined well in advance. And AB is often criticized when automation takes control.
But has anyone considered a more generalized database approach that simply provides observation/recommendations to assist in unusual situations?
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. Significant relationships that are entirely unknown are often discovered (the apocryphal example is the relationship between beer sales and disposable diapers in convenience stores).
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-
Of course the data could be wrong, causality could be off, and there are many reasons why this wouldn't work all the time. Data mining is never 100% effective, but it provides an additional input that isn't otherwise obvious to humans who have limited bandwidth.
However, with enough data, it seems likely that an independent system could easily announce:
• This seems to be an approach to a stall- Consider these remedies...
• You appear to be in a full stall...
• You appear to be well below the normal glide slope...
• You appear to be on final for AAO however the flight plan lists IAB as the final destination...
I imagine pilots might not appreciate another potential conflicting data source and the 'big brother' aspect. However think about this-- automation is likely to win in the long run for many reasons and it is very likely that similar systems would be integrated as automation increases.
So why not get ahead of the game and see if this would add value now? In the test phase, system recommendations could be withheld (to avoid conflicts with current procedures) and it would be relatively easy to monitor the recommendations that would have been made until the recommendations are strongly correlated with outcomes.
I'm sure some will say that this is just another prop to hold up the undertrained and that airmanship would suffer. But unlike GPS, ILS, or even the introduction of VORs, we're not talking about a system that simplifies the job or reduces the workload- the pilot still has to do everything as usual-
The system I am describing would be 'learning' all the time, but only come into play in the rare occasions when it appears likely that something is significantly wrong and the pilot still has the last word.
This may be entirely unrealistic, but it will be interesting to see if anyone is already thinking in this direction.