Though this processing of big data, the algorithm will make discoveries about the world that it is incapable of disclosing to humans. Instead it will act on these discoveries in an attempt to optimize some objective. There is a much more profound benefit of this arrangement: if the humans were to become aware of the discovery, they may be incapable of handling it. Humans will panic at the implications.
When considering whether to admit dark data to the data stores available to our algorithm, we can ask what would be different if we did not know this information, even if there is good reason to believe it to be true.
It is conceivable that our faith in science over observations could return the human condition to where it was at after the fall of the bronze age, only the mysterious monuments would need to be explained by even bigger giants. The risk of this happening is significant even if it is unlikely.
In the case of COVID19, we demand extraordinary evidence before accepting the normalcy of this pandemic. This sets a major precedence for all future novel diseases. From now on, we need to accept that anything new is an existential threat to humanity until evidence conclusively proves otherwise.
I put myself in the chair of the host and hearing someone ask me what they should do about their huge debt. I hope I would have the strength to hide my thankfulness of not being in their position, and instead look at their core condition. Debt is a fact of their existence. The worst advice is to say they need to get that debt to zero.
Looks do matter a lot in social and professional success. What really matters is that our looks match our personalities and aptitudes. Many of us do not live up to our appearances. We can try to compensate with changing things we can control, but we can not escape the messages sent by our height, our skeleton, and especially our facial features. The alternative is to work on our personality, changing it to match what people expect from our features. Many of us do that, but we never convince ourselves so it is always an act, and that act will eventually be exposed for what it is, leaving us where we started, alone.
Automation is needed for the operations productivity, but it adds new labor burdens on humans whose incentive of self-protection from automation drives him to pay attention to the credibility of the sensors in terms of correspondence to what it is supposedly measuring. The problem might be solved by live streaming of sensor observations of physical world back to some operations control center where a small staff can monitor all currently operating systems. This would require a data network to handle the data traffic in an timely manner, but I believe this is the right solution if it is feasible. Such as center would validate each sensor’s information against all information about the aircraft’s environment, and they would have the means to directly initiate the process to remove the bad sensor and mitigate its subsequent absence. Such a system also would allow the periodic review of more detailed sensor data collected from all operations to find anomalies that would identify the misbehaving automation, flagging it for engineering or certification review.
Evolution of species may really be an evolution of an ecosystem. That ecosystem could respond emotionally and that emotion motivates it to find some solution to relieve that emotion. Emotionally driven intelligence would almost always come up with flawed designs. Those designs would satisfy the emotions instead of the intelligence.
These are just thoughts that occur to me, a person who has no knowledge about the current realities of the engineering and data collection within the airline industry, but a person who recognize the value of comprehensive data collection, storage, and retrieval from actual operation of advanced designed systems, especially those designs that rely heavily on computer automation and simulation.
We should study observations separately from derivations from theories. The deliberately ignorant takes the position that data is superior to science. There is a valid place for the deliberately ignorant when included in teams with domain experts representing each of the relevant scientific disciplines. In order to work, the deliberately ignorant needs to be skilled at his craft of being ignorant in the right way to propel the team towards a new solution without annoying everyone to the point of being expelled.