AI Efficiency Could Cost Us the Next Generation of Experts
This is a very though-provoking that applies much wider than just AI. In fact, its origins go back to long before AI was even around. It is applicable to whenever automation is involved with humans. The problem with humans is they get lazy, and they lose muscle memory over time, and it is even worse if they never gained the muscle memory in the first place.
Examples given are a nuclear power station where, despite the possibility of fully automated processes, humans are deliberately kept in the loop to perform approval and manual processes. This was to keep them current and to practice what they need to do.
The other example was the Air France flight 447 accident which could have been prevented if the humans in the cockpit were not so accustomed to flying on autopilot for years, and they could have still assessed what went wrong using their manual flight skills.
It really brings to the foreground some of the inherent issues we have with humans, and how these can manifest themselves when humans work with, or let AI do their work for them.
The real meat of the article though, is the long term effects, and how junior engineers become senior engineers through hard effort, diagnosing and understanding problems, and struggling for hours to fix something. Most of today's senior engineers and designers went through these stages when they started out as junior engineers. This learning process is vital to later growth and success in most field. What I learnt this way in the 1990s, I still applied many decades later, even with newer technology, as I understood how the fundamentals fitted together and interacted together.
We've already seen signs of this reality with studies about students using AI and where, without the AI in exams, they actually score lower than students who did their studying without AI. Of course there are always exceptions to this, and it is certainly not that AI is just all bad, but it is how we use AI with humans that is important.
Another study I have quoted before, also showed that organisations fared economically better when AI was overseen by humans using it, versus organisations trying to just replace humans with AI.
What is becoming clear, is there is nothing wrong with AI, and it will be part of our future just like telephones are, but we need to think about AI's usage alongside humans to ensure a good future for both. It is no good, in 20 years time when today's senior engineers are due to retire, to then wake up and realise we don't have any suitable senior engineers to replace them.
It also brings home what I have preached before about just outsourcing everything to an external cloud provider. The organisation loses all its ability to deeply evaluate and quality assure any cloud provider because they have lost their own internal skills. If you ever want to withdraw from that external cloud provider, they have nothing to fall back on.
It all comes down to the same final argument in the linked article: “Deliberate inefficiency is not waste. In safety-critical engineering we have always known it as insurance, and we buy it on purpose”.
The linked article is really well worth reading, and should be part of any AI awareness training for senior management. Just looking too at some humans who have committed suicide based on “advice from their AI therapists” we humans have our own failings, and we need to consider how we use and interact with AI to harness it successfully into the future. This is probably going to be really fertile ground for doctoral thesis in the coming years.
See
AI Efficiency Could Cost Us the Next Generation of Experts
Lessons from aviation and nuclear power show how to preserve human skills
#technology #AI #skills
