From the opening remarks to the last session, many presenters and panelists raised the issue of people in the midst of the drive to automate. This showed that people selling the port automation technology and people buying that technology are uncertain of the impacts on the total size of the workforce. Nobody wants to lose a job to a robot and no decision maker wants to displaced by a freely thinking intelligent software program (yes, let’s not call it artificial intelligence). Then what gives?
I had the sense that nobody links increase in job opportunities within the port universe, while the automation displaces humans. Maybe because arguments of positions created in off-terminal logistics center as not as rewarding as driving equipment around the terminals. Temporarily, I have to leave this question unanswered.
Even more important to understand is that progressing automation requires changes to job descriptions and work instructions for people who will not be replaced by the machines, but will have to handle coexisting with them, if not outright collaborating with them as if they were humans. Impetus for this discussion came from the decision by Port of Singapore Authority (PSA) deciding to retrain 1,500+ engineers and you will be surprised in what they will be retrained. As it happens, the completely new Tuas container port in Singapore is envisioned to operate autonomously on the terminal grounds, from the vertical and horizontal transport machines to the back office where algorithms will be searching for the most optimal behavior of the machines handling the cargo.
The trouble arises from the fantastic notion of all those technologies being equal to humans with the distinction of not taking any breaks and working relentlessly 24/7. As you hear countless sales presentations of software vendors vying to operate in such environment, the humans will only be needed to handle “exceptions”, or what we would call in laymen’s terms, things too complicated to solve for the machine and the algorithm(s). Can you imagine complexity of the problems falling into the “exceptions” bucket? That is what clearly worried people at PSA, which gave the signal to start preparing the technical and operations workforce to become future saviors of the “thinking machines”.
While I would love to imagine a complete training course that could prepare people to handle what machines won’t be able to solve, I can’t stop thinking that whatever we can teach in class will still be insufficient to handle the actual problems in real life. I think that the most challenging aspect of such training is human ability to walk back in their minds over what happened and what they decided prior to the moment of running into the problem. That allows the humans to do two things: address earlier problem and restart the process where it was abandoned or makes the most sense to be restarted AND learn for the future. This is much more challenging when we decide to teach machines to react in the same way. It is a lengthy and rather complex process. That is where people coming from the berth and yard positions will be irreplaceable, as this is no job for a learned data scientist, back office employee, or someone coming from outside the terminal operations environment.
I am looking forward to hearing from the people working in transport and logistics industries where jobs are being affected by progressing automation.
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