A case for the modern engineer (Part II/II: Skills)
The time has come that I am approaching my last semester at university and will soon be graduating with a master’s degree in engineering (if all goes to plan and not too many more global crises hit planet Earth). Over the past years I spent progressively more thoughts on figuring out, what it needs to become a good engineer under the extrapolated trends we currently observe in technology, economy and society. I already mentioned in the first part of this series (see here or here) that tech people should realise that the products they build have far-reaching impacts on society, manipulating intricate aspects of human behaviour. Something, I believe, that has never been such a powerful characteristic in the past and therefore needs modern engineers to be aware and take on more social responsibility. On the other side, we have so many crises on our plate that we should invest and combine our brain power wisely. In my opinion, the following fields should deserve most attention: Renewable energies; global internet access; decentralised production and services; smart mobility; sustainable agricultural solutions; biodegradable materials and recycling processes; 3D-printing and mass customisation; AI and automation of repetitive work.
In addition to the focus of engineering content, I anticipate a change in the skill set that will be needed. We can currently sense a strong wish for automation as this promises higher productivity rates. I am certain that the process will not stop with only making highly repetitive (both manual and calculation-heavy) jobs obsolete. With the increasing capabilities of AI cognitive, data-heavy/complex as well as generative/creative tasks will be progressively become automated, too. Take generative design for example: A design engineer will potentially no longer be using a CAD model to manually produce the desired shape to then manually simulate it over and over again. Instead the task will be to correctly frame a problem, set boundary conditions and find the desired requirements and finally an algorithm with in-built feedback loops will run simulations, iteratively experiment and figure out an optimal design. Consequently, engineering work will take place on a meta level focussing less on functional and logical details, but rather on generic solution principles. Under the key word of “mass customisation” we will develop generic, integral processes that can deliver all possible solutions to a problem (a high-dimensional solution space) without knowing specific requirements beforehand. We will then be able to pick the optimal design according to the given constrains. We can repeat it with different input parameters and receive another output, while the solution path won’t change.
This is a fundamental difference to most current design processes that are tailored towards pre-defined requirements and only deliver one solution. Changing constraints would cause a complete overhaul of the process and cost money and time. These anticipated trends will inevitably inherit a strong demand on the ability to solve problems in an abstract way. I feel lucky that I had the chance to attend some university lectures on design languages, solution principles and software architecture. Abstraction is a powerful approach in software development. In my view, a well coded program presents a flexible recipe for solving various specific instantiations of the same generic problem type. However, I do not see these things being publicly addressed by our educational system. In many of my university courses engineering knowledge is presented in a rather static, old-fashioned/traditional way.
Furthermore, I would like to question whether it makes sense to present out-dated technological developments in high detail or rather convey the trends that can be observed. When I am preparing for exams and being forced to learn certain specifications by heart, I feel like I cannot see the forest in spite of all the trees (German saying). Students should develop a strong understanding of the fundamental physics, yes, but otherwise can only prepare for life-long learning in a rapidly advancing environment. I believe our educational system should adapt to this by conveying fewer fact-based knowledge. Admittedly, this would come with a re-design of our current exams. Fact-checking is easy, I understand, but it rarely shines light on relevant knowledge. What I am asking for instead is a stronger emphasis on curiosity, flexibility, practicability and the freedom to learn in a self-determined manner. For sure this request cannot be merely placed on the institutions’ shoulders. People in our society must realise that education will be the absolute defining measure in the future (in the war against the robots to phrase it dramatically) and that everyone must take on a self-responsibility for his individual education. With regards to engineering I like to think about is as an inventive labour that combines science and creativity. We must assure that this romantic vision will fuel future engineers and not let five years of college sober them.
Finally, let me bring up what I value as the holy grail (maybe a touch of exaggeration here): Multidisciplinarity. I used to visit a boarding school which valued a holistic approach to education and I always considered myself a fan of the classical polymaths like Humboldt and Goethe. With ever expanding knowledge in our world, it becomes impossible to take on such a role nowadays. Nevertheless, I think it is desirable as a broad understanding of different aspects of life helps to evaluate situations and most importantly helps to deal with complexity. Interestingly, multidisciplinarity and the ability for abstraction in my opinion go hand in hand.
As mentioned above engineering will take place on a meta level, focussing on solution principles. Once machines are programmed to execute calculations and repetitive work, specialist will no longer be urgently needed. What then becomes important is to think multidisciplinarily and connect different scientific fields in a beneficial way. Successful examples of this may be bionics applications where we learn from nature. To my knowledge, SpaceX also implemented building strategies from agricultural silo manufactures to engineer their highly pressurised rocket fuel tanks.
All those different science disciplines are made-up by humans, presumably as an excuse to reduce one’s field of attention or as an argument to differentiate oneself amongst others. However, the reality of the physical world does not know this distinction. For me, the seed of future innovation lies here and can be brought to life effectively if we manage to split the work wisely between humans and machines.
Speaking for myself, specialisation always comes with the slightly negative connotation of narrow-mindedness, whereas expanding my knowledge like the octopus’ arms in all directions while also diving into literature and arts gets the child in me really excited!
