This post was inspired by a question on Quora and so I put my answer here on the blog as well.
Looking in our heavily research driven crystal ball, we see the following 15 engineering disciplines the most sought after in the next 25 years. In the following 25–50 years thereafter it will change a bit as AI and model engineers will build ever smarter systems that can do quite some of the engineering work – but for many reasons we are certain – not all !!!

AI / ML / NLP and friends engineering

By 2030 AI will be in any product or many components of a single product
approx. a million open positions as of today, Dec 2018

Algorithmic engineering (mathematicians)

> It’s the substance AI is made of and we need hundreds of thousands of them

Model engineering

> The biggest challenge in AI: Creating the model of what AI should be intelligent about

Molecular engineering → Molecular model engineering

>A precursor to smart materials, bio materials and much more

Smart Material engineering → Smart Material model engineering

> By 2030/2040 isch it will affect most everything we produce. Any material we deal with in our everyday’s live may be smart and do things that we can’t believe today/ It’ll be as big as AI is today if not even more revolutionary

Bio engineering → bio structure model engineering

> By 2040 it is the base for augmented human bodies. Getting eyes like an eagle, joins like a panther, reflexes and organs we can only dream of today. But it will also change the way we see all life around us and the influence we may have.

Robotics → Robotics model engineering

> an obvious one – yet the robots of the future, past 2040, will be very different. Not because of AI but because of the smart material and the bio engineering development.

Autonomous machines engineering

> Today we see robots, cars, etc. as autonomous machines. Tomorrow, 2025 onwards, we can add IOT and other autonomous devices to the mix. By 2050, we can see far remote machines on the Moon doing work we won’t do on earth…

Nano Technology engineering (re-started)

> Carbon nano tubes are revitalized as material we could use to build a space elevator and other crazy things we cannot do otherwise.

MedTech engineering → MedTech model engineering

> BY 2030 we can finally expect getting nanobots into our body for surgery but also as monitoring and other robotic tasks. It will be only the top level in that space. There is a lot ongoingly that will need very specialized engineers.

FinTech engineering → FinTech model engineering

> Whether we have a cryptocurrency comeback or a new development on our “old” currency, by 2025 blockchain like technologies is in the financial business future.

SecureTech engineering

> 2020 to 2525+ everything we need is vulnerable on its own. Security is, was and will remain to be a huge part of our technology world.

Energy systems engineering

> 2020 to 2525+ whether we will harness one day the gigavolt flashes (~10 Billion volts) or leverage our abundant geothermal energy, everything we do will need ever more energy.

Civil engineering (urbanity trend eyc.)

> Already today we are building more and bigger cities in the next 20 years until we experience the turnaround back to country live around 2050/2075 or so, especially when not only all production but also must services will be automated. In the then following 50+ years we will rebuild earth like we cannot imagine today.

Quantum computing engineering perhopes

> Not sure if we ever find a solution to the still unstable quantum states in the quantum computing theory. But if – lots of engineers will all of a sudden be needed.

There are many many more like food engineering, life style engineering, education technology engineering, health care engineering, and so forth, but the above give you probably a good idea where we are going.

P.S.
Why do we (World Innovations Forum) think so? There has never been a technology that was invented and in less than 10 years mainstream. Since we see what is in very early stage development of startups, we can see well into the next 10 years. New inventions and findings coming in in the next 10 years, will take us well into 2035 which are obviously very hard to predict. But we can at least try to predict the development that will come on top of the current development like robots that will advance but will advance even further when other developments like smart material have advanced. That brings us into year 2050. Thereafter we can only see consequences of the development we predict like the turnaround of urbanization and megacities. If most people no longer work in corporate bird cages but do things they simply love to do, join the makers movement, start their own little business and so forth, there is not only no need to live in a city but possible an urge to go back into countryside. That assumed consequence gives us fruit for thoughts beyond 2075 into 2100 or so. Again nobody really knows but we have ever better indicators and prediction models improving accuracy and to do what we do :)

I see thousands of horror stories and get hundreds of fearful questions like will AI be harmful to humans, will “they” take over the world. People see them already as fully developed beings and thousands of times superior over humans. There is an interesting psychological analysis about that – but first let me stop this absurd craziness.

WHAT IS ARTIFICIAL INTELLIGENCE?

First and foremost AI is a piece of software. It is typically written in very well known and for decades widely used programming languages such as C, C++ or Python. To make the software do what is smarter than just “if this happens then do that” software developer are using smart algorithms – mathematics. Another technique that is used is so called “Neural Networks” – but also that is pure software. The neural networks is a mechanism that is seen in our brain handling all kinds of filtering, sorting and decision providing mechanisms. So all in all, AI is software, math and libraries of techniques.

Instead of keyboard and mouse, so called “Natural language Processing” tools or in layman’s terms: speech recognition tools are used. So we can talk to the computer and it will talk back by using speech synthesiser. And since we are used to use web cams, electric thermometers, GPS and stuff, we can attach these to the computer as well.

Now the combination of computer, software and all kind of sensors, the “machine” looks much smarter than before. But hey, it is still a machine, doing what the software we wrote, is dictating it to do.

Another thing, which started the avalanche of hysteria and craziness, is the idea that in the combination of smart algorithms and neural networks, we can actually program the machine to “learn”. The only magic in this is that we humans have an enormous respect for “learning”. The machine however learns VERY differently than we. Give the machine 100,000 images of dogs and it will learn how a dog looks like. If we now add a dog in 100,000 other pictures where also cats and other animals are in, the likelyhood to recognize the pattern of a dog is pretty high. In contrast to a human, my daughter took about 20 to 30 impressions of a dog to “learn” what a dog is. She also learned that a cat is a similar animal but not quite the same.

Why is AI such a big deal

Well, you could give an AI system the construction plan of a car. Then ask it to create an optimal body, that is as light as possible, as stiff as possible, has a dynamic material behavior in case of a crash and considerable ,ess expensive.
The AI system could instead of only 100,000 views take 10 Million iterations of each component and come back with a design where the car is only 100 KG instead of one ton, has a network style body instead of full material and using all kinds of stiffness measures that it is stronger and at the same time lighter. With less material and for instance only steel at certain point, carbon in others and so forth it would eventually cost 50%, weighs only one 10th and is much safer. Artificial INtelligence can be programmed to do things like that basically anywhere. Making enormously precise Weather Forecasts, analyze stock exchange behavior of thousands of companies over the past 100 years and the behavior of investors by the minute to predict much better value development. It can help analyze illness, make more accurate and more neutral decisions as a judge and so forth.

If it is so cool – why don’t we do all of this now?

Well – AI is still in development. Approximately 1 million engineers in approximately 100 countries work independently on all kinds of solutions. Mathematicians join the software developers and vice versa. However it is by far not as easy as many people think. The most advanced development right now is autonomous cars. Invented originally in Germany in 1992, where the first autonomous car drove 2,000 KM from southern Germany to Scandinavia and back, all in autonomous mode. Autonomous cars may then take 20 years to get all the kinks out and be safe enough to get on the road. Politicians go back and forth whether they should support it or not, the public is in hysteria to say the least and there is a lot of uncertainty about how AI could be turned into weapons.

What risk remains with AI?

Let’s assume for a moment, we would not have automobiles today. Now somebody would come and suggest we build cars and street, but also need to take in consideration that every year more than one million people will get killed and 20 – 50 million insured. Would we allow that anybody is building those killer machines? Never ever I guess. But the CAR is not the killer it is the human that drives the car. Like in all other ares, the human that uses the gun, the human that uses the knife, the human that drives the tank. Yes, AI and Robots could be build to go to war, kill the opposing country and possibly wipe out a nation. But it is not the robot that magically makes that decision – it is the human that designs it. And as seen in 1945 in Hiroshima, we could do that already in the last century.

On the other hand, we have 340 Million occupational deadly accidents a year. How about accelerating the AI and robotics development to get machines into those jobs and safe 340 Million humans each year. This is more than people dying at wars and accidents all together.

Yes, there are risks that ill-minded people take this technology as a weapon against others. We saw this with Social Media, the Internet, any type of technology in the past. and we need to do everything to prevent them. But those machines build from plastic, silicon and metal will not magically turn into living things with a purpose we didn’t program and wipe out all humans or stuff like that. Those visions – even coming from people like Steven Hawkins – are based in a huge deficiency of understanding what humans really are and that our “intelligence” is not more and not less to our brain, than the muscles are to our body. Today we can lift thousands of times more with our cranes than with our muscles. Soon we will be able to think through constructions or algorithms thousand times more complex than we can calculate with our brain. But one thing have cranes and AI in common: Humans have developed them and have the interest and responsibility to make them as safe as any way possible.

Autonomous Machines, driven by Artificial Intelligence, are no living beings with a purpose to kill us. They are machines with a purpose WE GIVE THEM. And if that purpose is killing, then it is still us who made it that way. It is not something THEY CAN DO unless we allow it to go that way.

15 most wanted engineering skills in the future