Engineering recruiting is accelerating rapidly. As I have shared many times in the past, we are in a ‘War For Talent’ for key engineers, scientists and other technical talent.
In the future, engineering recruiting will place a much higher value on information rather than on data and leverage AI at the edge when necessary.
The ability to quickly find, validate, and leverage interdisciplinary knowledge will be a critical challenge for many engineers and engineer-entrepreneurs.
As we encompass art and human-centric design principles both in engineering education and in our everyday practice, our ability to positively influence our lives and our world will continue to reach new heights.
Unfortunately, many hiring managers and executives have come to realize that demand for a key engineer, scientist or other technical candidates far exceeds the supply.
What Is The Future Of Engineering Recruitment?
In 1902 Charles Duell, the United States Commissioner of Patents, said: “Everything that can be invented has been invented.” I think he was proven wrong.
Nowadays attempts to predict details of the future of engineering or any technical, R&D or scientific field are fraught with folly. But history does provide us with a few insights into what might remain the same.
For example, unforeseen and previously impractical technologies are certain to foster new industries. Key market opportunities will correspondingly accelerate the discovery, development, cost-reduction and ultimate widespread adoption of those technologies. This is as true today as it was when the first Roman aqueducts were built or when Watt and Boulton improved upon Newcomen’s steam engine and helped to catalyze the industrial revolution.
A more recent example is the invention of autonomous automobiles. They seemed to suddenly leap from the realm of science fiction into reality in less than a decade.
What new factors may influence the nature of how we approach problems and develop solutions as engineers?
Information Will Change the Future of Engineering
We see every successive generation of engineers enter a world that innovates faster by collectively gathering engineering and technical tools and knowledge from their predecessors. This too, seems unlikely to change.
However, the tools at hands today, such as the proliferation of low-cost 32-bit microcontrollers, pervasive wireless connectivity, novel sensors and Internet of Things (IoT) functionality present a possible inflection point for the practice of engineering.
The first is the need for sensor fusion and data abstraction, “at the edge.” Why? Sensors are everywhere. After all, sensors are the eyes and ears of smart and not-so-smart products.
At a high level, the constant stream of measurements provides a flood of data. Often this leads to a “deficit” of useful methods to transform that data into meaningful, actionable and potentially profitable information.
In essence, IoT proliferation presents us with more data than we know what to do with. In the process it consumes excess bandwidth resources and energy in the process.
This suggests we’ll need to understand and creatively leverage distributed artificial intelligence (AI) to perform data abstraction at the edge in countless fields. These applications include robotics, medicine, factory and home automation, agriculture as well as for other sensor/mechatronics-based applications.
It won’t be enough to design-in the latest set of sensors. We’ll need to think in terms of information, not data. AI won’t be relegated to academia, consumer devices and personal assistants. Nor will it require expensive dedicated processing hardware or cloud resources.
AI will follow the path of low-cost 32-bit MCUs. It’s destined to be an essential component in many products and a frequently used tool in our design arsenal.
Just-in-Time Information For Interdisciplinary Applications
Another factor may be the requirement for us to balance a reliance on our current “traditional engineering” skillsets. We need to balance this with a just-in-time approach for gathering knowledge in other domains such as biology, botany, chemistry, optics, music, art, etc.
Think of this as an evolution of the just-in-time/best practices used in manufacturing. It’ll play a key upstream role in a product’s market definition, concept development and design phase.
Let’s say you’re involved in designing LED architectural/industrial lighting systems and are very experienced in this domain. You understand your end-customer’s correlated color temperature (CCT) and intensity requirements. You use familiar tools for thermal analysis and optical modeling.
Now you or your company becomes interested in entering the horticultural lighting industry. An LED module is an LED module, right? Perhaps, but the “end consumers” in this case are plants.
From an electrical perspective a properly designed horticultural lighting unit isn’t radically different from other lighting products. However, the LEDs may need to be selected to provide the optimum wavelengths (colors) and output power. These generally vary by plant type and its developmental growth phases.
In fact, even the unit of measurement for optical power will be different. Instead of the familiar foot-candles or lux (illuminance—the quantity of light falling on a given area), you’d probably be presented with a target value for photosynthetic photon flux density (PPFD). This is the number of photosynthetically active photons that impinge on the surface of the plants each second.
You’ll need on-demand practical knowledge in some aspects of plant science, ideally for the particular target plant. Your electrical and mechanical design experience will not be enough. Another example is the task of upgrading an existing MCU-based product like a home appliance to enable IoT functionality. The hardware changes may be relatively easy because so many off-the-shelf communications modules are available for LTE, WiFi, Bluetooth, LoRa and so on.
Indeed, hardware will not be the design challenge. It might be security, to include:
• determining the business-risk and cost of a data breach,
• uncovering and addressing all of the potential attack surfaces from your device up through to the cloud,
• preventing device “spoofing” with proper authentication and
• how to deliver secure over-the-air firmware updates.
Again, you’ll need on-demand practical knowledge.
Where Does Science End And Art Begin?
The third factor will be the increased significance of art and graphical design into our practices. This correlates with the trend to enrich students via STEAM (Science, Technology, Engineering, Art and Math) teaching concepts. As new engineers, our sons and daughters are viewing these as entirely synergistic disciplines.
For some anthropologists (and primatologists) there is one common synergistic characteristic. It is a tool in the user’s hand (or claw, beak or what ever) should function as a “transparent extension.”
Jane Goodall first observed chimpanzees gathering sticks, stripping off the leaves and using them as “fishing rods” in insect mounds. She realized the sticks were transparent. In other words, the animals didn’t view them as sticks any longer when using them for insect fishing. The sticks were functional extensions of their hands and fingers.
How does this apply to the question of science-art boundaries?
There’s a not-so-subtle shift in product design in the consumer space. This is especially true for immersive interaction experiences that reflect the user’s lifestyle, or the activity they are focused on. The device itself might be secondary.
A recent example is Samsung’s new series of TVs “The Frame”. When the TV is off, it becomes a framed work of art. Users can even browse and download new art from Samsung’s “Art Store.” Those TVs have a degree of transparency. Just as the stick isn’t viewed as a stick to the chimpanzee, the TV is no longer a TV when it’s off.
Design aesthetics and functional, thoughtful design really do matter. It’s evidenced by the most common interface people use for their smart appliances—the app on their phones.
The general (and long overdue) trend is for smart devices to conform to the user’s expectations, not the other way around. This provides a measure of transparency for the hardware and firmware.
Future engineers are destined to embrace human-centric design principles as well. Emphasis on contextual awareness and understanding the user’s implied intent may be placed on a par with circuit performance. It can be an important differentiator in the marketplace and help establish a compelling brand preference.
We will increasingly live and work in a world where unrelated devices and processes must interact with each other. The future of engineering will therefore need to encompass mechanisms to acquire just-in-time knowledge across a wide range of domains and disciplines.
Engineering students will be taught the value of finding and validating this information quickly, applying that knowledge to other disciplines while considering human-centric design principles.
The enormous future challenge is to find skilled talent encompassing all these disciplines. That challenge may already be upon us.
I have a recommendation to help meet the demands for key engineers, scientists and other technical candidates in our “War For Talent”. I recommend more aggressive and creative recruitment strategies such as my 12 Commandments of Recruiting for successfully staffing your organization.