Today's Paper Digital FAQ Coronavirus Updates Latest Obits HER Jobs Classifieds Newsletters Puzzles Circulars
ADVERTISEMENT
ADVERTISEMENT

What is the common factor between taking a hot shower in the winter, getting a ride on Uber, and talking to Alexa? Deep learning, and our ever-increasing dependence on machines! These things have become all so commonplace that we may have even stopped to think about what makes all this possible. To what extend will our reliance on such smart machines continue to grow; is there a limit to how many things may become automated.

To carry out my favorite pastime of the day taking a nice hot-shower I find myself having to adjust the tap lever to keep the water running at the perfect temperature to my liking. When the temperature is just right, I can let my mind wander and ponder about as many things as my heart desires. The other day while taking a shower, I asked myself, "what if the temperature could be adjusted automatically to my desired temperature without any manual intervention?". Being an engineer, I thought of the simple schematics of how such a solution would work. A sensor will measure the temperature of the running water, feed the signal to a processor which will compare it with the desired, set temperature, and the error difference will be fed back to the electronic valve that will modify the ratio of incoming hot and cold water accordingly until it is adjusted to the desired temperature. Simple, right? Yes, but it has taken control engineers decades to discover, understand, design, and incorporate such automated systems. Systems that can minimize, or even eliminate, the need for human intervention and manual work.

During the last few centuries, we had successfully transitioned most of the physical work from human labor to new forms of mechanical labor. Most of the physical work has been delegated to machines in the shape of robots. Imagine old times, ships being human-powered, hand grinding of the wheat, manual pulling of the water from well, too many other such chores within the home or outside in the commercial domain, were done manually. We have now developed ways to do all this with automatic machines. However, the new endeavor we have been enticed with is: can we have these machines become more intelligent? The goal is to see them more autonomous and not always needing human guidance and supervision.

When was the last time you took an Uber ride? Imagine that you ordered the ride using your cell phone, boarded the vehicle on arrival, and silently waited for the destination to disembark. I know silence was hard to imagine, given the socialization is built-in within all of us. Nevertheless, let us look at this example more closely, apart from the physical carriage, we have achieved the outsourcing of intelligent maneuvering of the vehicle through the traffic in this Uber ride. From a rider's perspective, the Uber ride is like an autonomous (self-driven) vehicle, though fitted with a biological processor (the human), working as intelligent transportation. In general, our new challenge is to replace this biological processor with an electronic processor that will help us free another human resource in the shape of an uber driver.

The usage of Alexa as a digital assistant is yet another example of the automation we are now confronted with. From industrial and commercial usage, automation is now entering the household and activating smart homes. In its initial form, it is open-loop control, where the instructions are implemented and not questioned. But we are moving in that direction whereby the instructions will be minimal and some of the action will be independent of the humans i.e., putting the coffee maker on at a certain preset time. Imagine the machine predicting and implementing the instructions on its own. On the lighter side, we will be told what we need to drink or maybe even further whether it is good for us to drink or not.

Freeing humans from the physical and now mental work too, could be creating brand new social issues and problems. Unemployment is the most important and widely discussed issue of these all. Some of the experts in Artificial Intelligence (AI) are predicting that we might have almost 40% skilled jobs displaced or at least become displaceable in the next 15 years or so. It is hard to deal with or get prepared for such disruptions.

Technology has always been creating such dilemmas for humans. Though, the good thing and hope are that we always met those challenges and used the developed technology as a tool for opening new avenues for human pursuit. We, humans, always need challenges and adventures. We get bored with repetitive and mundane routine things and therefore need machines for such tasks. The solution and right strategy could be to start working right away towards rehabilitation of the present workforce and establishing the right direction for the future workforce.

Innovation, creativity, out-of-the-box thinking, rapid adaptivity, agility, are becoming more relevant and an essential need than ever before. Academia with the help of legislators needs to meet such challenges upfront and take the lead to redefine the future. AI is not an option in the future rather it is the future. We must get ready to deal with the challenges AI is bringing to us and not be afraid of it. Innovation for long has been removing the pains, be it physical or mental. Let us welcome the new challenges together.

Strategically, we can priorities making the present jobs more efficient, reliable, and safe using AI than displacing them with totally automated jobs. A gradual phased seamless roadmap that helps us embrace AI with the least amount of disruption is a challenge we must work out. Let us not forget about privacy and other social issues as well which can create insecurity and anxiety in the public at large. Cybersecurity and corporate social responsibility are also vital ingredients towards our next recipe to success. We have led the world in productivity for almost a quarter of a millennium and now a long-term vision for the next quarter is at hand which can also be met with excellence.

Dr. Fawad Rauf is an associated professor of electrical engineering at Texas A&M University-Texarkana. Email him at [email protected]

COMMENTS - It looks like you're using Internet Explorer, which isn't compatible with our commenting system. You can join the discussion by using another browser, like Firefox or Google Chrome.
It looks like you're using Microsoft Edge. Our commenting system is more compatible with Firefox and Google Chrome.
ADVERTISEMENT
ADVERTISEMENT