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Although the person you hire for a particular job may have all the correct qualifications, sometimes said individual does not perform as well as expected. I should know. While employed at a public relations company in England, I decided it was my duty to inform our clients as to how I thought they should run their PR campaigns. So rather than listen to what the client wanted and duly perform those tasks, I told our clients what they should want.
Needless to say, the resulting personality conflicts resulted in my dismissal from the company after just a two-year stint. Luckily, I have contacts. And one of them, Dr. John Miklosz, then-editor of Computer Design magazine in the United States, offered me a position on the editorial team. Before I could be hired, however, Dr. John had mandated that every new employee be given a written test to probe their knowledge of the fundamentals of writing style.
After an eight-hour flight, I was put to work, editing numerous manuscripts. After passing the test with flying colors, I was fortunate enough to be hired as an editor for the magazine.
In today’s competitive environment, those companies involved in machine vision and image processing must also be careful when hiring new employees. But how, for example, could one judge the capabilities of a C programmer? Of course, programmers could be tested on their knowledge of pointers and references, and stack, queue, and linked list data structures and other textbook-learnt concepts.
Better yet, any potential candidate could be asked to write a program to perform one or more of the specific tasks the company was looking to implement. And still this would only paint half a picture of the capabilities of any particular candidate.
In the future, however, companies may more properly evaluate a particular candidate’s capabilities with the help of psychometric theory—the science of measuring mental capacities and processes. It’s a given that the measurement of unobservable phenomena such as a person’s knowledge, abilities, attitudes, and personality traits is difficult. But researchers at the University of California–Santa Barbara’s Brain Imaging Center have recently developed a system that can predict how much a person can learn.
To do so, the researchers collected MRI imaging data from people performing a motor task and then analyzed how 112 different areas of the brain connected while they performed the task. This connectivity or “flexibility,” the researchers concluded, seems to be the factor that predicts learning. Thus, if a person’s brain is more “flexible,” the person will be better at learning.
Hypothetically speaking
Such systems are still in the research stage; in the future, they may well be used in conjunction with heart-rate monitors, facial recognition systems, and perspiration monitors to discover the true abilities of an individual. Of course, just as there has been an outcry from civil liberties groups who argue that backscatter x-ray machines should not be used in airports, there will no doubt be those who similarly argue that such technologies are an invasion of privacy and subject to false positives.
Fortunately, I am not one of them. Just as machine-vision and image-processing systems have benefited mankind in ways as simple as sorting apples to more complex tasks such as the automated diagnosis of tumors, the systems can also be used to evaluate the capabilities of the next generation of engineers designing them.
Although I can see the advantages of such systems, I am not sure whether I would have liked to see the response from my own brain scan and how it might have affected my chances of landing that editorial job all those years ago. From what some people tell me, such a technique may have revealed that I was far too intelligent for the position I was applying for!
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