Editor’s note: Mark Bagnall is head of innovation at market research firm Basis Research, London. Kate Hartzell is senior vice president of the same company and is based in Los Angeles.
The concept of machines replacing human researchers is very prevalent at the moment, though the broader theme of robots and artificial intelligence replacing people seems to come to the fore every so often. Further back, similar fears surfaced in the face of mechanization and the industrial revolution. This is not a new fear! Or perhaps more accurately, this is not the first time news fodder has played into that fear.
As market researchers, we rely more and more on machines and algorithms to supplement our work, but we support the argument that we’re a very long way from being replaced by them altogether. The two fundamental disciplines of science, the theoretical and the experimental, help explain why.
Oddly, we have to go all the way back to 16th century to find a time when theoretical science dominated, where thinking about why things are was prioritized over doing. Descartes, the French mathematician and philosopher, was famous for carrying out theoretical science while sitting in his armchair. Simply, he thought about things.
In the 17th century, our ability to manufacture equipment such as telescopes, microscopes and other scientific gadgetry created a sea change towards experimental science, people could now do a lot of the things they had so long hypothesized about. And, it was a lot sexier to tinker with these new toys than sit around in an armchair and ponder. In fact, the Royal Society in England famously put on a show of experiments for visiting dignitaries including weighing air, demonstrating magnetic forces and showing how hydrochloric acid could eat through flesh. Excitement in experimentation was palpable!
One of the lone champions of theoretical science of that time, philosopher Margaret Cavendish, challenged this hard shift towards experimentation. In her 1666 book Observations on Experimental Philosophy, Cavendish warned against the belief in experimentalism alone. To paraphrase her arguments, how do you know what to experiment on if you don’t think about it first?
Theoretical science of course still exists today – there are many people (scientific theorists) that make a living out of theorizing why things might be so, and these people never do physical experiments to prove or disprove these theories. They leave that to the experimental scientists. The truth is that there is a symbiotic – and vital – relationship between the two disciplines. Quite often, theorists and their theories prompt experiments, and vice versa. Possibly the most famous modern day example of theory leading to experiment is The Large Hadron Collider, the largest machine in the world. Its purpose? Provide physicists with a way to actually test out various theories, predictions and other unsolved physics conundrums scientific theorists have been pondering.
Why is this relevant to market research? At its core, market research is about understanding people: their oddities, idiosyncrasies, behaviors, dreams and fears. To truly understand people, only other people (we as researchers), with a free-thinking capacity to theorize, can carry this out. Clever computers might be able to beat a human at a game of chess, but they are a very long way from pondering the future brand value of a cartoon mouse in white gloves, red shorts and yellow shoes.
Yes, machines are very good at helping us carry out experiments in research. From statistical analysis and data computation, to heart rate monitoring and galvanic skin response, and even at recognizing the emotions behind facial expressions, machines benefit us and our work. Let machines assist us in testing our theories but let’s stop the cycle of fear-driven news. We are not going to be replaced by robots. We should thrive on the symbiotic partnerships we have with machines, just as the theoretical and experimental scientists thrive together through their respective disciplines. A recent evolution that runs alongside this argument is the concept of collaborative robots. To us, this seems a much more sensible and realistic future for the market research industry and indeed, the world at large.
When the day comes that a machine conceives of and writes theories on the arithmetic of passions or “the head of a man compared to a hive of bees” as Cavendish did nearly 400 years ago, then we’ll have a true reason to worry!