All of us are constantly taking in information and make predictions or guestimates on what an outcome might be. All of us take in information and fill in any gaps in that data with what we’ve learnt from previous experience. And we are all curious.
These are the reasons given by three data science professionals as to why we are all data scientists.
According to Luke Horgan, the director of digital experience delivery at US Automobile Association, every one of us applies the principles of data science to our everyday lives without even knowing it.
We demonstrate this when we are driving towards a junction with several skid marks because we slow down and approach it with extreme caution. We avoid patronising particular restaurants that look run down and dirty because experience has taught us that eating from such establishments could be hazardous to our health.
Horgan said that even dogs do data science when they predict the trajectory of a ball that is about to be thrown to them in order to catch it. He said that we do this because the key part of learning is trial, test, experimentation and adaptation.
Rebecca Nugent, associate department head and director of undergraduate studies in the Department of Statistics and Data Science at Carnegie Mellon University, has a similar view. That every time we cross the road, we are building probabilistic models and are employing statistics to predict the trajectories of oncoming vehicles and time our crossing precisely to safely cross the street. “It’s probability and statistics at its best,” she said.
Nugent said that another instance in which we employ the skills of a data scientist is when we continually assess and reassess our surroundings in order to avoid bumping into another person in a crowded area. Or when we check the clouds in the sky or the moisture on the ground to determine whether or not to leave the house with a raincoat or umbrella.
Speaking on a similar topic of the essential skills of a data scientist, Jose Miguel Cansado, head of global accounts and consulting at Alto Data Analytics, stated that what differentiates a human data scientist from a machine is the curiosity to turn data to insights. “Big data needs the curious brain of an artist to make a difference,” he said.
These three experts were speaking to a wide audience on the TEDx platform, and I agree with them to an extent. I would view curiosity as one of the defining traits of humanity and I see our ability to navigate our surroundings and predict and anticipate the actions of others are essential skills to be able to move about our environments relatively unscathed.
So I would agree that almost all of us employ some of the disciplines of data science on an almost constant basis. We figure out the chances of a particular incident happening. We simulate scenarios in our minds by imaging various factors that could produce different outcomes. We anticipate how our actions or the actions of others will produce a certain effect.
But how many of us could use these innate skills to work professionally in the data and analytics field? How confident are we in our mathematical abilities to even see data and analytics as a viable career choice? I would suspect not that many.
Years ago, data consultant Mike Bugembe said to me that the way maths is taught needs to change so that students learn about the creativity of the subject. There also needs to be an attitude shift so that maths isn’t automatically seen as abstract and difficult to grasp, and people aren’t so quick to resign themselves to being bad at maths.
Raising the level of numeracy in the general population would go some way towards a more solid foundation that would decrease the gap between being the ordinary person on the street and the data professional.
So perhaps we are all data scientists. But do we have the confidence and direction to use those skills in a professional setting?