Data science is capable of amazing predictions, but communicating the power of a great model can be tough. All the hard work, insight and importance can be lost on someone who just doesn’t think about these things on a regular basis. Not only can big accomplishments go under-appreciated, but people’s everyday alienation from data science can also make them question its validity.
For example, if I told you quantum electrodynamics can predict how electrically charged particles will interact and share photons with an accuracy of up to 0.0038 parts per million, a lot of people would say “so what? I don’t get it, and even if I did, it’s hard to believe it really works.”
That’s why it’s so critical to break down and communicate data science research in ways non-data scientists can appreciate. It isn’t that non-data-heads don’t care or aren’t smart. Of course they are. Rather, as data scientists it’s on us to connect the dots for them. We need to help them digest what’s being done and, most importantly, why it matters. This is hard, we know. It’s especially tough when empirical knowledge conflicts with people’s intuitive sense of how the world works (as it usually does). The science may be right, but if it doesn’t feel right, people can become disengaged.
That’s what we love about this video. While it wasn’t made (we’re guessing) explicitly with data science in mind, it’s a fantastic example of how a little empirical knowledge can lead to surprisingly accurate predictions. In a simple, elegant way, it connects the power of quantitative prediction with something anyone can really feel.