Nowadays, with the internet, smartphones, and social media, it is a clear sign that technology is now more personalized and tailored towards the individual rather than the masses. This new wave made nerds and technology cooler than ever. We keep creating more data, build faster machines, and connected services make us understand how powerful data could be.
We are living in an era where throwing around buzzwords like deep learning, chatbots, or big data seems like a pre-requisite for companies. Technology moves so fast and we don’t want to show that we can’t keep up. So we just accept things the way they are because we don’t know how to fight them. Or worse, we don’t even realize that we could even change them. We are fine with our social media presence being analyzed, our news being hand-picked, or our medical decisions being made for us.
Data-driven not only means that we are using data, but it means that we carefully generate it, that we monitor it, and that we understand its power and lack thereof. And nowadays, we are so incredibly far from this. We just have to look at the job market and see the lack of supply for data scientists. Even as companies pretend that their employees who make graphs using Excel are now data engineers, artificial intelligence experts, or smart solution architects, we are still facing an incredible shortage of qualified professionals. This is even worse in policy-making. Our laws must adapt to the new reality, but we have lawmakers who are for the most part, completely uneducated about the topic. And the news media does not help by spreading hoaxes and clear falsehoods about the power of artificial intelligence and data.
We have come a long way in understanding how we can teach our computers to learn new things, but we haven’t changed the way we teach our own people. We have seen the power of data in making intelligent decisions, but we still somehow use outdated electoral systems and indirect representation in politics. If we want to become truly data-driven in the future, we will have to fix these two things. The way we create intelligence and data, and the way we make use of it.