The risks of over-reliance on quantifiable data

Abstract

The rise of interest in artificial intelligence and machine learning has a flip side. It might not be so smart if we fail to design the methods correctly. A question out there — can we compress the reality into measurable numbers? Artificial Intelligence relies on what can be measured and quantified, risking an over-reliance on measurable knowledge.

The problem with many other technical problems is that it all ends with humans that design and assess according to their own perceived reality. The designers’ bias, perceived reality, weltanschauung, and outlook — everything goes into the design. The limitations are not on the machine side; the humans are far more limiting. Even if the machines learn from a point forward, it is still a human that stake out the starting point and the initial landscape.