Data practitioners: data scientists, analysts, researchers, data engineers, data ops engineers, machine learning engineers and artificial intelligence engineers, all dedicate considerable time and energy clarifying and purifying data in the belief that some system, be it human or artificial, will make better decisions with better data. There’s a belief, optimism, that accuracy and validity help to drive understanding, reason, and in general, better. It’s better to be accurate with fatter error bars, experience more discomfort with the ambiguity and make decisions that make things somewhat better than to feel extremely confident and making things a lot worse. Ground truth is difficult to chart, and it’s the bedrock upon which progress is built. It’s why we bother to try. In our[…]
