Читать книгу Decision Intelligence For Dummies - Pamela Baker - Страница 52

Data analytics, especially those powered by AI, are incredibly good at detecting patterns in data. They can not only find patterns in megasized data sets too large for human eyes to sort out but also find patterns in larger or smaller data sets that humans didn’t know to seek. It’s a little miraculous how well data analytics work, if you think about it.

Finding patterns is no small matter. According to global consultants, McKinsey & Company’s report, machine learning models have outperformed most medical professions in diagnosing and predicting the onset of disease. For example, machine learning has outperformed board certified dermatologists in identifying melanoma and has beaten oncologists at accurately predicting cancers using radiomics and other machine learning techniques. Numerous other reports from other industry analysts detail a spectacular array of lifesaving successes from machine pattern discoveries.

Couple such successes with the proven success of recent mRNA COVID-19 vaccines and you’re well on the way to significant breakthroughs for a variety of disease cures and vaccines. And a lot of the secret sauce is based on the patterns found in data. Nevertheless, I’m here to say that, though there’s plenty to cheer about, it’s also prudent to realize that it’s eminently possible that one identifies the patterns correctly and yet can still completely miss the big picture.

It’s time to take a look at how that happens in order to understand in later chapters how decision intelligence helps circumvent these and similar problems in the decision-making process.