Algorithms are only as good as their trainers, argues Alchemy One’s Joel Trethowan.
He makes a thoughtful case in Mumbrella:
In problem solving, you have two parts – the first part, where you break the problem down into its components to really see what’s going on, and the second part, where you put everything back together again. As Wernicke says: “The crucial thing is that data and data analysis is only good for the first part…It’s not suited to put those pieces back together again, and then to come to a conclusion.
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An algorithm is only as good as its trainer. While real-time insights and data point analysis are invaluable, human intelligence is necessary to determine which combination of points will drive the required outcomes.
As data scientist Cathy O’Neil said in her book Weapons of Math Destruction, “algorithms are just opinions embedded in code”. And without the right humans imparting those opinions, you can bet your algorithm won’t know what to think.
