Data Scientists Need To Get Better About Communicating Uncertainty And Risk In Their Results

Data is truth and algorithms uncover that single indisputable truth. Those two beliefs lie at the center of the data science revolution, yet they are absolutely wrong. Data merely constructs an artificial reality from which algorithms uncover one of many possible truths.

As the corporate and governmental decision-making process is increasingly data-driven, data scientists must learn how to better communicate risk and uncertainty in their findings. One of the greatest challenges data scientists face each day is that far from being able to feed indisputable data into unerring algorithms to define ultimate truth, they are frequently able only to feed piecemeal data of unknown accuracy and completeness through biased algorithms yielding answers that may be little better than random guesses.

Author: Kalev Leetaru

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