When — and Why — You Should Explain How Your AI Works

“With the amount of data today, we know there is no way we as human beings can process it all…The only technique we know that can harvest insight from the data, is artificial intelligence,” IBM CEO Arvind Krishna recently told the Wall Street Journal.

The insights to which Krishna is referring are patterns in the data that can help companies make predictions, whether that’s the likelihood of someone defaulting on a mortgage, the probability of developing diabetes within the next two years, or whether a job candidate is a good fit. More specifically, AI identifies mathematical patterns found in thousands of variables and the relations among those variables. These patterns can be so complex that they can defy human understanding.

This can create a problem: While we understand the variables we put into the AI (mortgage applications, medical histories, resumes) and understand the outputs (approved for the loan, has diabetes, worthy of an interview), we might…

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This article was written by Reid Blackman and originally published on hbr.org