Avoiding AI failure
A Gartner prediction in 2018 led to numerous articles stating that, “85% of AI and machine learning projects fail to deliver.” It’s hard to be certain of the original source of this statistic because some poetic license appears to have been taken in interpreting it. This, however, hasn’t stopped this statistic from being referenced often when discussing the relatively low success rates of AI projects.
85%?
The ironic misinterpretation may come from the line, “Gartner predicts that through 2022, 85 percent of AI projects will deliver erroneous outcomes due to bias in data, algorithms or the teams responsible for managing them” (https://www.gartner.com/en/newsroom/press-releases/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence).
Why has this statistic of questionable accuracy captured so much attention? As many I interviewed pointed out, failure is a normal part of the scientific...