This is a big opportunity for clients to automate decisions. In the ’90s and ’00s, the industry wrapped software around business processes. Over the next two decades we’re going to wrap software around decisions, automating bets people are going to make. … I do think this idea that we’re automating capabilities that used to be gut-driven is going to be a fundamental transition for our enterprise clients. Making decisions based on data and spotting patterns that are invisible to human eye will be the way successful companies execute.
— Cloudera founder Mike Olson: ‘We’re moving from automating processes to automating decisions’
Expanding our enterprise system development from a focus on automating processes to add a focus on more efficiently making effective data driven decisions is a sea change in how we operate. This article is correct in recognizing the importance of this change.
However, what is missing in this discussion is a recognition that for complex consequential decisions most often we won’t fully automate those decisions. Rather we will build Human-AI hybrid systems, where the AI is providing support to the human decision maker. We are starting to see such systems appear for a wide variety of knowledge workers. Everyone from journalists to lawyers to Airbnb hosts to nuclear sub captains.
This type of hybrid decision making inherently requires the output of the AI models to be human interpretable. If the AI assistant is a black box than the human who is making the final decision won’t know how to integrate and leverage that assistance.