From
hbr
“Recent developments in AI are about lowering the cost of prediction. Better predictions matter when you make decisions in the face of uncertainty, as every business does, constantly. But how do you think through what it would take to incorporate a prediction machine into your decision-making process? In teaching this subject to MBA graduates at the University of Toronto’s Rotman School of Management, the authors have introduced a simple decision-making tool: the AI Canvas. Each space on the canvas contains one of the requirements for machine-assisted decision making, beginning with a prediction. To explain how the AI Canvas works, the authors use an example crafted during one of their AI strategy workshops: home security.”
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This HBR article by Ajay Agrawal, Joshua Gans, and Avi Goldfarb focuses on bringing AI into human-in-the-loop decision making. It acknowledges the need for actions, outcomes, and human judgment. It provides an example using a tool, the AI Canvas, to analyze where actions, outcomes, AI, human judgment, and other factors fit into a decision process.
There are a couple of enhancements that it appears this approach is missing:
1) A causal diagramming tool like a CDD that helps to map the path from actions to outcomes
2) A connection to systems thinking / systems modeling which forms the basis for understanding of causal mechanisms, especially nonlinear effects