The Good, the Bad, and the Ugly
Some predictive systems have helped governments improve inspections, anticipate service needs, target interventions, and allocate resources more effectively. Others have failed because of poor data, flawed assumptions, feedback loops, bias, or misplaced confidence in uncertain forecasts. Through real-world examples, participants will examine both successful and unsuccessful deployments of predictive AI and learn how to identify common warning signs, limitations, and unintended consequences before they become costly mistakes.
The Good, the Bad and the Ugly of Predictive…Coming UpPrediction Isn't Judgment: What Predictive AI Can—and Cannot—Do
Predictive systems are increasingly used to forecast risks, identify priorities, allocate resources, and support public-sector decision-making. But prediction is not the same as judgment. This session explores how predictive AI works, what different kinds of p…
The Good, the Bad and the Ugly of Predictive…Coming UpGoverning Prediction
What questions should public professionals ask before adopting a predictive system? How should agencies evaluate performance, monitor outcomes, and maintain accountability when predictive tools are used to inform decisions? This session examines practical appr…