Entering Model Development for the predictive-maintenance initiative, Meridian's project manager works with the data science lead to define the model-development requirements before any modeling begins. Which of the following belongs in that requirements definition?
Select an answer to reveal the explanation.
Short Explanation
Model-development requirements are the model's job description before anyone writes code: what it's predicting, over what window, how wrong it's allowed to be, and whether a mechanic needs to understand why it flagged something.
Full Explanation
Defining AI model-development requirements means specifying, before modeling starts, exactly what the model needs to do and how it will be judged: the prediction target and horizon (predicting failure within a defined window, not just "predict failures" vaguely), acceptable accuracy and false-alarm tolerance (since over-alerting erodes mechanic trust while under-alerting risks safety), and interpretability needs — maintenance technicians and union-represented mechanics signing off on a flagged component likely need some explanation of why the model raised the flag, not just a black-box score. The laptop brand each data scientist uses is an IT-provisioning detail with zero bearing on what the model needs to accomplish. Press-release wording is a communications/marketing artifact, unrelated to defining technical model requirements. Selecting the production cloud region for the inference endpoint is an Operationalization/deployment decision that comes much later, after a model has been built and evaluated — bundling it into Model Development requirements confuses "what should this model do" with "where will it eventually run." Getting these requirements right up front is what lets the Phase IV Go/No-Go later be judged against criteria the team actually agreed on, rather than shifting goalposts.