Food AI Decision Engine (FAIDE)
Description
Prioritize limited regulatory resources and maximize public health protection.
Detailed example
Probability of being violative per the model's classifier, and whether that probability is above the model's recommended threshold (optimizing sensitivity and specificity).
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Reduced regulatory burden on establishments with a lower probability of being violative or causing public health harm; more efficient and effective regulatory oversight.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Internal FDA sample and inspection data, third-party purchased and open-source data.