Adaptive Risk Model for Inspected Small Passenger Vessels

Overview

Development stage

DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2021-01-01 (day precision)Source: 2021-01-01T00:00:00

Withheld from public reporting

Not reported

Mission

Topic area

Administrative Functions

Operational functions

Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

A lack of a comprehensive data-driven tool for informing marine inspection policy has left policymakers to make decisions based on qualitative and anecdotal information, resulting in less-than-optimal allocation of limited marine inspection resources.

Expected benefits

The Small Passenger Vessels Safety Task Force uses machine learning and expert input to build a flexible analysis tool that identifies the main causes of marine casualties and calculates a risk score for each vessel in the largest segment of the U.S.-inspected fleet. By using a logistic regression–based model with basic machine learning, this effort improves how inspectors are allocated, sharpens the focus on higher-risk vessels, and strengthens oversight to improve passenger safety.

System outputs

Numerical score that compares vessels predicted safety risk relative to each other.

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Developed in-houseSource: b) Developed in-house

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

No

Privacy Impact Assessment

Not reported

Authorization to Operate

No

Demographic features

Not reported

Training and evaluation data

Commercial vessel profiles including: engineering, life saving, propulsion, fire protection, manning, operating routes, plan review, and USCG inspection activity details.

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported