Determine Appropriate Lift Process

Surface Analysis Tools: Could evaluate surfaces and suggest suitable lift methods
Evidence Type Matching: Could pair lift techniques with the type of trace evidence
Workflow Guidance: Could assist in following best practices for lifting
Real-Time Adaptation: Could change lift process recommendations as new conditions are observed
Visual Guides: Could assist technicians during the lift process

Policies and Procedures: Develop protocols for AI-guided lift processes
Accountability Structures: Assign technicians to review AI lift suggestions
Training and Education: Educate staff on AI recommendations
Documentation Standards: Maintain logs of lift processes used
Compliance Checks: Regular audits for lift process adherence

Risk Identification:

Technical - Incorrect lift method
Operational - Over-reliance
Ethical - Potential data bias

Risk Sources: Limited training data for new surfaces
Criminal Justice Partner Analysis: Crime scene technicians, lab staff, supervisors
Risk Documentation: Logs of lift decisions and results

Performance Metrics: Efficiency and accuracy of lifted evidence
Assessment Tools: Compare AI-recommended methods with outcomes
Monitoring Techniques: Regular reviews of lift results
Feedback Loops: Collect technician feedback
Validation Processes: Expert reviews of lift processes

Mitigation Strategies: Train AI with diverse surface data
Incident Response Plan: Manual intervention if lifting fails
Adaptation and Continuous Improvement: Update algorithms based on field feedback