Course Description
This program examines the shift in U.S. immigration adjudications from traditional, point-in-time petition review to continuous, data-driven vetting across government systems. Agencies increasingly use artificial intelligence, machine learning, and cross-agency data integration to identify inconsistencies across filings, public records, and other data sources.
The panel will analyze how automated flagging systems influence adjudicator decision-making and trigger requests for evidence, audits, or enforcement actions. It will also address transparency concerns and due process limitations in AI-assisted adjudications.
Participants will gain practical strategies to prepare consistent, “AI-ready” filings, conduct pre-filing audits, and advise clients effectively in an era of continuous government scrutiny.
Syllabus
- Transition from discrete adjudication to continuous lifecycle vetting
- Government use of AI and data analytics in immigration screening
- Hybrid AI–human decision-making and adjudicatory bias effects
- Cross-agency data integration and inconsistency detection
- Triggers for RFEs, audits, and enforcement actions
- Transparency gaps and due process implications
- Preparing consistent, “AI-ready” filings
- Pre-filing audits and digital footprint alignment
- Ethical counseling under continuous monitoring conditions
- Strategic risk management for employers and stakeholders