AI hiring review starts with use-case inventory, jurisdiction scope, evidence ownership, and the distinction between system-generated records and customer-supplied artifacts.
Start with the employment decision
Do not begin with the model name. Begin with the decision the AI touches: recruiting, resume screening, candidate ranking, interview analysis, promotion, or other employment opportunity. That use case determines which obligations are worth reviewing.
Separate jurisdictions from policy preference
AI hiring obligations can depend on location, candidate population, employee population, and the role of the tool in the decision. Track New York City, Illinois, Colorado, and federal employment-law review separately instead of putting every rule into one generic policy row.
Use three evidence buckets
Tallin can supply system-generated inventory, usage, gateway, identity, and discovery records from configured sources. The customer supplies or attests documents outside Tallin, such as audits, notices, impact assessments, and counsel reviews. Required but missing evidence should remain an open gap. Your legal team determines which obligations apply; this checklist is not legal advice or a guarantee of compliance.
Key takeaways
- 01Name the employment decision before naming the AI model.
- 02Track jurisdictions explicitly rather than using a freeform policy note.
- 03Separate system-generated records from customer-attested evidence.
- 04Keep missing audits, notices, and sign-offs visible as open gaps.