Algorithmic disgorgement
An enforcement remedy, most notably used by the US Federal Trade Commission, requiring destruction of a model or algorithm derived from unlawfully collected data, treating the model as a fruit of the unlawful collection in the same way courts treat ill-gotten financial gains as subject to disgorgement.
Defined in 3 GAGE programs, which carry 9 distinct definitions of it. The wording above is taught in Certified AI Data Governance Professional (CADGP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
An enforcement remedy, most notably used by the US Federal Trade Commission, requiring destruction of a model or algorithm derived from unlawfully collected data, treating the model as a fruit of the unlawful collection in the same way courts treat ill-gotten financial gains as subject to disgorgement.
An enforcement remedy (used by the United States Federal Trade Commission) ordering deletion of a model and the data it was trained on. Named here to contrast the mandatory pile (a real legal consequence) with the voluntary pile (a certificate, which cannot prevent such a remedy). (see Topic 6.1)
A remedy, used by the US FTC, requiring a company to delete models and algorithms trained on improperly obtained data. Severe because it can destroy the core asset a business was built on.
A regulatory remedy, most notably used by the US FTC, requiring destruction not only of improperly obtained data but of any algorithm or model trained on it.
A regulatory remedy, most clearly demonstrated by the US Federal Trade Commission's 2021 order against Everalbum, Inc., requiring an organization to delete or destroy not only unlawfully collected data but also the models or algorithms built using that data.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- Purpose archaeology: what your data was collected FOR versus what it feeds now · Consent, Purpose, and the Law of Data, Certified AI Data Governance Professional (CADGP)
- Retention versus the model that memorized: deleting data a model already learned from · Consent, Purpose, and the Law of Data, Certified AI Data Governance Professional (CADGP)
- The deletion decision: the terabytes your organization should destroy this quarter, defended · The Money of Data, Certified AI Data Governance Professional (CADGP)
- The wrong data fed the model: the recall decision for an AI system in production · Data Incidents, Certified AI Data Governance Professional (CADGP)
- The deletion that was not: personal data found in a model trained last year · Data Incidents, Certified AI Data Governance Professional (CADGP)
- Machine unlearning: the emerging answer to deleting what a model learned · The Frontier Discipline, Certified AI Data Governance Professional (CADGP)
- The US mosaic: federal signals, state laws, and the agencies that already reach workplace AI · The World's Rulebooks, Certified AI Governance Professional (CAIGP)
- Standards versus law: what certification buys you and what it never will · The World's Rulebooks, Certified AI Governance Professional (CAIGP)
- Regulatory Compliance Navigator · Governance and Responsible AI, Certified AI Transformation Professional (CATP)
Where it shows up at work
A definition is where Algorithmic disgorgement starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Tracks executive orders, OMB guidance, agency rules and the state patchwork, and knows which state laws reach hiring, insurance and consumer decisions.
2 lessons on this page teach it as a primary outcome.
Classifies a system by role and risk tier, knows which obligations bind on which date after the Digital Omnibus, and what evidence conformity needs.
One lesson on this page teach it as a primary outcome.
Classifies AI incidents by severity, runs containment, preserves evidence, manages notification, and closes the loop with lessons learned.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Regulatory Counselneeds it at depth · 14 open postings this week
- AI Policy Analystneeds it at depth · 7 open postings this week
- Senior AI Compliance Analystneeds it at depth
- AI Compliance Managerneeds it at depth · 2 open postings this week
- AI Compliance Specialistneeds working knowledge · 1 open posting this week
- Chief Compliance Officer, AI compliance editionneeds working knowledge
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: OMB M-25-21 and M-25-22; Colorado SB 24-205; NYC Local Law 144; Regulation (EU) 2024/1689.
One interview question about it
A US company operates in several states. How do you track which state AI laws apply to which systems, and what changes when a new one passes?
Asked of candidates for us federal and state ai regulation. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Policy, legislative and government affairs staff carries it as a claim to back up: You follow federal and state developments already.
- A public policy, political science or international relations degree carries it as a claim to back up: US federal and state process is familiar; the AI statutes are new.
- A law degree (JD, LLB or LLM), no AI work yet carries it as a claim to back up: The EU AI Act reads like the statutes you were trained on; the content is new, the method is not.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.