Law / Frameworks / NIST Privacy Framework / Identify-P
NIST Privacy Framework, Identify-PID.RA-P3
Potential problematic data actions and associated problems are identified.NIST Privacy Framework, version 1.0, January 2020, ID.RA-P3
We read each law below as bearing on this control. That does not mean the control, done well, meets the law: what each law asks is on its own page. Law library as of .
- 5
- laws
- 5
- jurisdictions
- 1
- with court rulings behind it
- 1
- not yet in force
A law in force is unmarked; the rest wear their state: not yet in force
Comprehensive regime
3 laws, 3 jurisdictions| Jurisdiction | Law | What it asks, as read here |
|---|---|---|
| Loi n° 18-07 relative à la protection des personnes physiques dans le traitement des données à caractère personnel, modifiée et complétée par la loi n° 25-11 |
If you are the judicial authority, a body legally empowered to investigate offences, a judicial auxiliary or the prison administration processing personal data under Title V bis for the prevention or detection of offences, investigations, inquiries, criminal prosecutions or the execution of sentences, study the impact of a type of processing likely to create a high risk to a person's rights and freedoms before carrying it out. |
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| SB 21-190, Colorado Privacy Act (CPA) |
Offer consumers a way to opt out of targeted advertising, the sale of personal data, and profiling that produces legal or similarly significant effects, and complete a data protection assessment before processing that presents a heightened risk of harm. |
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| Québec | Act respecting the protection of personal information in the private sector, comprehensive regime |
Establish and implement governance policies and practices for personal information, including a framework for retention and destruction, and conduct a privacy impact assessment before acquiring, developing or overhauling a system or service that collects, uses, communicates, keeps or destroys personal information. |
AI sector rules
1 law, 1 jurisdiction| Jurisdiction | Law | What it asks, as read here |
|---|---|---|
| OSFI Guideline E-23, Model Risk Management (2027) from , in 6 months |
For models using advanced techniques such as AI/ML, model owners should consider the level of transparency and explainability required, the need for alternative controls, and the potential for biased outcomes, negative social and ethical implications or privacy risks. |
Enforcement supervision
1 law, 1 jurisdiction| Jurisdiction | Law | What it asks, as read here |
|---|---|---|
| FTC Act Section 5, Unfair or Deceptive Acts or Practices (privacy and data-security enforcement) |
Assess foreseeable privacy harms before deploying a system that collects or uses biometric identifiers derived from photographs, videos, or voice recordings, and disclose material facts about that collection. |
Full text of the NIST Privacy Framework, public domain (a US government work). Every control of the framework.