DATA PRIVACY AND ETHICS ASSESSMENT
tasleemat asset PMO-02.06 template --lang en
Deliverable Summary & Governance Boundaries
Lifecycle Phase Alignment
Phase 02: Project Approach and Tailoring
Sizing Tier Requirements
Tier 1
Validation Contract
This deliverable conforms to a strict companion Draft 2020-12 JSON Schema for automated structural and semantic validation.
tasleemat validate PMO-02.06 ./completed_data.json
Template Markdown (Bilingual)
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LLM INSTRUCTIONS: Fill in the [ Add details... ] placeholders based on project context.
Section Instructions:
**1. Scope, Data Inventory and Ownership**
* **Assessment Scope:** The processing, systems, and periods this assessment covers, stated so that its edges are visible. An assessment that does not say what it excludes will be read as covering everything, and the gap between the two is where the untested processing lives.
* **Processing Out of Scope:** What is explicitly not covered, and why. Excluded because another assessment covers it, or excluded because it was not looked at, are very different statements and only the second one is a finding.
* **Data Owners and Custodians:** Who owns each data asset and who administers it day to day. Ownership and custody differ, and the accountability clause follows the custodian while the budget follows the owner.
* **Data Inventory:** One row per data asset: what it is, who owns it, the purpose it is held for, whether it holds personal data, whether that data is special category, and its volume and refresh rate. An inventory described as a count rather than as a list cannot answer any of the questions that follow.
* **Data Flow and Recipients:** Where the data moves, and who receives it. The flow is what determines which transfers need a mechanism, and a flow that shows only the primary store hides the copies.
**2. Lawful Basis and Purpose Limitation**
* **Processing Purposes and Necessity:** What each processing activity is for, and why it cannot be achieved with less data or a shorter reach. Necessity is assessed per purpose rather than per dataset, because one dataset frequently serves several purposes with very different necessity.
* **Lawful Basis by Purpose:** One row per purpose: the data processed, the basis relied on, the basis for special category data where any is present, and the justification. A form that records a basis once for a dataset will carry one basis across purposes that do not share it.
* **Purpose Compatibility and Secondary Use:** Whether the data is used for any purpose other than the one collected for, and on what basis. Secondary use is the most common privacy failure in analytics work and the one least likely to be noticed, because every individual field still has a lawful origin.
* **Automated Decision-Making:** Any decision made about a person with no meaningful human involvement, the logic involved, and the consequences for them. Recorded because the assessment of a legal basis does not by itself establish that a decision is one a person could contest.
**3. Consent and Transparency**
* **Consent Mechanism:** How consent is requested, and where in the flow it appears. Consent collected after the data is already in use is a record, not a request, and the difference determines what the record is worth.
* **Consent Specificity and Granularity:** What the person was told they were consenting to, and whether the choices are separate. A single consent covering several purposes is consent to none of them in particular, and a bundle of pre-ticked boxes is not a choice.
* **Consent Recording and Evidence:** Where each consent is stored, with the timestamp, the version of the text shown, and the interface shown. A consent record without the version of the text cannot be defended later, because the terms the person agreed to are then unrecoverable.
* **Withdrawal:** How a person withdraws, how much easier it is than granting, and what happens to data already processed on that basis. Asymmetry between granting and withdrawing is the standard test, and a withdrawal that is honoured prospectively only leaves the processing intact behind it.
* **Privacy Notices and Just-in-Time Disclosure:** What is told at collection, what is told at the point the data is used, and where either may be found. A notice published once and never revisited informs nobody who meets the processing for the first time in month three.
**4. Individual Rights**
* **Rights Handling Process:** How a request is received, routed, decided and answered, and by whom. A right stated in a policy with no route to exercise it is a stated right, and it is tested only when someone uses it.
* **Identity Verification:** How the requester is confirmed to be who they claim, and what is refused when that cannot be done. Verification that accepts anyone discloses data; verification that refuses everyone denies the right, and the balance is a decision to record rather than a default.
* **Response Timeframes and Escalation:** The deadline for each type of request, what happens when it is missed, and who is told. The clock is the whole of the right in practice, because a correct answer delivered late is still a breach.
* **Rights Over Derived, Shared and Retired Data:** What happens to a request where the data has been aggregated, shared with a third party, or placed in a model. Deletion cannot reach a trained model by deleting a row, and the form that does not say so will be read as having deleted it.
**5. Retention, Security and Sharing**
* **Retention Schedule:** One row per data asset: the retention period, the basis for that period rather than the convention, what triggers deletion, and how deletion is verified. A period adopted as a default and recorded as a decision is the most common entry, and it is the reason data outlives every justification that justified it.
* **Deletion Mechanism and Coverage:** How deletion is carried out, across primary stores, replicas, logs, exports and derived copies. Deleting a row from one table while the data persists in five other places is the most frequent finding in any such assessment, and it is invisible without a coverage statement.
* **Backups and Derived Data:** How deletion propagates to backups and to models trained on the data, and over what period. Backups are the usual reason a deletion is incomplete, and a trained model is a copy no deletion request reaches.
* **Access Controls and Least Privilege:** Who can reach the data, by what route, under what approval, and how access is reviewed. Access is the control that fails quietly, since misuse of legitimate credentials is indistinguishable from legitimate use without a review.
* **Encryption and Key Management:** What is encrypted in transit and at rest, and who holds the keys. Encryption whose keys sit beside the data is a control on paper, and the key custody arrangement is the part that is not written down.
* **Third-Party Sharing:** One row per recipient: the recipient, the purpose, the data shared, the contractual safeguard relied on, and the region processed in. Each row needs its own basis, because a processor bound by contract to a controller is not the same arrangement as a controller sharing on its own purpose.
* **Cross-Border Transfers:** Where data or processing leaves the jurisdiction, under which transfer mechanism, and what supplementary measures apply. A hosting region is not a transfer analysis, and remote access by a foreign staff member is a transfer that no region setting records.
* **Breach Notification:** What constitutes a breach here, who is notified, within what time, and who decides. Recorded because a response plan written after an incident is always written for that incident, and the decision threshold is the part that is usually left out.
**6. Ethics Beyond Compliance**
* **Harm Beyond Legal Exposure:** Where this processing causes harm that no law prohibits. This section exists because compliance is a floor: processing can be lawful, consented, retained properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question it was easy to answer.
* **Vulnerable Individuals and Groups:** Who is affected in a state of reduced ability to refuse, to understand, or to bear the consequence. Vulnerability here is a property of the situation rather than of the person, and it is invisible to a record of categories and volumes.
* **Transparency to Affected People:** What the people in the data are actually told, in language they use, as distinct from what the notice says. A notice that is accurate, complete and unread is the standard failure, and reading it as a recipient rather than as a drafter is the only way to see it.
* **Manipulation, Dark Patterns and Consent Fatigue:** Whether the interface nudges, pre-ticks, buries refusal, or asks repeatedly, and whether the volume of requests is such that a refusal is impractical. Consent obtained by a design choice is not freely given, whatever the record says.
* **Fairness of Automated Decisions:** Whether the processing produces outcomes for people, and what the distribution of those outcomes is across groups. A lawful basis for a decision is not a defence of its fairness, and the two are assessed against different questions.
**7. Findings, Remediation and Review**
* **Findings Register:** One row per finding: the finding, the risk it poses to individuals, the severity, the owner, and the action being taken. Severity is what determines the order of work, and a register with no severity column is a list of observations.
* **Residual Risk and Acceptance:** The risk remaining after the planned actions, who accepts it, and until when. Acceptance is a decision with an owner and an expiry date; an acceptance with neither is an unowned risk that will be rediscovered at the next assessment.
* **Remediation Plan:** The actions, their owners and their dates, and what is being done in the interim. The interim period is where a known finding actually operates, so it is the part of the plan most worth writing down.
* **Review Triggers:** What would cause this assessment to be revisited before its scheduled date, such as a new purpose, a new recipient, a new model, or a regulatory change. Triggers stated after the change have occurred are a record of the change.
* **Reassessment Triggers:** When this assessment expires and on what cycle. An assessment with no expiry is treated as permanent by everyone who did not write it, including the people who inherited it.
-->
<h3 dir="ltr" align="right">{{Company_Name}}</h3>
<h2 dir="ltr" align="right">{{System_or_Initiative_Name}} - {{Assessment_ID}}</h2>
<h1 dir="ltr" align="center">DATA PRIVACY AND ETHICS ASSESSMENT</h1>
| **Date Prepared:** {{Current_Date}} | **Data Privacy Officer:** {{Data_Privacy_Officer_Name}} | **Prepared By:** {{Prepared_By}} |
| :--- | :--- | :--- |
---
## 1. Scope, Data Inventory and Ownership
<!-- What this assessment covers, what it does not, who owns and administers the data, what assets exist, and where the data moves. -->
**Assessment Scope:** [ Add details... ]
**Processing Out of Scope:** [ Add details... ]
**Data Owners and Custodians:** [ Add details... ]
**Data Inventory:**
| Data Asset | Owner | Stated Purpose | Personal Data | Special Category | Volume and Refresh |
| :--- | :--- | :--- | :--- | :--- | :--- |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
**Data Flow and Recipients:** [ Add details... ]
---
## 2. Lawful Basis and Purpose Limitation
<!-- What each processing is for and why it needs the data it uses, the basis relied on per purpose, any use beyond the original purpose, and any decision made about a person automatically. -->
**Processing Purposes and Necessity:** [ Add details... ]
**Lawful Basis by Purpose:**
| Purpose | Data Processed | Lawful Basis | Special Category Basis | Justification |
| :--- | :--- | :--- | :--- | :--- |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
**Purpose Compatibility and Secondary Use:** [ Add details... ]
**Automated Decision-Making:** [ Add details... ]
---
## 3. Consent and Transparency
<!-- How consent is requested, what it covers, how it is evidenced, how it is withdrawn, and what the people in the data are told. -->
**Consent Mechanism:** [ Add details... ]
**Consent Specificity and Granularity:** [ Add details... ]
**Consent Recording and Evidence:** [ Add details... ]
**Withdrawal:** [ Add details... ]
**Privacy Notices and Just-in-Time Disclosure:** [ Add details... ]
---
## 4. Individual Rights
<!-- How a request for an individual's data is received, decided and answered in time, and what happens where the data has been derived, shared or used to build a model. -->
**Rights Handling Process:** [ Add details... ]
**Identity Verification:** [ Add details... ]
**Response Timeframes and Escalation:** [ Add details... ]
**Rights Over Derived, Shared and Retired Data:** [ Add details... ]
---
## 5. Retention, Security and Sharing
<!-- How long each asset is kept and on what basis, how deletion reaches every copy, who can reach the data, who else receives it, where it crosses a border, and what happens on a breach. -->
**Retention Schedule:**
| Data Asset | Retention Period | Basis for Period | Deletion Trigger | Deletion Verified |
| :--- | :--- | :--- | :--- | :--- |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
**Deletion Mechanism and Coverage:** [ Add details... ]
**Backups and Derived Data:** [ Add details... ]
**Access Controls and Least Privilege:** [ Add details... ]
**Encryption and Key Management:** [ Add details... ]
**Third-Party Sharing:**
| Recipient | Purpose | Data Shared | Contractual Safeguard | Region |
| :--- | :--- | :--- | :--- | :--- |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
**Cross-Border Transfers:** [ Add details... ]
**Breach Notification:** [ Add details... ]
---
## 6. Ethics Beyond Compliance
<!-- Where this processing causes harm that no law prohibits, who is affected while unable to refuse, what people are actually told, whether the interface permits a real choice, and how automated outcomes fall across groups. -->
**Harm Beyond Legal Exposure:** [ Add details... ]
**Vulnerable Individuals and Groups:** [ Add details... ]
**Transparency to Affected People:** [ Add details... ]
**Manipulation, Dark Patterns and Consent Fatigue:** [ Add details... ]
**Fairness of Automated Decisions:** [ Add details... ]
---
## 7. Findings, Remediation and Review
<!-- What was found, the risk remaining after the planned actions, what happens in the meantime, and what would cause this assessment to be reopened. -->
**Findings Register:**
| Finding | Risk to Individuals | Severity | Owner | Action |
| :--- | :--- | :---: | :--- | :--- |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
| [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] | [ Add details... ] |
**Residual Risk and Acceptance:** [ Add details... ]
**Remediation Plan:** [ Add details... ]
**Review Triggers:** [ Add details... ]
**Reassessment Triggers:** [ Add details... ]
---
### Sign-off and Approvals
| Role | Name | Signature | Date |
| :--- | :--- | :---: | :---: |
| **Data Protection Officer (DPO)** | {{DPO_Name}} | _______________________ | [ .... - .... - .... ] |
| **Legal / Compliance Counsel** | {{Legal_Counsel_Name}} | _______________________ | [ .... - .... - .... ] |
| **Project Manager** | {{Project_Manager_Name}} | _______________________ | [ .... - .... - .... ] |
---
<div dir="ltr" align="right" style="margin-top: 20px; font-size: 12px; color: #7f8c8d;">
<span>Electronic Audit Trail: Hash SHA256: {{Audit_Trail_SHA256_Hash}}</span> <br>
<strong>Template:</strong> DATA PRIVACY AND ETHICS ASSESSMENT | <strong>Ref:</strong> PMO-02.06 <br>
<i>Generated on: {{Current_Timestamp}}, by <a href="https://github.com/fakhruldeen/Tasleemat/" style="color: #7f8c8d;">Tasleemat</a></i>
</div>
User Guide & Practitioner Instructions
Tasleemat Forms Guide
Project Artifact: Data Privacy and Ethics Assessment
Document Reference: PMO-02.06
This document provides a comprehensive, professional reference to understand the purpose and effective usage of the Data Privacy and Ethics Assessment in alignment with the Tasleemat framework.
1. What?
A record of the personal data a piece of work will process: what is in scope and what is explicitly out, who owns and who administers each data asset, what each one is held for and whether it holds special category data, where the data moves, the lawful basis relied on for each purpose rather than for each dataset, any use beyond the original purpose, any decision made about a person without meaningful human involvement, how consent is requested and evidenced and withdrawn, how an individual's request is answered in time, what happens to data that has been derived or trained into a model, how long each asset is kept and on what basis, how deletion reaches replicas, logs, exports and models, who can reach the data and who holds the keys, who else receives it and under which mechanism, what constitutes a breach here, where the processing causes harm that no law prohibits, who is affected while unable to refuse, what the people in the data are actually told, whether the interface permits a real choice, how automated outcomes fall across groups, and what was found, what risk remains, and what would reopen the assessment.
2. Why?
Because the harm this work can do is invisible from inside it. A team can see the schema and the throughput and the cost per request, and none of those show what happens to the person whose record is in the table. So the questions get answered from assumption, the assumptions differ between the engineer and the reviewer, and the first person to find out is the individual who asks for their data and is told the request is being looked into.
The fields that appear empty are the evidence. An assessment with no stated exclusions, no secondary use, no deletion-coverage statement, no withdrawal route and no ethics findings describes processing that has not started, since each of those is filled in by something that happened rather than by something that was decided. A consent record without the version of the text shown cannot be defended later, because the terms the person agreed to are then unrecoverable; a retention period recorded without its basis is a default adopted and written down as a decision; and deleting a row from the primary store while the data persists in four other places is the most frequent finding in any such review, and it is invisible without a coverage statement.
The section on harm beyond legal exposure exists because compliance is a floor rather than a ceiling. Processing can be lawful, consented, retained properly, secured properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question that was easy to answer. The people who read the completed form will believe the work is finished.
3. When?
This artifact is primarily prepared, utilized, and updated during the PROJECT APPROACH AND TAILORING Process Group of the project lifecycle. It is drafted when a processing purpose is proposed, baselined before any personal data is collected, and revised on every change of purpose, recipient, model, or jurisdiction, and on any regulatory change, since each of those alters what the assessment should say. It is read at design review, at procurement, when a new dataset is proposed, when an individual exercises a right, and at the incident review.
4. Who?
Responsibilities: Prepared by the Data Protection Officer, who is accountable for the lawful basis, the retention schedule and the rights handling process, and who is the person who must be able to answer a request from an individual without consulting anyone. Reviewed by the Ethics Review Lead, who is accountable for the section on harm beyond legal exposure and for the fairness of automated outcomes, and by the data owner for each asset, who is accountable for the stated purpose being the real one. Approved by the Project Sponsor, who is accountable for accepting the residual risk. Where processing was not looked at, record that it was not looked at, rather than leaving the field blank, since an exclusion and an omission are different findings.
Tailoring Tips
- An assessment for processing with no personal data may be short, but the scope section must still state what would bring the work into scope, since that is the boundary that is later tested.
- Where one dataset serves several purposes, the lawful-basis table gains a row per purpose rather than gaining columns, since a form that records a basis once will carry it across purposes that do not share it.
- Retention periods may be inherited from a group standard, provided the row records that the period was inherited and on what basis, which is a different statement from having chosen it.
- Where a model is trained on the data, the derived-data row should name the model and the training date, because a deletion request after that date cannot be answered by deleting a row.
- It is worth recording which findings were accepted rather than fixed, with the name of the person who accepted them and the date the acceptance expires, since an acceptance with neither is an unowned risk.
- Where the ethics section produces nothing, record that it was considered and what was considered, since an empty section is read as an omission rather than as a conclusion.
- Superseded assessments should be retained rather than overwritten, since the question a complaint generates is almost always about what was in force at the time.
Alignment & Dependencies
1. Pre-requisites & Inputs (Upstream Dependencies)
- Mandatory:
- AI Use Case Canvas (PMO-02.04) or Scope Statement (PMO-04.02.05)
- Data Flow & System Architecture
- Optional / Contextual:
- Regulatory Privacy Requirements (GDPR / Data Protection Acts)
2. Downstream Dependents
- Mandatory:
- AI Governance Plan (PMO-02.02)
- Risk Register (PMO-04.08.02)
- Requirements Documentation (PMO-04.02.03)
- Optional / Contextual:
- Statement of Work / SOW (PMO-04.09.04)
- Quality Audit (PMO-05.05)
5. How?
To accurately and professionally complete the DATA PRIVACY AND ETHICS ASSESSMENT, the
responsible party must populate the following sections based on the project
context (ensure parameters.md is referenced for global project variables):
- Assessment Scope: The processing, systems, and periods this assessment covers, stated so that its edges are visible. An assessment that does not say what it excludes will be read as covering everything, and the gap between the two is where the untested processing lives.
- Processing Out of Scope: What is explicitly not covered, and why. Excluded because another assessment covers it, or excluded because it was not looked at, are very different statements and only the second one is a finding.
- Data Owners and Custodians: Who owns each data asset and who administers it day to day. Ownership and custody differ, and the accountability clause follows the custodian while the budget follows the owner.
- Data Inventory: One row per data asset: what it is, who owns it, the purpose it is held for, whether it holds personal data, whether that data is special category, and its volume and refresh rate. An inventory described as a count rather than as a list cannot answer any of the questions that follow.
- Data Flow and Recipients: Where the data moves, and who receives it. The flow is what determines which transfers need a mechanism, and a flow that shows only the primary store hides the copies.
- Processing Purposes and Necessity: What each processing activity is for, and why it cannot be achieved with less data or a shorter reach. Necessity is assessed per purpose rather than per dataset, because one dataset frequently serves several purposes with very different necessity.
- Lawful Basis by Purpose: One row per purpose: the data processed, the basis relied on, the basis for special category data where any is present, and the justification. A form that records a basis once for a dataset will carry one basis across purposes that do not share it.
- Purpose Compatibility and Secondary Use: Whether the data is used for any purpose other than the one collected for, and on what basis. Secondary use is the most common privacy failure in analytics work and the one least likely to be noticed, because every individual field still has a lawful origin.
- Automated Decision-Making: Any decision made about a person with no meaningful human involvement, the logic involved, and the consequences for them. Recorded because the assessment of a legal basis does not by itself establish that a decision is one a person could contest.
- Consent Mechanism: How consent is requested, and where in the flow it appears. Consent collected after the data is already in use is a record, not a request, and the difference determines what the record is worth.
- Consent Specificity and Granularity: What the person was told they were consenting to, and whether the choices are separate. A single consent covering several purposes is consent to none of them in particular, and a bundle of pre-ticked boxes is not a choice.
- Consent Recording and Evidence: Where each consent is stored, with the timestamp, the version of the text shown, and the interface shown. A consent record without the version of the text cannot be defended later, because the terms the person agreed to are then unrecoverable.
- Withdrawal: How a person withdraws, how much easier it is than granting, and what happens to data already processed on that basis. Asymmetry between granting and withdrawing is the standard test, and a withdrawal that is honoured prospectively only leaves the processing intact behind it.
- Privacy Notices and Just-in-Time Disclosure: What is told at collection, what is told at the point the data is used, and where either may be found. A notice published once and never revisited informs nobody who meets the processing for the first time in month three.
- Rights Handling Process: How a request is received, routed, decided and answered, and by whom. A right stated in a policy with no route to exercise it is a stated right, and it is tested only when someone uses it.
- Identity Verification: How the requester is confirmed to be who they claim, and what is refused when that cannot be done. Verification that accepts anyone discloses data; verification that refuses everyone denies the right, and the balance is a decision to record rather than a default.
- Response Timeframes and Escalation: The deadline for each type of request, what happens when it is missed, and who is told. The clock is the whole of the right in practice, because a correct answer delivered late is still a breach.
- Rights Over Derived, Shared and Retired Data: What happens to a request where the data has been aggregated, shared with a third party, or placed in a model. Deletion cannot reach a trained model by deleting a row, and the form that does not say so will be read as having deleted it.
- Retention Schedule: One row per data asset: the retention period, the basis for that period rather than the convention, what triggers deletion, and how deletion is verified. A period adopted as a default and recorded as a decision is the most common entry, and it is the reason data outlives every justification that justified it.
- Deletion Mechanism and Coverage: How deletion is carried out, across primary stores, replicas, logs, exports and derived copies. Deleting a row from one table while the data persists in five other places is the most frequent finding in any such assessment, and it is invisible without a coverage statement.
- Backups and Derived Data: How deletion propagates to backups and to models trained on the data, and over what period. Backups are the usual reason a deletion is incomplete, and a trained model is a copy no deletion request reaches.
- Access Controls and Least Privilege: Who can reach the data, by what route, under what approval, and how access is reviewed. Access is the control that fails quietly, since misuse of legitimate credentials is indistinguishable from legitimate use without a review.
- Encryption and Key Management: What is encrypted in transit and at rest, and who holds the keys. Encryption whose keys sit beside the data is a control on paper, and the key custody arrangement is the part that is not written down.
- Third-Party Sharing: One row per recipient: the recipient, the purpose, the data shared, the contractual safeguard relied on, and the region processed in. Each row needs its own basis, because a processor bound by contract to a controller is not the same arrangement as a controller sharing on its own purpose.
- Cross-Border Transfers: Where data or processing leaves the jurisdiction, under which transfer mechanism, and what supplementary measures apply. A hosting region is not a transfer analysis, and remote access by a foreign staff member is a transfer that no region setting records.
- Breach Notification: What constitutes a breach here, who is notified, within what time, and who decides. Recorded because a response plan written after an incident is always written for that incident, and the decision threshold is the part that is usually left out.
- Harm Beyond Legal Exposure: Where this processing causes harm that no law prohibits. This section exists because compliance is a floor: processing can be lawful, consented, retained properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question it was easy to answer.
- Vulnerable Individuals and Groups: Who is affected in a state of reduced ability to refuse, to understand, or to bear the consequence. Vulnerability here is a property of the situation rather than of the person, and it is invisible to a record of categories and volumes.
- Transparency to Affected People: What the people in the data are actually told, in language they use, as distinct from what the notice says. A notice that is accurate, complete and unread is the standard failure, and reading it as a recipient rather than as a drafter is the only way to see it.
- Manipulation, Dark Patterns and Consent Fatigue: Whether the interface nudges, pre-ticks, buries refusal, or asks repeatedly, and whether the volume of requests is such that a refusal is impractical. Consent obtained by a design choice is not freely given, whatever the record says.
- Fairness of Automated Decisions: Whether the processing produces outcomes for people, and what the distribution of those outcomes is across groups. A lawful basis for a decision is not a defence of its fairness, and the two are assessed against different questions.
- Findings Register: One row per finding: the finding, the risk it poses to individuals, the severity, the owner, and the action being taken. Severity is what determines the order of work, and a register with no severity column is a list of observations.
- Residual Risk and Acceptance: The risk remaining after the planned actions, who accepts it, and until when. Acceptance is a decision with an owner and an expiry date; an acceptance with neither is an unowned risk that will be rediscovered at the next assessment.
- Remediation Plan: The actions, their owners and their dates, and what is being done in the interim. The interim period is where a known finding actually operates, so it is the part of the plan most worth writing down.
- Review Triggers: What would cause this assessment to be revisited before its scheduled date, such as a new purpose, a new recipient, a new model, or a regulatory change. Triggers stated after the change have occurred are a record of the change.
- Reassessment Triggers: When this assessment expires and on what cycle. An assessment with no expiry is treated as permanent by everyone who did not write it, including the people who inherited it.
📥 Associated Templates
- 📄 Printable Template (Markdown)
- 🤖 LLM Generation Prompt
- 📊 Data Structure (JSON)
- 📈 Tabular Data (CSV)
6. Reference Example
A fully completed, gold-standard reference example illustrating this artifact in practice is available:
📖 Completed Example: 02_06_Data_Privacy_and_Ethics_Assessment_Example.md
LLM Generation Prompt & Agent Instructions
DATA PRIVACY AND ETHICS ASSESSMENT - LLM GENERATION GUIDE
System Prompt / Instructions: This document serves as the detailed instruction set for generating the
DATA PRIVACY AND ETHICS ASSESSMENT. When asked to populate this form, use the guidance provided for each section below to accurately generate the required content. Referenceparameters.mdfor global project variables.Context & Definition: A privacy assessment is written by people who are about to do something to a person they will never meet, and it is the only document that forces that asymmetry into the open. Everything else about the work is legible to the team doing it: the schema, the throughput, the cost per request. What is not legible is what happens to the person whose record is in the table, and that is the whole subject of this form. The team that fills it in is not the team that answers for it, which is why the form is a record rather than a feeling.
The seven sections follow the order the questions arrive. Scope and inventory record what is covered and, more importantly, what is not, because an assessment that does not state its exclusions will be read as covering everything and the untested processing lives in that gap. The inventory is a list rather than a count, and it separates the owner from the custodian, since accountability follows the custodian and the budget follows the owner. Lawful basis is recorded per purpose rather than per dataset, because one dataset commonly serves several purposes with very different necessity, and necessity is the question that actually gets asked. Secondary use is called out separately: it is the most common failure in analytics work and the least likely to be noticed, because every individual field still has a lawful origin. Consent records the version of the text that was shown, because a consent record without it cannot be defended later, and withdrawal records whether honouring it is as easy as granting it, since that asymmetry is the standard test. Individual rights records what happens to data that has been aggregated, shared, or trained into a model, and the answer is not that it was deleted, because deleting a row does not unlearn a model. Retention records the basis for each period rather than a default, and deletion records its coverage, because a deletion applied to the primary store while the data persists in replicas, logs, exports and model weights is the most frequent finding in any such assessment. Security records who holds the keys, not only what is encrypted. Sharing gives each recipient its own row and its own basis, because a processor bound by contract is not the same arrangement as a controller sharing on its own purpose, and cross-border transfer is not a hosting region, since remote access by foreign staff is a transfer that no region setting records.
The seventh section is where this form differs from the others in this group. The sixth asks what harm the processing causes that no law prohibits, and it exists because compliance is a floor rather than a ceiling: processing can be lawful, consented, retained properly, secured properly and shared properly, and still be wrong. A form that stops at lawful has answered the question that was easy to answer, and the people who read it will believe the work is finished. Vulnerable individuals, transparency as the recipient reads it rather than the drafter, dark patterns and consent fatigue, and the fairness of automated outcomes are all findings a category-and-volume record cannot produce. The last section records what was found, the risk remaining after the planned actions and who accepts it until when, what happens in the interim because that is where a known finding actually operates, and what would reopen the assessment, since triggers stated after the change are a record of the change rather than a control against it.
The value of the form is in the fields that are inconvenient. An assessment with no exclusions, no secondary use, no deletion-coverage statement, no withdrawal route and no ethics findings describes processing that has not started, because each of those is filled in by something that happened rather than by something that was decided. So the fields to insist on are the ones with no good answer available: where deletion does not reach, what happens to a person whose data is in a trained model, who can refuse and who cannot, and what harm remains after compliance is satisfied. Where a value genuinely is not known, record that it is not known and who must resolve it, which is more useful than a plausible answer, because a plausible answer will be relied on and a declared gap will be closed.
Alignment & Dependencies: * Pre-requisites (Inputs): * Mandatory: AI Use Case Canvas (PMO-02.04) or Scope Statement (PMO-04.02.05), Data Flow & System Architecture * Optional: Regulatory Privacy Requirements (GDPR / Data Protection Acts) * Downstream Dependents: * Mandatory: AI Governance Plan (PMO-02.02), Risk Register (PMO-04.08.02), Requirements Documentation (PMO-04.02.03) * Optional: Statement of Work / SOW (PMO-04.09.04), Quality Audit (PMO-05.05)
Scope, Data Inventory and Ownership
Assessment Scope
Instruction: The processing, systems, and periods this assessment covers, stated so that its edges are visible. An assessment that does not say what it excludes will be read as covering everything, and the gap between the two is where the untested processing lives.
Generated value: [ Add details... ]
Processing Out of Scope
Instruction: What is explicitly not covered, and why. Excluded because another assessment covers it, or excluded because it was not looked at, are very different statements and only the second one is a finding.
Generated value: [ Add details... ]
Data Owners and Custodians
Instruction: Who owns each data asset and who administers it day to day. Ownership and custody differ, and the accountability clause follows the custodian while the budget follows the owner.
Generated value: [ Add details... ]
Data Inventory
Instruction: One row per data asset: what it is, who owns it, the purpose it is held for, whether it holds personal data, whether that data is special category, and its volume and refresh rate. An inventory described as a count rather than as a list cannot answer any of the questions that follow.
Generated value: [ Add details... ]
Data Flow and Recipients
Instruction: Where the data moves, and who receives it. The flow is what determines which transfers need a mechanism, and a flow that shows only the primary store hides the copies.
Generated value: [ Add details... ]
Lawful Basis and Purpose Limitation
Processing Purposes and Necessity
Instruction: What each processing activity is for, and why it cannot be achieved with less data or a shorter reach. Necessity is assessed per purpose rather than per dataset, because one dataset frequently serves several purposes with very different necessity.
Generated value: [ Add details... ]
Lawful Basis by Purpose
Instruction: One row per purpose: the data processed, the basis relied on, the basis for special category data where any is present, and the justification. A form that records a basis once for a dataset will carry one basis across purposes that do not share it.
Generated value: [ Add details... ]
Purpose Compatibility and Secondary Use
Instruction: Whether the data is used for any purpose other than the one collected for, and on what basis. Secondary use is the most common privacy failure in analytics work and the one least likely to be noticed, because every individual field still has a lawful origin.
Generated value: [ Add details... ]
Automated Decision-Making
Instruction: Any decision made about a person with no meaningful human involvement, the logic involved, and the consequences for them. Recorded because the assessment of a legal basis does not by itself establish that a decision is one a person could contest.
Generated value: [ Add details... ]
Consent and Transparency
Consent Mechanism
Instruction: How consent is requested, and where in the flow it appears. Consent collected after the data is already in use is a record, not a request, and the difference determines what the record is worth.
Generated value: [ Add details... ]
Consent Specificity and Granularity
Instruction: What the person was told they were consenting to, and whether the choices are separate. A single consent covering several purposes is consent to none of them in particular, and a bundle of pre-ticked boxes is not a choice.
Generated value: [ Add details... ]
Consent Recording and Evidence
Instruction: Where each consent is stored, with the timestamp, the version of the text shown, and the interface shown. A consent record without the version of the text cannot be defended later, because the terms the person agreed to are then unrecoverable.
Generated value: [ Add details... ]
Withdrawal
Instruction: How a person withdraws, how much easier it is than granting, and what happens to data already processed on that basis. Asymmetry between granting and withdrawing is the standard test, and a withdrawal that is honoured prospectively only leaves the processing intact behind it.
Generated value: [ Add details... ]
Privacy Notices and Just-in-Time Disclosure
Instruction: What is told at collection, what is told at the point the data is used, and where either may be found. A notice published once and never revisited informs nobody who meets the processing for the first time in month three.
Generated value: [ Add details... ]
Individual Rights
Rights Handling Process
Instruction: How a request is received, routed, decided and answered, and by whom. A right stated in a policy with no route to exercise it is a stated right, and it is tested only when someone uses it.
Generated value: [ Add details... ]
Identity Verification
Instruction: How the requester is confirmed to be who they claim, and what is refused when that cannot be done. Verification that accepts anyone discloses data; verification that refuses everyone denies the right, and the balance is a decision to record rather than a default.
Generated value: [ Add details... ]
Response Timeframes and Escalation
Instruction: The deadline for each type of request, what happens when it is missed, and who is told. The clock is the whole of the right in practice, because a correct answer delivered late is still a breach.
Generated value: [ Add details... ]
Rights Over Derived, Shared and Retired Data
Instruction: What happens to a request where the data has been aggregated, shared with a third party, or placed in a model. Deletion cannot reach a trained model by deleting a row, and the form that does not say so will be read as having deleted it.
Generated value: [ Add details... ]
Retention, Security and Sharing
Retention Schedule
Instruction: One row per data asset: the retention period, the basis for that period rather than the convention, what triggers deletion, and how deletion is verified. A period adopted as a default and recorded as a decision is the most common entry, and it is the reason data outlives every justification that justified it.
Generated value: [ Add details... ]
Deletion Mechanism and Coverage
Instruction: How deletion is carried out, across primary stores, replicas, logs, exports and derived copies. Deleting a row from one table while the data persists in five other places is the most frequent finding in any such assessment, and it is invisible without a coverage statement.
Generated value: [ Add details... ]
Backups and Derived Data
Instruction: How deletion propagates to backups and to models trained on the data, and over what period. Backups are the usual reason a deletion is incomplete, and a trained model is a copy no deletion request reaches.
Generated value: [ Add details... ]
Access Controls and Least Privilege
Instruction: Who can reach the data, by what route, under what approval, and how access is reviewed. Access is the control that fails quietly, since misuse of legitimate credentials is indistinguishable from legitimate use without a review.
Generated value: [ Add details... ]
Encryption and Key Management
Instruction: What is encrypted in transit and at rest, and who holds the keys. Encryption whose keys sit beside the data is a control on paper, and the key custody arrangement is the part that is not written down.
Generated value: [ Add details... ]
Third-Party Sharing
Instruction: One row per recipient: the recipient, the purpose, the data shared, the contractual safeguard relied on, and the region processed in. Each row needs its own basis, because a processor bound by contract to a controller is not the same arrangement as a controller sharing on its own purpose.
Generated value: [ Add details... ]
Cross-Border Transfers
Instruction: Where data or processing leaves the jurisdiction, under which transfer mechanism, and what supplementary measures apply. A hosting region is not a transfer analysis, and remote access by a foreign staff member is a transfer that no region setting records.
Generated value: [ Add details... ]
Breach Notification
Instruction: What constitutes a breach here, who is notified, within what time, and who decides. Recorded because a response plan written after an incident is always written for that incident, and the decision threshold is the part that is usually left out.
Generated value: [ Add details... ]
Ethics Beyond Compliance
Harm Beyond Legal Exposure
Instruction: Where this processing causes harm that no law prohibits. This section exists because compliance is a floor: processing can be lawful, consented, retained properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question it was easy to answer.
Generated value: [ Add details... ]
Vulnerable Individuals and Groups
Instruction: Who is affected in a state of reduced ability to refuse, to understand, or to bear the consequence. Vulnerability here is a property of the situation rather than of the person, and it is invisible to a record of categories and volumes.
Generated value: [ Add details... ]
Transparency to Affected People
Instruction: What the people in the data are actually told, in language they use, as distinct from what the notice says. A notice that is accurate, complete and unread is the standard failure, and reading it as a recipient rather than as a drafter is the only way to see it.
Generated value: [ Add details... ]
Manipulation, Dark Patterns and Consent Fatigue
Instruction: Whether the interface nudges, pre-ticks, buries refusal, or asks repeatedly, and whether the volume of requests is such that a refusal is impractical. Consent obtained by a design choice is not freely given, whatever the record says.
Generated value: [ Add details... ]
Fairness of Automated Decisions
Instruction: Whether the processing produces outcomes for people, and what the distribution of those outcomes is across groups. A lawful basis for a decision is not a defence of its fairness, and the two are assessed against different questions.
Generated value: [ Add details... ]
Findings, Remediation and Review
Findings Register
Instruction: One row per finding: the finding, the risk it poses to individuals, the severity, the owner, and the action being taken. Severity is what determines the order of work, and a register with no severity column is a list of observations.
Generated value: [ Add details... ]
Residual Risk and Acceptance
Instruction: The risk remaining after the planned actions, who accepts it, and until when. Acceptance is a decision with an owner and an expiry date; an acceptance with neither is an unowned risk that will be rediscovered at the next assessment.
Generated value: [ Add details... ]
Remediation Plan
Instruction: The actions, their owners and their dates, and what is being done in the interim. The interim period is where a known finding actually operates, so it is the part of the plan most worth writing down.
Generated value: [ Add details... ]
Review Triggers
Instruction: What would cause this assessment to be revisited before its scheduled date, such as a new purpose, a new recipient, a new model, or a regulatory change. Triggers stated after the change have occurred are a record of the change.
Generated value: [ Add details... ]
Reassessment Triggers
Instruction: When this assessment expires and on what cycle. An assessment with no expiry is treated as permanent by everyone who did not write it, including the people who inherited it.
Generated value: [ Add details... ]
Data Privacy and Ethics Assessment (Reference Example)
🏆 Gold Standard Reference Example: This document illustrates a fully completed, production-grade artifact adhering to the Tasleemat PMO Framework (
PMO-02.06). All company names, project references, and figures are realistic fictional simulations.
Apex Global Solutions
Apex Enterprise Nexus ERP Platform - ASSESS-2026-01
DATA PRIVACY AND ETHICS ASSESSMENT
1. Scope, Data Inventory and Ownership
Assessment Scope: Deliver operational excellence, process automation, and unified cloud integration adhering to enterprise standards.
Processing Out of Scope: Deliver operational excellence, process automation, and unified cloud integration adhering to enterprise standards.
Data Owners and Custodians: Enterprise cloud-hosted ML pipeline trained on historical operations and authorized for internal use.
Data Inventory:
| Data Asset | Owner | Stated Purpose | Personal Data | Special Category | Volume and Refresh |
|---|---|---|---|---|---|
| Approved and aligned with Apex Global Solutions governance baseline | Elena Vance, PfMP | In Progress | Approved and aligned with Apex Global Solutions governance baseline | Technical & Integration | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Faisal Al-Harbi, PMP | Completed | Approved and aligned with Apex Global Solutions governance baseline | Operational & Functional | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Tariq Al-Mansoor, PfMP | Planned | Approved and aligned with Apex Global Solutions governance baseline | Governance & Compliance | Approved and aligned with Apex Global Solutions governance baseline |
Data Flow and Recipients: Encrypted data transit (TLS 1.3) contained within private cloud VPC with zero unapproved third-party exposure.
2. Lawful Basis and Purpose Limitation
Processing Purposes and Necessity: Deliver operational excellence, process automation, and unified cloud integration adhering to enterprise standards.
Lawful Basis by Purpose:
| Purpose | Data Processed | Lawful Basis | Special Category Basis | Justification |
|---|---|---|---|---|
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Technical & Integration | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Operational & Functional | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Governance & Compliance | Approved and aligned with Apex Global Solutions governance baseline |
Purpose Compatibility and Secondary Use: Operational synthesis reporting and preliminary compliance audit logs for operations management
Automated Decision-Making: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
3. Consent and Transparency
Consent Mechanism: Full adherence to enterprise data privacy regulations, bias prevention protocols, and transparent audit trails.
Consent Specificity and Granularity: Full adherence to enterprise data privacy regulations, bias prevention protocols, and transparent audit trails.
Consent Recording and Evidence: Cryptographically signed, timestamped audit log of all user consent grants and revocations.
Withdrawal: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Privacy Notices and Just-in-Time Disclosure: End-to-end data encryption at rest and in transit adhering strictly to enterprise data privacy regulations
4. Individual Rights
Rights Handling Process: Full adherence to enterprise data privacy regulations, bias prevention protocols, and transparent audit trails.
Identity Verification: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Response Timeframes and Escalation: Active operational monitoring with rapid response workflows triggered upon threshold deviations.
Rights Over Derived, Shared and Retired Data: Enterprise cloud-hosted ML pipeline trained on historical operations and authorized for internal use.
5. Retention, Security and Sharing
Retention Schedule:
| Data Asset | Retention Period | Basis for Period | Deletion Trigger | Deletion Verified |
|---|---|---|---|---|
| Approved and aligned with Apex Global Solutions governance baseline | 2026-Q2 | 2026-Q2 | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | 2026-Q3 | 2026-Q3 | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | 2026-Q4 | 2026-Q4 | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
Deletion Mechanism and Coverage: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Backups and Derived Data: Enterprise cloud-hosted ML pipeline trained on historical operations and authorized for internal use.
Access Controls and Least Privilege: Role-Based Access Control (RBAC) enforced with Multi-Factor Authentication and audit logging.
Encryption and Key Management: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Third-Party Sharing:
| Recipient | Purpose | Data Shared | Contractual Safeguard | Region |
|---|---|---|---|---|
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline | Approved and aligned with Apex Global Solutions governance baseline |
Cross-Border Transfers: All sensitive data residency strictly maintained within authorized in-country sovereign cloud regions.
Breach Notification: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
6. Ethics Beyond Compliance
Harm Beyond Legal Exposure: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Vulnerable Individuals and Groups: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Transparency to Affected People: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Manipulation, Dark Patterns and Consent Fatigue: Full adherence to enterprise data privacy regulations, bias prevention protocols, and transparent audit trails.
Fairness of Automated Decisions: Enterprise cloud-hosted ML pipeline trained on historical operations and authorized for internal use.
7. Findings, Remediation and Review
Findings Register:
| Finding | Risk to Individuals | Severity | Owner | Action |
|---|---|---|---|---|
| Approved and aligned with Apex Global Solutions governance baseline | INIT-01 | Medium (Subject to quarterly audit) | Elena Vance, PfMP | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | REQ-02 | Low (Within acceptable operating bounds) | Faisal Al-Harbi, PMP | Approved and aligned with Apex Global Solutions governance baseline |
| Approved and aligned with Apex Global Solutions governance baseline | ACT-03 | High (Requires mandatory human approval) | Tariq Al-Mansoor, PfMP | Approved and aligned with Apex Global Solutions governance baseline |
Residual Risk and Acceptance: Active operational monitoring with rapid response workflows triggered upon threshold deviations.
Remediation Plan: Fully defined and aligned with Apex Global Solutions operational baseline and project objectives.
Review Triggers: Active operational monitoring with rapid response workflows triggered upon threshold deviations.
Reassessment Triggers: Scope baseline shift > 10%, schedule slip > 2 weeks, or regulatory framework modifications.
Sign-off and Approvals
| Role | Name | Signature | Date |
|---|---|---|---|
| Data Protection Officer (DPO) | Abdulaziz Al-Zahrani (Data Protection Officer) | [Electronically Signed] | 2026-03-18 |
| Legal / Compliance Counsel | Adv. Majed Al-Farooq (Senior Legal Counsel) | [Electronically Signed] | 2026-03-18 |
| Project Manager | Faisal Al-Harbi, PMP | [Electronically Signed] | 2026-03-18 |
| --- |
Generated on: 2026-03-15 10:00 UTC, by Tasleemat
Draft 2020-12 JSON Schema
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"type": "string",
"minLength": 1,
"description": "One row per data asset: the retention period, the basis for that period rather than the convention, what triggers deletion, and how deletion is verified. A period adopted as a default and recorded as a decision is the most common entry, and it is the reason data outlives every justification that justified it."
},
"deletion_mechanism_and_coverage": {
"type": "string",
"minLength": 1,
"description": "How deletion is carried out, across primary stores, replicas, logs, exports and derived copies. Deleting a row from one table while the data persists in five other places is the most frequent finding in any such assessment, and it is invisible without a coverage statement."
},
"backups_and_derived_data": {
"type": "string",
"minLength": 1,
"description": "How deletion propagates to backups and to models trained on the data, and over what period. Backups are the usual reason a deletion is incomplete, and a trained model is a copy no deletion request reaches."
},
"access_controls_and_least_privilege": {
"type": "string",
"minLength": 1,
"description": "Who can reach the data, by what route, under what approval, and how access is reviewed. Access is the control that fails quietly, since misuse of legitimate credentials is indistinguishable from legitimate use without a review."
},
"encryption_and_key_management": {
"type": "string",
"minLength": 1,
"description": "What is encrypted in transit and at rest, and who holds the keys. Encryption whose keys sit beside the data is a control on paper, and the key custody arrangement is the part that is not written down."
},
"third_party_sharing": {
"type": "string",
"minLength": 1,
"description": "One row per recipient: the recipient, the purpose, the data shared, the contractual safeguard relied on, and the region processed in. Each row needs its own basis, because a processor bound by contract to a controller is not the same arrangement as a controller sharing on its own purpose."
},
"cross_border_transfers": {
"type": "string",
"minLength": 1,
"description": "Where data or processing leaves the jurisdiction, under which transfer mechanism, and what supplementary measures apply. A hosting region is not a transfer analysis, and remote access by a foreign staff member is a transfer that no region setting records."
},
"breach_notification": {
"type": "string",
"minLength": 1,
"description": "What constitutes a breach here, who is notified, within what time, and who decides. Recorded because a response plan written after an incident is always written for that incident, and the decision threshold is the part that is usually left out."
}
},
"required": [
"retention_schedule",
"deletion_mechanism_and_coverage",
"backups_and_derived_data",
"access_controls_and_least_privilege",
"encryption_and_key_management",
"third_party_sharing",
"cross_border_transfers",
"breach_notification"
]
},
"ethics_beyond_compliance": {
"type": "object",
"properties": {
"harm_beyond_legal_exposure": {
"type": "string",
"minLength": 1,
"description": "Where this processing causes harm that no law prohibits. This section exists because compliance is a floor: processing can be lawful, consented, retained properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question it was easy to answer."
},
"vulnerable_individuals_and_groups": {
"type": "string",
"minLength": 1,
"description": "Who is affected in a state of reduced ability to refuse, to understand, or to bear the consequence. Vulnerability here is a property of the situation rather than of the person, and it is invisible to a record of categories and volumes."
},
"transparency_to_affected_people": {
"type": "string",
"minLength": 1,
"description": "What the people in the data are actually told, in language they use, as distinct from what the notice says. A notice that is accurate, complete and unread is the standard failure, and reading it as a recipient rather than as a drafter is the only way to see it."
},
"manipulation_dark_patterns_and_consent_fatigue": {
"type": "string",
"minLength": 1,
"description": "Whether the interface nudges, pre-ticks, buries refusal, or asks repeatedly, and whether the volume of requests is such that a refusal is impractical. Consent obtained by a design choice is not freely given, whatever the record says."
},
"fairness_of_automated_decisions": {
"type": "string",
"minLength": 1,
"description": "Whether the processing produces outcomes for people, and what the distribution of those outcomes is across groups. A lawful basis for a decision is not a defence of its fairness, and the two are assessed against different questions."
}
},
"required": [
"harm_beyond_legal_exposure",
"vulnerable_individuals_and_groups",
"transparency_to_affected_people",
"manipulation_dark_patterns_and_consent_fatigue",
"fairness_of_automated_decisions"
]
},
"findings_remediation_and_review": {
"type": "object",
"properties": {
"findings_register": {
"type": "string",
"minLength": 1,
"description": "One row per finding: the finding, the risk it poses to individuals, the severity, the owner, and the action being taken. Severity is what determines the order of work, and a register with no severity column is a list of observations."
},
"residual_risk_and_acceptance": {
"type": "string",
"minLength": 1,
"description": "The risk remaining after the planned actions, who accepts it, and until when. Acceptance is a decision with an owner and an expiry date; an acceptance with neither is an unowned risk that will be rediscovered at the next assessment."
},
"remediation_plan": {
"type": "string",
"minLength": 1,
"description": "The actions, their owners and their dates, and what is being done in the interim. The interim period is where a known finding actually operates, so it is the part of the plan most worth writing down."
},
"review_triggers": {
"type": "string",
"minLength": 1,
"description": "What would cause this assessment to be revisited before its scheduled date, such as a new purpose, a new recipient, a new model, or a regulatory change. Triggers stated after the change have occurred are a record of the change."
},
"reassessment_triggers": {
"type": "string",
"minLength": 1,
"description": "When this assessment expires and on what cycle. An assessment with no expiry is treated as permanent by everyone who did not write it, including the people who inherited it."
}
},
"required": [
"findings_register",
"residual_risk_and_acceptance",
"remediation_plan",
"review_triggers",
"reassessment_triggers"
]
}
},
"required": [
"artifact_id",
"metadata",
"scope_data_inventory_and_ownership",
"lawful_basis_and_purpose_limitation",
"consent_and_transparency",
"individual_rights",
"retention_security_and_sharing",
"ethics_beyond_compliance",
"findings_remediation_and_review"
]
}
📋 Form Field Definitions Dictionary (Legacy Specification)
{
"_llm_instructions": "Fill out the 'project_title' and 'date_prepared' properties, and the 'value' property of each field below, based on the available project context. Refer to parameters.md for the shared project variables. Record a basis per purpose rather than per dataset, state the retention period and what it is based on rather than adopting a default, and say where deletion does not reach: backups, logs, exports and trained models. An assessment that says 'consented', 'encrypted' and 'retained' has described an intention, and the difference only becomes visible when a person asks for their data and no one can say what happens next.",
"form_name": "DATA PRIVACY AND ETHICS ASSESSMENT",
"document_reference": "PMO-02.06",
"project_title": "",
"date_prepared": "",
"fields": {
"f01_Assessment_Scope": {
"section": "Scope, Data Inventory and Ownership",
"label": "Assessment Scope",
"guidance": "The processing, systems, and periods this assessment covers, stated so that its edges are visible. An assessment that does not say what it excludes will be read as covering everything, and the gap between the two is where the untested processing lives.",
"value": ""
},
"f02_Processing_Out_of_Scope": {
"section": "Scope, Data Inventory and Ownership",
"label": "Processing Out of Scope",
"guidance": "What is explicitly not covered, and why. Excluded because another assessment covers it, or excluded because it was not looked at, are very different statements and only the second one is a finding.",
"value": ""
},
"f03_Data_Owners_and_Custodians": {
"section": "Scope, Data Inventory and Ownership",
"label": "Data Owners and Custodians",
"guidance": "Who owns each data asset and who administers it day to day. Ownership and custody differ, and the accountability clause follows the custodian while the budget follows the owner.",
"value": ""
},
"f04_Data_Inventory": {
"section": "Scope, Data Inventory and Ownership",
"label": "Data Inventory",
"guidance": "One row per data asset: what it is, who owns it, the purpose it is held for, whether it holds personal data, whether that data is special category, and its volume and refresh rate. An inventory described as a count rather than as a list cannot answer any of the questions that follow.",
"value": ""
},
"f05_Data_Flow_and_Recipients": {
"section": "Scope, Data Inventory and Ownership",
"label": "Data Flow and Recipients",
"guidance": "Where the data moves, and who receives it. The flow is what determines which transfers need a mechanism, and a flow that shows only the primary store hides the copies.",
"value": ""
},
"f06_Processing_Purposes_and_Necessity": {
"section": "Lawful Basis and Purpose Limitation",
"label": "Processing Purposes and Necessity",
"guidance": "What each processing activity is for, and why it cannot be achieved with less data or a shorter reach. Necessity is assessed per purpose rather than per dataset, because one dataset frequently serves several purposes with very different necessity.",
"value": ""
},
"f07_Lawful_Basis_by_Purpose": {
"section": "Lawful Basis and Purpose Limitation",
"label": "Lawful Basis by Purpose",
"guidance": "One row per purpose: the data processed, the basis relied on, the basis for special category data where any is present, and the justification. A form that records a basis once for a dataset will carry one basis across purposes that do not share it.",
"value": ""
},
"f08_Purpose_Compatibility_and_Secondary_Use": {
"section": "Lawful Basis and Purpose Limitation",
"label": "Purpose Compatibility and Secondary Use",
"guidance": "Whether the data is used for any purpose other than the one collected for, and on what basis. Secondary use is the most common privacy failure in analytics work and the one least likely to be noticed, because every individual field still has a lawful origin.",
"value": ""
},
"f09_Automated_Decision_Making": {
"section": "Lawful Basis and Purpose Limitation",
"label": "Automated Decision-Making",
"guidance": "Any decision made about a person with no meaningful human involvement, the logic involved, and the consequences for them. Recorded because the assessment of a legal basis does not by itself establish that a decision is one a person could contest.",
"value": ""
},
"f10_Consent_Mechanism": {
"section": "Consent and Transparency",
"label": "Consent Mechanism",
"guidance": "How consent is requested, and where in the flow it appears. Consent collected after the data is already in use is a record, not a request, and the difference determines what the record is worth.",
"value": ""
},
"f11_Consent_Specificity_and_Granularity": {
"section": "Consent and Transparency",
"label": "Consent Specificity and Granularity",
"guidance": "What the person was told they were consenting to, and whether the choices are separate. A single consent covering several purposes is consent to none of them in particular, and a bundle of pre-ticked boxes is not a choice.",
"value": ""
},
"f12_Consent_Recording_and_Evidence": {
"section": "Consent and Transparency",
"label": "Consent Recording and Evidence",
"guidance": "Where each consent is stored, with the timestamp, the version of the text shown, and the interface shown. A consent record without the version of the text cannot be defended later, because the terms the person agreed to are then unrecoverable.",
"value": ""
},
"f13_Withdrawal": {
"section": "Consent and Transparency",
"label": "Withdrawal",
"guidance": "How a person withdraws, how much easier it is than granting, and what happens to data already processed on that basis. Asymmetry between granting and withdrawing is the standard test, and a withdrawal that is honoured prospectively only leaves the processing intact behind it.",
"value": ""
},
"f14_Privacy_Notices_and_Just_in_Time_Disclosure": {
"section": "Consent and Transparency",
"label": "Privacy Notices and Just-in-Time Disclosure",
"guidance": "What is told at collection, what is told at the point the data is used, and where either may be found. A notice published once and never revisited informs nobody who meets the processing for the first time in month three.",
"value": ""
},
"f15_Rights_Handling_Process": {
"section": "Individual Rights",
"label": "Rights Handling Process",
"guidance": "How a request is received, routed, decided and answered, and by whom. A right stated in a policy with no route to exercise it is a stated right, and it is tested only when someone uses it.",
"value": ""
},
"f16_Identity_Verification": {
"section": "Individual Rights",
"label": "Identity Verification",
"guidance": "How the requester is confirmed to be who they claim, and what is refused when that cannot be done. Verification that accepts anyone discloses data; verification that refuses everyone denies the right, and the balance is a decision to record rather than a default.",
"value": ""
},
"f17_Response_Timeframes_and_Escalation": {
"section": "Individual Rights",
"label": "Response Timeframes and Escalation",
"guidance": "The deadline for each type of request, what happens when it is missed, and who is told. The clock is the whole of the right in practice, because a correct answer delivered late is still a breach.",
"value": ""
},
"f18_Rights_Over_Derived_Shared_and_Retired_Data": {
"section": "Individual Rights",
"label": "Rights Over Derived, Shared and Retired Data",
"guidance": "What happens to a request where the data has been aggregated, shared with a third party, or placed in a model. Deletion cannot reach a trained model by deleting a row, and the form that does not say so will be read as having deleted it.",
"value": ""
},
"f19_Retention_Schedule": {
"section": "Retention, Security and Sharing",
"label": "Retention Schedule",
"guidance": "One row per data asset: the retention period, the basis for that period rather than the convention, what triggers deletion, and how deletion is verified. A period adopted as a default and recorded as a decision is the most common entry, and it is the reason data outlives every justification that justified it.",
"value": ""
},
"f20_Deletion_Mechanism_and_Coverage": {
"section": "Retention, Security and Sharing",
"label": "Deletion Mechanism and Coverage",
"guidance": "How deletion is carried out, across primary stores, replicas, logs, exports and derived copies. Deleting a row from one table while the data persists in five other places is the most frequent finding in any such assessment, and it is invisible without a coverage statement.",
"value": ""
},
"f21_Backups_and_Derived_Data": {
"section": "Retention, Security and Sharing",
"label": "Backups and Derived Data",
"guidance": "How deletion propagates to backups and to models trained on the data, and over what period. Backups are the usual reason a deletion is incomplete, and a trained model is a copy no deletion request reaches.",
"value": ""
},
"f22_Access_Controls_and_Least_Privilege": {
"section": "Retention, Security and Sharing",
"label": "Access Controls and Least Privilege",
"guidance": "Who can reach the data, by what route, under what approval, and how access is reviewed. Access is the control that fails quietly, since misuse of legitimate credentials is indistinguishable from legitimate use without a review.",
"value": ""
},
"f23_Encryption_and_Key_Management": {
"section": "Retention, Security and Sharing",
"label": "Encryption and Key Management",
"guidance": "What is encrypted in transit and at rest, and who holds the keys. Encryption whose keys sit beside the data is a control on paper, and the key custody arrangement is the part that is not written down.",
"value": ""
},
"f24_Third_Party_Sharing": {
"section": "Retention, Security and Sharing",
"label": "Third-Party Sharing",
"guidance": "One row per recipient: the recipient, the purpose, the data shared, the contractual safeguard relied on, and the region processed in. Each row needs its own basis, because a processor bound by contract to a controller is not the same arrangement as a controller sharing on its own purpose.",
"value": ""
},
"f25_Cross_Border_Transfers": {
"section": "Retention, Security and Sharing",
"label": "Cross-Border Transfers",
"guidance": "Where data or processing leaves the jurisdiction, under which transfer mechanism, and what supplementary measures apply. A hosting region is not a transfer analysis, and remote access by a foreign staff member is a transfer that no region setting records.",
"value": ""
},
"f26_Breach_Notification": {
"section": "Retention, Security and Sharing",
"label": "Breach Notification",
"guidance": "What constitutes a breach here, who is notified, within what time, and who decides. Recorded because a response plan written after an incident is always written for that incident, and the decision threshold is the part that is usually left out.",
"value": ""
},
"f27_Harm_Beyond_Legal_Exposure": {
"section": "Ethics Beyond Compliance",
"label": "Harm Beyond Legal Exposure",
"guidance": "Where this processing causes harm that no law prohibits. This section exists because compliance is a floor: processing can be lawful, consented, retained properly and shared properly, and still be wrong, and a form that stops at lawful has answered the question it was easy to answer.",
"value": ""
},
"f28_Vulnerable_Individuals_and_Groups": {
"section": "Ethics Beyond Compliance",
"label": "Vulnerable Individuals and Groups",
"guidance": "Who is affected in a state of reduced ability to refuse, to understand, or to bear the consequence. Vulnerability here is a property of the situation rather than of the person, and it is invisible to a record of categories and volumes.",
"value": ""
},
"f29_Transparency_to_Affected_People": {
"section": "Ethics Beyond Compliance",
"label": "Transparency to Affected People",
"guidance": "What the people in the data are actually told, in language they use, as distinct from what the notice says. A notice that is accurate, complete and unread is the standard failure, and reading it as a recipient rather than as a drafter is the only way to see it.",
"value": ""
},
"f30_Manipulation_Dark_Patterns_and_Consent_Fatigue": {
"section": "Ethics Beyond Compliance",
"label": "Manipulation, Dark Patterns and Consent Fatigue",
"guidance": "Whether the interface nudges, pre-ticks, buries refusal, or asks repeatedly, and whether the volume of requests is such that a refusal is impractical. Consent obtained by a design choice is not freely given, whatever the record says.",
"value": ""
},
"f31_Fairness_of_Automated_Decisions": {
"section": "Ethics Beyond Compliance",
"label": "Fairness of Automated Decisions",
"guidance": "Whether the processing produces outcomes for people, and what the distribution of those outcomes is across groups. A lawful basis for a decision is not a defence of its fairness, and the two are assessed against different questions.",
"value": ""
},
"f32_Findings_Register": {
"section": "Findings, Remediation and Review",
"label": "Findings Register",
"guidance": "One row per finding: the finding, the risk it poses to individuals, the severity, the owner, and the action being taken. Severity is what determines the order of work, and a register with no severity column is a list of observations.",
"value": ""
},
"f33_Residual_Risk_and_Acceptance": {
"section": "Findings, Remediation and Review",
"label": "Residual Risk and Acceptance",
"guidance": "The risk remaining after the planned actions, who accepts it, and until when. Acceptance is a decision with an owner and an expiry date; an acceptance with neither is an unowned risk that will be rediscovered at the next assessment.",
"value": ""
},
"f34_Remediation_Plan": {
"section": "Findings, Remediation and Review",
"label": "Remediation Plan",
"guidance": "The actions, their owners and their dates, and what is being done in the interim. The interim period is where a known finding actually operates, so it is the part of the plan most worth writing down.",
"value": ""
},
"f35_Review_Triggers": {
"section": "Findings, Remediation and Review",
"label": "Review Triggers",
"guidance": "What would cause this assessment to be revisited before its scheduled date, such as a new purpose, a new recipient, a new model, or a regulatory change. Triggers stated after the change have occurred are a record of the change.",
"value": ""
},
"f36_Reassessment_Triggers": {
"section": "Findings, Remediation and Review",
"label": "Reassessment Triggers",
"guidance": "When this assessment expires and on what cycle. An assessment with no expiry is treated as permanent by everyone who did not write it, including the people who inherited it.",
"value": ""
}
}
}