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Data Protection Impact Assessment (DPIA) Template

Ask Eve AI

Date of Assessment: [Date]
Assessed By: [Name, Role]
Review Date: [Date - recommend annual review]


1. Executive Summary

Field Details
Processing Activity Name [e.g., "Job Candidate Assessment Specialist"]
Brief Description [1-2 sentence summary]
Risk Level ☐ Low ☐ Medium ☐ High
DPIA Required? ☐ Yes ☐ No
Status ☐ Draft ☐ Under Review ☐ Approved ☐ Requires Revision

2. Description of the Processing

2.1 Nature of the Processing

What Personal Data will be processed?

  • Contact information (name, email, phone)
  • Identification data (ID numbers, passport)
  • Professional data (CV, work history, qualifications)
  • Assessment results or scores
  • Communication records
  • Behavioral data (how users interact with the system)
  • Technical data (IP addresses, device information)
  • Other: _______________

Categories of Data Subjects:

  • Job applicants/candidates
  • Employees
  • Customers
  • End users/consumers
  • Other: _______________

Volume of Data Subjects:

  • < 100
  • 100-1,000
  • 1,000-10,000
  • > 10,000

2.2 Scope of the Processing

What is the purpose of the processing?

[Describe the specific business purpose, e.g., "To assess job candidates' suitability for specific roles by analyzing their responses to standardized questions"]

How will the data be collected?

  • Directly from data subjects (forms, interviews)
  • From third parties (recruiters, references)
  • Automated collection (web forms, chatbots)
  • Other: _______________

Where will data be stored?

  • EU (specify: France - Scaleway)
  • Non-EU (specify and justify): _______________

2.3 Context of the Processing

Is this processing new or existing?

  • New processing activity
  • Modification of existing processing
  • Existing processing (periodic review)

Who has access to the Personal Data?

  • Ask Eve AI employees (specify roles): _______________
  • Customer/Tenant employees
  • Partners (specify): _______________
  • Sub-Processors (list): _______________
  • Other: _______________

How long will data be retained?

[Specify retention period and justification, e.g., "Candidate data retained for 12 months to comply with recruitment record-keeping requirements"]


3. Necessity and Proportionality Assessment

3.1 Lawful Basis

What is the lawful basis for processing? (Article 6 GDPR)

  • Consent - Data subject has given explicit consent
  • Contract - Processing necessary for contract performance
  • Legal obligation - Required by law
  • Vital interests - Necessary to protect someone's life
  • Public task - Performing a public interest task
  • Legitimate interests - Necessary for legitimate interests (requires balancing test)

Justification:

[Explain why this lawful basis applies]

3.2 Special Categories of Data (if applicable)

Does the processing involve special categories of data? (Article 9 GDPR)

  • No
  • Yes - racial or ethnic origin
  • Yes - political opinions
  • Yes - religious or philosophical beliefs
  • Yes - trade union membership
  • Yes - genetic data
  • Yes - biometric data for identification
  • Yes - health data
  • Yes - sex life or sexual orientation data

If yes, what is the additional lawful basis?

[Article 9(2) provides specific conditions - specify which applies]

3.3 Automated Decision-Making

Does the processing involve automated decision-making or profiling?

  • No
  • Yes - automated decision-making WITH human oversight
  • Yes - fully automated decision-making (no human intervention)

If yes:

Does it produce legal effects or similarly significant effects?

  • No
  • Yes (explain): _______________

What safeguards are in place?

  • Right to obtain human intervention
  • Right to express point of view
  • Right to contest the decision
  • Regular accuracy reviews
  • Transparency about logic involved
  • Other: _______________

3.4 Necessity Test

Is the processing necessary to achieve the stated purpose?

☐ Yes ☐ No

Justification:

[Explain why this specific processing is necessary and whether less intrusive alternatives were considered]

Could the purpose be achieved with less data or through other means?

☐ Yes (explain why not pursued): _______________
☐ No

3.5 Proportionality Test

Is the processing proportionate to the purpose?

☐ Yes ☐ No

Data Minimization:

  • Are you collecting only the minimum data necessary? ☐ Yes ☐ No
  • Have you considered pseudonymization or anonymization? ☐ Yes ☐ No ☐ N/A
  • Can data be aggregated instead of individual records? ☐ Yes ☐ No ☐ N/A

Storage Limitation:

  • Is the retention period justified and documented? ☐ Yes ☐ No
  • Is there an automated deletion process? ☐ Yes ☐ No ☐ Planned

4. Stakeholder Consultation

4.1 Data Subject Consultation

Have data subjects been consulted about this processing?

☐ Yes ☐ No ☐ Not required

If yes, how were they consulted?

[Describe consultation method: surveys, focus groups, user research, etc.]

Key concerns raised by data subjects:

[List any concerns and how they were addressed]

4.2 DPO or Security Contact Consultation

Has the DPO or security contact been consulted?

☐ Yes ☐ No ☐ N/A (no formal DPO)

Comments from DPO/Security Contact:

[Record any recommendations or concerns]


5. Risk Assessment

5.1 Risk Identification

For each risk, assess:

  • Likelihood: Negligible / Low / Medium / High
  • Severity: Negligible / Low / Medium / High
  • Overall Risk: Low / Medium / High / Very High

Risk 1: Unauthorized Access or Data Breach

Description: Personal data could be accessed by unauthorized parties due to security vulnerabilities.

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 2: Discrimination or Bias in Automated Decisions

Description: Automated processing could result in discriminatory outcomes or unfair treatment.

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 3: Lack of Transparency

Description: Data subjects may not understand how their data is processed or decisions are made.

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 4: Inability to Exercise Data Subject Rights

Description: Data subjects may have difficulty exercising their rights (access, erasure, portability, etc.).

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 5: Data Quality Issues

Description: Inaccurate or outdated data could lead to incorrect decisions or outcomes.

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 6: Function Creep / Scope Expansion

Description: Data collected for one purpose could be used for other purposes without consent.

Assessment Rating
Likelihood ☐ Negligible ☐ Low ☐ Medium ☐ High
Severity (if occurs) ☐ Negligible ☐ Low ☐ Medium ☐ High
Overall Risk ☐ Low ☐ Medium ☐ High ☐ Very High

Additional Risks:

[Add any processing-specific risks]


6. Mitigation Measures

For each identified risk, document mitigation measures:

Risk 1: Unauthorized Access or Data Breach

Mitigation Measures:

  • Encryption in transit (TLS 1.2+)
  • Encryption at rest
  • Multi-factor authentication
  • Access controls (RBAC)
  • Regular security audits
  • WAF and DDoS protection (Bunny.net Shield)
  • Multi-tenant data isolation
  • Regular security training
  • Incident response plan
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 2: Discrimination or Bias in Automated Decisions

Mitigation Measures:

  • Regular bias testing of AI models
  • Diverse training data sets
  • Human review of automated decisions
  • Clear criteria for decision-making
  • Right to contest decisions
  • Transparency about decision logic
  • Regular fairness audits
  • Monitoring of outcomes by demographic groups
  • Ability to request explanation
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 3: Lack of Transparency

Mitigation Measures:

  • Clear Privacy Policy explaining processing
  • Explicit consent mechanisms
  • Plain language explanations
  • Information provided before data collection
  • Explanation of automated decision logic
  • Contact information for questions
  • Regular communication with data subjects
  • Privacy-by-design approach (anonymous until consent)
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 4: Inability to Exercise Data Subject Rights

Mitigation Measures:

  • Clear procedures for rights requests
  • Multiple request channels (email, helpdesk)
  • 30-day response timeframe
  • Technical capability to extract data
  • Data portability in standard formats
  • Secure deletion processes
  • Account disabling/restriction capability
  • Identity verification procedures
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 5: Data Quality Issues

Mitigation Measures:

  • Data validation on input
  • Regular data accuracy reviews
  • Ability for data subjects to correct errors
  • Clear data update procedures
  • Data quality monitoring
  • Source verification for third-party data
  • Archiving of outdated data
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Risk 6: Function Creep / Scope Expansion

Mitigation Measures:

  • Documented purpose limitation
  • Access controls preventing unauthorized use
  • Regular compliance audits
  • Privacy Policy clearly states purposes
  • Consent required for new purposes
  • Technical controls preventing misuse
  • Staff training on data protection
  • Other: _______________

Residual Risk After Mitigation: ☐ Low ☐ Medium ☐ High ☐ Very High

Additional Mitigation Measures

[Document any additional mitigation measures not covered above]


7. Data Subject Rights Implementation

How will you ensure data subjects can exercise their rights?

Right of Access (Article 15)

  • Procedure documented
  • Technical capability implemented
  • Response within 30 days
  • Method: _______________

Right to Rectification (Article 16)

  • Procedure documented
  • Technical capability implemented
  • Response within 30 days
  • Method: _______________

Right to Erasure (Article 17)

  • Procedure documented
  • Technical capability implemented
  • Response within 30 days
  • Method: _______________
  • Limitations: _______________

Right to Restriction (Article 18)

  • Procedure documented
  • Technical capability implemented (account disabling)
  • Response within 30 days

Right to Data Portability (Article 20)

  • Procedure documented
  • Technical capability implemented
  • Export format: JSON / CSV / XML / Other: _______________

Right to Object (Article 21)

  • Procedure documented
  • Opt-out mechanisms implemented
  • Clear in Privacy Policy

Rights Related to Automated Decision-Making (Article 22)

  • Human intervention available
  • Explanation of logic provided
  • Right to contest implemented
  • Documented in Privacy Policy

8. Privacy by Design and Default

Privacy Enhancing Technologies Implemented:

  • Data minimization (collect only necessary data)
  • Pseudonymization (where applicable)
  • Anonymization (where applicable)
  • Anonymous interaction until consent (privacy-by-design)
  • Encryption (in transit and at rest)
  • Access controls and authentication
  • Audit logging
  • Secure deletion
  • Data isolation (multi-tenant architecture)
  • Other: _______________

Default Settings:

  • Most privacy-protective settings by default
  • Opt-in (not opt-out) for non-essential processing
  • Clear consent mechanisms before data collection
  • Limited data sharing by default

9. Compliance with Principles

For each GDPR principle, confirm compliance:

Lawfulness, Fairness, Transparency (Article 5(1)(a))

  • Lawful basis identified and documented
  • Processing is fair and transparent
  • Privacy Policy clearly explains processing
  • Evidence: _______________

Purpose Limitation (Article 5(1)(b))

  • Specific purposes documented
  • Data not used for incompatible purposes
  • New purposes require new consent/legal basis
  • Evidence: _______________

Data Minimization (Article 5(1)(c))

  • Only necessary data collected
  • Regular review of data collected
  • Excess data not retained
  • Evidence: _______________

Accuracy (Article 5(1)(d))

  • Mechanisms to ensure data accuracy
  • Ability to correct inaccurate data
  • Regular data quality reviews
  • Evidence: _______________

Storage Limitation (Article 5(1)(e))

  • Retention periods defined and documented
  • Automated deletion where appropriate
  • Justification for retention documented
  • Evidence: _______________

Integrity and Confidentiality (Article 5(1)(f))

  • Appropriate security measures implemented
  • Protection against unauthorized access
  • Encryption and access controls in place
  • Evidence: See Annex 2 of DPA

Accountability (Article 5(2))

  • Documentation of compliance measures
  • Records of processing activities maintained
  • DPIA conducted and documented
  • DPA in place with processors
  • Evidence: This DPIA, DPA with customers

10. International Transfers

Does this processing involve transfer to third countries?

☐ No - all processing within EU
☐ Yes (complete below)

If yes:

Country/Region: _______________

Transfer Mechanism:

  • Adequacy decision (Article 45)
  • Standard Contractual Clauses (Article 46)
  • Binding Corporate Rules (Article 47)
  • Other: _______________

Transfer Impact Assessment Completed? ☐ Yes ☐ No

Additional Safeguards:

[Document supplementary measures to ensure adequate protection]


11. Documentation and Records

Documentation Maintained:

  • This DPIA
  • Privacy Policy
  • Data Processing Agreement
  • Consent records (if applicable)
  • Records of processing activities (Article 30)
  • Data breach register
  • Data Subject rights request log
  • Staff training records
  • Sub-processor agreements

Record of Processing Activities (Article 30) Completed?

☐ Yes ☐ No ☐ In Progress


12. Outcomes and Recommendations

12.1 Overall Risk Assessment

After implementing mitigation measures, what is the residual risk level?

☐ Low - processing can proceed
☐ Medium - additional measures recommended
☐ High - significant concerns, consult DPO/legal counsel
☐ Very High - processing should not proceed without major changes

12.2 Recommendations

Recommended Actions Before Processing Begins:

  1. [Action item 1]
  2. [Action item 2]
  3. [Action item 3]

Recommended Monitoring/Review Activities:

  1. [Monitoring item 1]
  2. [Monitoring item 2]
  3. [Monitoring item 3]

12.3 Consultation with Supervisory Authority

Is consultation with supervisory authority required?

☐ No - residual risk is acceptable
☐ Yes - high residual risk remains despite mitigation (Article 36)

If yes, when will consultation occur? _______________

12.4 Sign-Off

DPIA Completed By:

Name: _______________
Role: _______________
Date: _______________
Signature: _______________

Reviewed and Approved By:

Name: _______________
Role: _______________
Date: _______________
Signature: _______________

Next Review Date: _______________

(Recommend annual review or when significant changes occur)


Appendix A: Completed Example - Job Candidate Assessment

This appendix provides a completed example for reference.

Example: Job Candidate Assessment Specialist

Processing Activity: AI-powered job candidate assessment tool

Personal Data Processed:

  • Assessment responses (text)
  • Communication records (chatbot interactions)
  • Contact information (name, email) - collected AFTER assessment with consent
  • Assessment scores/results

Purpose: To assess candidates' suitability for job roles based on their responses to standardized questions

Lawful Basis:

  • Consent (candidates explicitly consent before providing contact information)
  • Contract (processing necessary to take steps at request of data subject prior to entering into contract)

Automated Decision-Making: Yes, with human oversight. Candidates are assessed by AI, but:

  • Contact information only collected AFTER positive assessment
  • Human recruiter makes final hiring decisions
  • Candidates can restart assessment at any time
  • Candidates informed about AI assessment before beginning

Key Risks Identified:

  1. Bias/discrimination in assessment algorithms - MEDIUM risk
  2. Lack of transparency about assessment criteria - MEDIUM risk
  3. Data breach exposing candidate information - LOW risk (after mitigation)

Key Mitigation Measures:

  • Anonymous assessment until consent obtained
  • Clear explanation of assessment process
  • Right to contest results
  • Human review of all final decisions
  • Regular bias testing of algorithms
  • Strong technical security measures (encryption, access controls)
  • 12-month retention period with secure deletion

Residual Risk: LOW - processing can proceed

Special Considerations:

  • Candidates must be informed about automated decision-making
  • Privacy Policy must explain assessment logic
  • Contact information collected only after explicit consent
  • Right to human intervention clearly communicated

Appendix B: Resources and References

GDPR Articles Referenced:

  • Article 5: Principles relating to processing
  • Article 6: Lawfulness of processing
  • Article 9: Special categories of data
  • Article 13-14: Information to be provided
  • Article 15-22: Data subject rights
  • Article 22: Automated decision-making
  • Article 28: Processor obligations
  • Article 30: Records of processing activities
  • Article 33-34: Data breach notification
  • Article 35: Data Protection Impact Assessment
  • Article 36: Prior consultation with supervisory authority
  • Article 45-46: International transfers

Additional Guidance:

  • WP29 Guidelines on DPIAs (WP 248)
  • WP29 Guidelines on Automated Decision-Making (WP 251)
  • ICO DPIA Guidance
  • EDPB Guidelines on processing personal data for scientific research
  • Belgian DPA Guidance (https://www.gegevensbeschermingsautoriteit.be)

Internal Documents:

  • Ask Eve AI Data Protection Agreement
  • Ask Eve AI Privacy Policy
  • Technical and Organizational Measures (DPA Annex 2)

End of DPIA Template