Data Protection Impact Assessment (DPIA): Difference between revisions
No edit summary |
No edit summary |
||
| Line 43: | Line 43: | ||
| style="background-color:#ffffff;" | 24 June 2025 | | style="background-color:#ffffff;" | 24 June 2025 | ||
|- style="font-weight:bold;" | |- style="font-weight:bold;" | ||
| colspan="3 | | colspan="3" | | ||
=== 2. Purpose of Processing === | === 2. Purpose of Processing === | ||
Justify why personal data is processed. | Justify why personal data is processed. | ||
Revision as of 15:45, 7 July 2025
Introduction
A Data Protection Impact Assessment, also called a DPIA is a process required under Article 35 of the GDPR to help organizations identify and minimize the data protection risks of high-risk processing activities. It is especially important when using new technologies or handling sensitive data at scale. A DPIA ensures that privacy risks are assessed before processing begins and that appropriate safeguards are in place to protect individuals’ rights and freedoms.
A DPIA is necessary when data processing is likely to result in a high risk to individuals’ rights and freedoms—such as when using automated decision-making, profiling, large-scale processing of sensitive data, or systematic monitoring of public spaces. It is required before such processing begins to ensure risks are identified and mitigated in advance. The purpose of a DPIA is not only to protect individuals but also to help organizations demonstrate GDPR compliance, avoid legal or reputational harm, and implement privacy-by-design principles from the outset.
A DPIA is required when:
- System is used for systematic monitoring in a work environment, especially if used at scale
- AI is involved
- There is a potential risk to individuals' rights
As a rule of thumb, we advise deployers to conduct a DPIA. Please refer to the additional documentation, which includes a sample and a template specifically designed for Safety AI deployments.
Guide and sample DPIA
| Titles | Explanations | Sample Document |
|---|---|---|
1. Project DescriptionSet the context for the deployment. | ||
| Project Name | Choose a clear, descriptive name | Safety AI Deployment for Logistics Area Monitoring |
| Description | Briefly describe what the Safety AI system will do and where. Include zone coverage, system purpose, and any special setup. | Installation of Event Gates Safety AI system on factory floor to detect and log safety-critical events involving personnel and machinery (e.g., person–forklift proximity). |
| Data Controller | Enter your company name—the deployer is the data controller. | XYZ Manufacturing Ltd. |
| Contact Person | The responsible manager or DPO handling GDPR matters. | Jane Doe, Compliance Manager ([email protected]) |
| Date of Assessment | When you start or update this DPIA. | 24 June 2025 |
2. Purpose of ProcessingJustify why personal data is processed. | ||
| Explain the safety goals (e.g., prevent accidents, improve incident response). | To enhance occupational safety by detecting, recording, and reporting unsafe interactions between workers and moving equipment (e.g., forklifts, cranes). Data is used for real-time alerts and incident analysis. | |
| Be specific—link AI use to real, necessary safety functions. | ||
| This section supports your lawful basis (usually legitimate interest or legal obligation). | ||
3. Nature of Personal Data ProcessedClarify what types of personal data are involved. | ||
| Types of data | Include video recordings, logs, system metadata. | Video footage (optional), AI-detected safety events, timestamped logs |
| Data subjects | Who might be captured (e.g., employees, contractors, visitors). | Factory employees, contractors, and authorized visitors who enter monitored zones |
| Identifiers | State whether data is anonymized or could be indirectly identifying (e.g., uniform, patterns of movement). | While names are not recorded, individuals may be indirectly identifiable via video or behavioral patterns (e.g., unique clothing, routine movement) |
4. Data Flow and StorageDocument how data is collected, stored, and accessed. | ||
| Processing location | Note that Event Gates Safety AI operates on edge, not in the cloud. | On-edge device at each monitored zone (no cloud transfer) |
| Storage location | Specify where recordings and logs are stored, how long they are kept, and who has access. | Local edge device (internal SSD) |
| Retention | Mention features like automatic deletion, no internet access, and secured physical access. | Video footage and logs retained for max 7 days (configurable) Automatic deletion by default |
| Access | Restricted to safety personnel with login credentials and physical device access | |
5. Assessment of Necessity and ProportionalityShow that data processing is justified and minimal. | ||
| Necessity | Explain why this method (AI + video) is necessary for the purpose. | Monitoring is essential to prevent human–machine accidents in high-risk operational zones |
| Proportionality | Describe minimization features: zone filtering, event-based logging, optional recording. | No continuous surveillance; only event-triggered logging Recording limited to incident-related events Zones and rules configured to avoid unnecessary data capture Video recording can be disabled entirely if not needed |
| Show that there’s no less-intrusive way to achieve the same safety goal. | ||
6. Risks to Data SubjectsIdentify potential GDPR risks. | ||
| Use a table to rate risks (e.g., unauthorized access, over-monitoring, inability to fulfill access requests). | See table below | |
| Consider likelihood, impact, and what mitigations you’ve applied. | ||
| Event Gates features like on-edge processing, no facial recognition, and access control help reduce risk. | ||
7. Measures to Mitigate RisksList safeguards you have in place. | ||
| Technical | Built-in system features and configurations that enforce data protection through design and technology. | On-edge processing (no cloud dependency) Optional blurring of persons in recorded footage Password-protected user interface with audit logs Automatic deletion of video and logs based on retention settings No facial recognition or biometric profiling |
| Organizational | Internal controls and resource management practices that govern who can access data and how systems are operated. | Data access limited to trained safety staff |
| Process-based | Policies, documentation, and routines that ensure consistent, compliant handling of personal data and privacy responsibilities. | Clear internal policy defining processing purposes and operational restrictions |
8. ConsultationDemonstrate accountability and awareness. | ||
| Document any internal consultation with your DPO or legal team. | Internal consultation with DPO and legal department | |
| Note whether external advice was sought (only required for high-risk cases). | No external supervisory authority contact required at this stage | |
| State how data subjects are informed (e.g., signage, employee briefings, privacy notices). | Staff informed via updated safety policy and signage in monitored areas | |
9. ConclusionSum up the overall risk and your readiness. | ||
| Briefly confirm whether privacy risks are acceptable with the safeguards in place. | The Safety AI deployment at XYZ Manufacturing is deemed low risk when configured and operated as described. The system supports privacy-by-design through edge processing, role-based access, and configurable data minimization features. | |
| Note whether any actions are still required (e.g., install signage, finalize DPA). | No further mitigation required at this stage. | |
| If the system is compliant and no further risk exists, you can conclude the DPIA. | ||