GDPR Article 22
Automated individual decision-making, including profiling
The data subject shall have the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects concerning him or her or similarly significantly affects him or her.
Paragraph 1 shall not apply if the decision:
(a) is necessary for entering into, or performance of, a contract between the data subject and a data controller;
(b) is authorised by Union or Member State law to which the controller is subject and which also lays down suitable measures to safeguard the data subject's rights and freedoms and legitimate interests; or
(c) is based on the data subject's explicit consent.
In the cases referred to in points (a) and (c) of paragraph 2, the data controller shall implement suitable measures to safeguard the data subject's rights and freedoms and legitimate interests, at least the right to obtain human intervention on the part of the controller, to express his or her point of view and to contest the decision.
Decisions referred to in paragraph 2 shall not be based on special categories of personal data referred to in Article 9(1), unless point (a) or (g) of Article 9(2) applies and suitable measures to safeguard the data subject's rights and freedoms and legitimate interests are in place.
· GDPR Article 22 Compliance Guide
Article 22 of the GDPR addresses automated decision-making and profiling that significantly affects individuals. For businesses using AI, algorithms, or automated systems that make decisions about people, implementing proper safeguards is essential. Here's your practical guide to compliance:
Understanding the Core Requirements
Article 22 gives individuals the right not to be subject to purely automated decisions that have legal or similarly significant effects, with three specific exceptions where such processing is permitted.
Step-by-Step Implementation Plan
1. Identify Your Automated Decision Systems
Start by conducting an inventory of all your automated processing systems:
Credit scoring algorithms
Automated recruitment tools
Pricing algorithms that personalize offers
Customer segmentation systems
Fraud detection systems
Automated approval/denial processes
2. Assess Impact & Applicability
For each system identified:
Determine if decisions are "solely automated" (without meaningful human oversight)
Evaluate if outcomes produce legal or similarly significant effects
Document your assessment with concrete examples
3. Establish Your Legal Basis
If your automated system falls under Article 22, implement one of these exceptions:
Contract necessity: Document specifically how the automated decision is essential for contract performance
Legal authorization: Identify the specific EU or Member State law permitting the processing
Explicit consent: Develop clear consent mechanisms that specifically address automated decision-making
4. Implement Required Safeguards
Regardless of which exception you use, establish these protective measures:
Human intervention mechanism: Create a clear process allowing individuals to request human review of automated decisions
Designate qualified staff responsible for reviews
Set reasonable timeframes for completion
Document the review process
Expression of views: Develop channels for individuals to present their perspective
Create user-friendly forms or interfaces
Train staff to handle these submissions appropriately
Contestation procedure: Establish a formal process for challenging decisions
Design clear appeal workflows with defined steps
Document how contested decisions are reassessed
5. Enhance Transparency
Update your privacy notices to include:
Clear explanations of automated decision-making processes
The logic involved in these decisions (in simple terms)
The significance and potential consequences for individuals
How to access safeguards (human intervention, expression of views, contestation)
6. Special Categories Protection
For systems that might process sensitive data (race, health, etc.):
Implement additional safeguards and security measures
Ensure you have appropriate legal basis under Article 9
Consider data minimization techniques or pseudonymization
Conduct enhanced impact assessments
7. Document Everything
Maintain comprehensive records including:
System descriptions and data flow diagrams
Decision-making logic documentation
Risk assessments
Safeguard implementation details
Staff training records
Human oversight procedures
Practical Best Practices
Conduct DPIAs: Perform Data Protection Impact Assessments for all automated decision systems
Test for bias: Regularly audit systems for unfair outcomes or discriminatory patterns
Create escalation paths: Develop clear workflows for handling complex cases
Monitor effectiveness: Track metrics on human interventions and appeals
Staff training: Ensure team members understand Article 22 requirements
Regular reviews: Schedule periodic assessments of automated systems
· GDPR Article 22 Compliance Guide
Article 22 of the GDPR addresses automated decision-making and profiling that significantly affects individuals. For businesses using AI, algorithms, or automated systems that make decisions about people, implementing proper safeguards is essential. Here's your practical guide to compliance:
Understanding the Core Requirements
Article 22 gives individuals the right not to be subject to purely automated decisions that have legal or similarly significant effects, with three specific exceptions where such processing is permitted.
Step-by-Step Implementation Plan
1. Identify Your Automated Decision Systems
Start by conducting an inventory of all your automated processing systems:
Credit scoring algorithms
Automated recruitment tools
Pricing algorithms that personalize offers
Customer segmentation systems
Fraud detection systems
Automated approval/denial processes
2. Assess Impact & Applicability
For each system identified:
Determine if decisions are "solely automated" (without meaningful human oversight)
Evaluate if outcomes produce legal or similarly significant effects
Document your assessment with concrete examples
3. Establish Your Legal Basis
If your automated system falls under Article 22, implement one of these exceptions:
Contract necessity: Document specifically how the automated decision is essential for contract performance
Legal authorization: Identify the specific EU or Member State law permitting the processing
Explicit consent: Develop clear consent mechanisms that specifically address automated decision-making
4. Implement Required Safeguards
Regardless of which exception you use, establish these protective measures:
Human intervention mechanism: Create a clear process allowing individuals to request human review of automated decisions
Designate qualified staff responsible for reviews
Set reasonable timeframes for completion
Document the review process
Expression of views: Develop channels for individuals to present their perspective
Create user-friendly forms or interfaces
Train staff to handle these submissions appropriately
Contestation procedure: Establish a formal process for challenging decisions
Design clear appeal workflows with defined steps
Document how contested decisions are reassessed
5. Enhance Transparency
Update your privacy notices to include:
Clear explanations of automated decision-making processes
The logic involved in these decisions (in simple terms)
The significance and potential consequences for individuals
How to access safeguards (human intervention, expression of views, contestation)
6. Special Categories Protection
For systems that might process sensitive data (race, health, etc.):
Implement additional safeguards and security measures
Ensure you have appropriate legal basis under Article 9
Consider data minimization techniques or pseudonymization
Conduct enhanced impact assessments
7. Document Everything
Maintain comprehensive records including:
System descriptions and data flow diagrams
Decision-making logic documentation
Risk assessments
Safeguard implementation details
Staff training records
Human oversight procedures
Practical Best Practices
Conduct DPIAs: Perform Data Protection Impact Assessments for all automated decision systems
Test for bias: Regularly audit systems for unfair outcomes or discriminatory patterns
Create escalation paths: Develop clear workflows for handling complex cases
Monitor effectiveness: Track metrics on human interventions and appeals
Staff training: Ensure team members understand Article 22 requirements
Regular reviews: Schedule periodic assessments of automated systems
· GDPR Article 22 Compliance Guide
Article 22 of the GDPR addresses automated decision-making and profiling that significantly affects individuals. For businesses using AI, algorithms, or automated systems that make decisions about people, implementing proper safeguards is essential. Here's your practical guide to compliance:
Understanding the Core Requirements
Article 22 gives individuals the right not to be subject to purely automated decisions that have legal or similarly significant effects, with three specific exceptions where such processing is permitted.
Step-by-Step Implementation Plan
1. Identify Your Automated Decision Systems
Start by conducting an inventory of all your automated processing systems:
Credit scoring algorithms
Automated recruitment tools
Pricing algorithms that personalize offers
Customer segmentation systems
Fraud detection systems
Automated approval/denial processes
2. Assess Impact & Applicability
For each system identified:
Determine if decisions are "solely automated" (without meaningful human oversight)
Evaluate if outcomes produce legal or similarly significant effects
Document your assessment with concrete examples
3. Establish Your Legal Basis
If your automated system falls under Article 22, implement one of these exceptions:
Contract necessity: Document specifically how the automated decision is essential for contract performance
Legal authorization: Identify the specific EU or Member State law permitting the processing
Explicit consent: Develop clear consent mechanisms that specifically address automated decision-making
4. Implement Required Safeguards
Regardless of which exception you use, establish these protective measures:
Human intervention mechanism: Create a clear process allowing individuals to request human review of automated decisions
Designate qualified staff responsible for reviews
Set reasonable timeframes for completion
Document the review process
Expression of views: Develop channels for individuals to present their perspective
Create user-friendly forms or interfaces
Train staff to handle these submissions appropriately
Contestation procedure: Establish a formal process for challenging decisions
Design clear appeal workflows with defined steps
Document how contested decisions are reassessed
5. Enhance Transparency
Update your privacy notices to include:
Clear explanations of automated decision-making processes
The logic involved in these decisions (in simple terms)
The significance and potential consequences for individuals
How to access safeguards (human intervention, expression of views, contestation)
6. Special Categories Protection
For systems that might process sensitive data (race, health, etc.):
Implement additional safeguards and security measures
Ensure you have appropriate legal basis under Article 9
Consider data minimization techniques or pseudonymization
Conduct enhanced impact assessments
7. Document Everything
Maintain comprehensive records including:
System descriptions and data flow diagrams
Decision-making logic documentation
Risk assessments
Safeguard implementation details
Staff training records
Human oversight procedures
Practical Best Practices
Conduct DPIAs: Perform Data Protection Impact Assessments for all automated decision systems
Test for bias: Regularly audit systems for unfair outcomes or discriminatory patterns
Create escalation paths: Develop clear workflows for handling complex cases
Monitor effectiveness: Track metrics on human interventions and appeals
Staff training: Ensure team members understand Article 22 requirements
Regular reviews: Schedule periodic assessments of automated systems