Has your team been excitedly pitching you the latest AI automation system that promises to revolutionize customer assessments, credit decisions, or resource allocation? Before you sign off on that purchase order, there’s something you should know: the EU courts just made it crystal clear that algorithmic transparency isn’t optional – it’s mandatory.
The EU Court Just Raised the Stakes
In a landmark judgment (Case C‑203/22) delivered on February 27, 2025, the Court of Justice of the European Union (CJEU) has provided crucial clarity on what companies must disclose when they use automated decision-making systems.
The ruling establishes that (38):
“In the case of automated decision-making, including profiling, within the meaning of Article 22(1) of that regulation, the data subject may require the controller, as ‘meaningful information about the logic involved’, to explain, by means of relevant information and in a concise, transparent, intelligible and easily accessible form, the procedure and principles actually applied in order to use, by automated means, the personal data concerning that person with a view to obtaining a specific result, such as a credit profile.”
Let that sink in for a moment. Your fancy new AI system needs to be explainable – not just to your data scientists, but to the average customer whose data you’re processing.
No, You Can’t Hide Behind “It’s a Trade Secret”
Many organizations have been hiding behind the shield of “trade secrets” to avoid explaining how their algorithms work. The Court has now definitively rejected this approach (75):
“Article 15(1)(h) of the GDPR precludes inter alia the application of a provision such as Paragraph 4(6) of the DSG which excludes, as a rule, the data subject’s right of access, provided for in Article 15 of the GDPR, where such access would compromise a business or trade secret of the controller or of a third party.”
In other words, you can’t simply refuse to explain your algorithm because you consider it a trade secret. The rights of individuals to understand decisions made about them take precedence.
What You Need to Explain
Good news: you don’t have to disclose your entire algorithm or all the mathematical formulas behind your AI system. The Court clarified that (59):
“Those requirements cannot be satisfied either by the mere communication of a complex mathematical formula, such as an algorithm, or by the detailed description of all the steps in automated decision-making, since none of those would constitute a sufficiently concise and intelligible explanation.”
But you do need to provide meaningful explanations that allow individuals to understand:
- Which of their personal data was used
- How that data influenced the decision
- The procedure and principles applied
- How variations in the data might have led to different results
When Your System Can’t Be Explained, It Shouldn’t Be Deployed
The Court’s reasoning leads to a crucial conclusion: if an algorithmic outcome cannot be meaningfully contested because it cannot be meaningfully explained, then the AI system should not be deployed. Period.
As the judgment states (56):
“If the individuals affected by an automated decision, including profiling, were not in a position to understand the reasons which led to that decision before expressing their point of view or contesting the decision, those rights would not, accordingly, satisfy in full their purpose of protecting those individuals against the particular risks to their rights and freedoms represented by the automated processing of their personal data.”
Why You Need Professional Help
This is exactly why you should contact professionals (like digitaliziran.si) before implementing complex automations. They can help you:
- Design AI systems with explainability built in from the ground up
- Create proper documentation and explanation frameworks
- Implement robust data protection impact assessments
- Establish procedures for handling access requests
- Balance innovation with compliance requirements
The Bottom Line
The message from the EU’s highest court is clear: algorithmic transparency is not negotiable. Organizations that deploy automated decision-making systems must be able to explain them in a way that’s meaningful to the individuals affected.
If you’re considering implementing AI systems without professional guidance on these requirements, think again. The cost of getting this wrong isn’t just potential fines – it’s also potential litigation, reputation damage, and having to dismantle systems you’ve already invested in.
So before you sign off on that next AI project, ask yourself: can we explain how this works to the people it will affect? If the answer is no, it’s time to call in the experts.