"Beyond the Algorithm: Challenges, Ethics, and Humanism in the Standardization and Use of AI in EEG (2025)"

Standardization reaches maturity: but... what now?

We are entering a new era of electroencephalography: AI algorithms (such as SCORE-AI) match or exceed the performance of experts, enabling instant and democratized interpretation of clinical EEGs. But with technological maturity, new medical, ethical, regulatory, and human challenges arise that will be decisive for the future of our discipline.

Scientific and Practical Challenges

• Generalization and robustness: Although current models learn from thousands of SCORE-annotated EEGs, they still struggle to maintain high accuracy in the face of artifacts or signals extracted from unconventional equipment/setups.

• Managing "noise" and artifacts: A constant concern: AI can misinterpret muscular or electrical artifacts as pathological brain activity if not properly trained.

• Global interoperability: The SCORE standard and its equivalents need to be adopted by laboratories around the world. Achieving multiplatform and multilingual compatibility is currently one of the central debates in international forums and consortia.

Ethics and Data Sovereignty

• Privacy and consent: Global EEG databases require clear policies for anonymization, access, and secondary use of sensitive biomedical information.

• Transparency and explainability: Systems like XAIguiFormer seek to have models "explain" the reason for their diagnoses, allowing physicians to review which signal components the prediction was based on.

• Reducing algorithmic bias: Training AI in diverse populations is key to avoiding systematic errors or inequities in access and clinical outcomes.

Humanism and Medical Education in the Digital Age

• Hybrid training: The future demands that physicians understand not only the clinical aspects, but also the operational foundations and limitations of artificial intelligence applied to EEG. Medical education must be updated to integrate “algorithmic literacy” into curricula.

• The irreplaceable role of the expert: AI can facilitate interpretation and filter routine or simple cases, but complex conditions, clinical integration, and final decision-making must remain in human hands.

Future Perspectives

• Global SCORE consortia and next-generation standards: Open platforms allow for the sharing and unification of criteria, data, and codes across continents.

• The goal: universal, equitable, ethical, and secure access to the best possible EEG interpretation, from large hospitals to rural communities.

Conclusion

It's not “AI or the human,” but “AI with the human.” The maturity of standardization and AI in EEG marks a turning point; now, the challenge is to build ethical, educational, and technological frameworks that empower this transformation for the real and safe benefit of patients around the world.

“The future of standardization is no longer measured only in precision, but also in ethics, equity, and collaboration.”

What role will you play in this revolution?