Last Updated on 2026 年 3 月 9 日 by 総合編集組
Taiwan AIEC Evaluation Center: Complete 2024 Guide to 42 AI Models, Taiwan Values Indicators, and Four Risk Levels
Taiwan stands at the forefront of global AI governance with the launch of its Artificial Intelligence Evaluation Center (AIEC). Established under the guidance of the Ministry of Digital Affairs’ Department of Industrial Development, AIEC serves as a trusted third-party testing hub that bridges international standards with local needs. This in-depth summary explains every key aspect of AIEC’s framework, real-world testing results, submission process, and strategic importance for developers, enterprises, and policymakers worldwide who want to understand how Taiwan is building responsible, sovereign AI.
Global Context and Why Taiwan Needs Its Own AI Evaluation Center The world is shifting from “technology-first” to “responsibility-first” AI governance. The European Union AI Act, America’s NIST AI Risk Management Framework, and ISO/IEC 42001 now set the global benchmark. Taiwan, as a semiconductor powerhouse and critical node in global supply chains, cannot rely solely on foreign models trained on less than 0.1% Traditional Chinese data. This cultural and linguistic gap often causes bias in understanding Taiwanese law, values, and social norms. AIEC was created precisely to close this gap while aligning with international best practices.
Three-Pillar Structure: Evaluation Center, Verification Body, and Testing Lab AIEC operates through a clear “testing-verification separation” model to guarantee objectivity. The central AIEC office sets policies, testing methods, and industry guidelines and acts as the single contact point for vendors. The Verification Body, run by the National Institute of Cybersecurity (NICS), reviews reports for legal and standards compliance before issuing the final certificate. Actual technical testing is performed by accredited Testing Labs, with the Industrial Technology Research Institute (ITRI) Measurement Center as the first approved lab. This separation prevents conflicts of interest and mirrors internationally recognized laboratory accreditation systems.
Four-Stage Submission Process Designed for Real-World Development Vendors follow a practical four-step journey. First comes application and preliminary risk classification, where product descriptions, technical manuals, and API documents are submitted. Next is technical integration—either online API testing for cloud models or offline model deployment for high-privacy scenarios such as defense or finance. The third stage offers a free Mock Evaluation using approximately 1,725 public test questions, allowing developers to identify and fix issues early without any certification pressure. Finally, formal testing uses confidential private question banks. Testing Labs produce raw data reports, which NICS then reviews to issue the official evaluation certificate.
Ten Core Evaluation Dimensions with Five Key Pillars AIEC’s system covers ten technical criteria, but the five most critical pillars are accuracy, privacy, reliability, fairness, and cybersecurity. Accuracy varies by domain: large language models are tested on factual correctness, hallucination avoidance, legal understanding, and logical reasoning using Taiwan’s high-school exam questions. Computer vision models are evaluated on recognition rate, object localization, and robustness to lighting or occlusion changes. Medical AI follows TFDA guidelines with sensitivity, specificity, and Taiwan-specific clinical data validation. Privacy and security tests simulate adversarial attacks such as prompt injection and inference attacks that attempt to extract personally identifiable information. Edge computing models receive extra checks on resource consumption and side-channel attack resistance.
The Unique “Taiwan Values” Indicator One of AIEC’s most innovative contributions is the “Taiwan Values” benchmark. This indicator measures whether model outputs align with Taiwan’s democratic principles, human rights, and everyday language habits—something rarely seen in global evaluation frameworks. It ensures AI systems do not introduce cultural bias against specific genders, ethnic groups, or social contexts.
Risk Classification System Based on EU AI Act AIEC adopts a four-tier risk model that is easy for international companies to understand:
- Unacceptable Risk – social scoring or manipulative systems that threaten human rights; prohibited in Taiwan.
- High Risk – critical infrastructure, education admissions, recruitment, law enforcement, and medical diagnosis; mandatory full evaluation and lifecycle monitoring required.
- Limited Risk – chatbots and deepfake generators; must clearly label AI-generated content.
- Minimal Risk – spam filters or game NPCs; voluntary compliance encouraged but not required.
This classification helps companies quickly determine compliance obligations and plan their development roadmap.
2024 Benchmark Results: 42 Models Tested In 2024, AIEC released its first large-scale benchmark covering 42 models. Small models (under 13B parameters) showed that Taiwan’s locally fine-tuned TAIDE model outperformed Google’s Gemma in Traditional Chinese contexts, proving the value of localized training. In the large-model category, OpenAI’s GPT-5 led in cross-disciplinary reasoning. Google Gemini 2.5 Flash topped the Taiwan Values indicator, demonstrating strong cultural understanding. Foreign models lacking sufficient Traditional Chinese training data consistently scored lower on local values, while some Chinese-origin models performed reasonably well due to knowledge distillation rather than genuine cultural comprehension.
Specialized Tracks for Medical AI and Edge Computing Medical AI evaluation is jointly managed with the Taiwan Food and Drug Administration (TFDA). The 2025 updated guidelines demand Taiwan-specific population data testing and full algorithm explainability. Edge computing tests focus on model compression techniques (quantization, pruning) and protection against physical access or side-channel attacks in low-power IoT devices—critical for Taiwan’s strong hardware manufacturing sector.
Integration of ISO 42001 and NIST AI RMF Technical testing alone is not enough. AIEC requires organizations to build an AI Management System (AIMS) according to ISO/IEC 42001, including clear policies for handling bias or hallucinations, impact assessments, and continuous improvement processes. NIST’s Map-Measure-Manage-Govern functions are translated into automated testing tools, making governance practical and measurable.
Industry Feedback and Real-World Challenges The launch sparked lively discussion in Taiwan’s tech community. Developers worry about cost and time, but AIEC offers free services during trial periods and automated platforms to lower barriers. Early hardware giants expressed concerns about over-regulation, yet most now support the center because global supply chains increasingly demand “trustworthy AI” certification. Technical challenges such as non-determinism in large language models are addressed through confidence scoring and contamination-free test data.
Geopolitical Strategy: Sovereign AI and Taiwan-U.S. Cooperation AIEC is more than a testing lab—it is a strategic asset. Through the U.S.-Taiwan Science and Technology Dialogue and the 21st Century Trade Initiative, Taiwan is building a “common security zone” with America. The government’s Sovereign AI Corpus project supplies high-quality Traditional Chinese data, enabling local models to outperform global giants in government document processing, legal consultation, and cultural content creation.
Practical Advice for Vendors Planning to Submit Models Companies preparing for evaluation should: establish an AIMS early using ISO 42001; physically separate training and test datasets with self-contamination checks; and maintain detailed records of decision logic and loss functions—especially important for high-risk medical and financial applications. Looking ahead, AIEC plans to obtain TAF national accreditation within two years, making its reports internationally recognized, and will expand testing to multimodal models including voice, video, and real-time AI agents.
Conclusion: Building Trust to Drive Innovation Taiwan’s AI Evaluation Center marks the island’s transition from AI adopter to governance leader. In an era of misinformation, algorithmic bias, and cybersecurity threats, trust has become the scarcest and most valuable asset in AI. Through rigorous ten-dimension testing, the pioneering Taiwan Values indicator, and seamless alignment with ISO and NIST, AIEC not only gives local companies a world-class technical check-up but also defines what “Taiwan-made, trustworthy AI” means on the global stage. For international businesses, understanding AIEC is the first step toward entering Taiwan’s market or partnering with its vibrant AI ecosystem.
