Taiwan Artificial Intelligence Basic Act: A Statutory Framework for Human-Centerd AI Governance

Introduction 

In early 2025, while the world watched Silicon Valley's AI arms race intensify, Taiwan took a different path. On 8 January 2026, President Lai Ching-te signed Presidential Order Hua-Zong-Yi-Yi-Zi No. 11400001461, promulgating the Artificial Intelligence Basic Act, Taiwan's first comprehensive legal framework for AI governance. The Act came into force on 14 January 2026, marking Taiwan's commitment to shaping AI development through principles-first, human-centred governance rather than reactive regulation. 

What makes Taiwan's approach distinctive? Unlike the EU's AI Act with its hundreds of pages of prescriptive rules, Taiwan's Act serves as a Basic Act, a constitutional framework for AI rather than a rulebook. It establishes guiding principles, designates responsibilities, and sets timelines for sector-specific regulators to develop detailed rules. 

Article 1 captures the ambition: "to build a smart nation; promote human-centered AI research and industrial advancement; construct a safe environment for AI applications; realize digital equity; protect fundamental rights; and elevate international competitiveness, while ensuring technological applications comply with social ethics." Taiwan's phased, principle-driven approach offers a middle path between Europe's prescriptive regulation and America's hands-off stance. 

Who's in Charge? Governance Structure 

Article 2 gives responsibility to the National Science and Technology Council (NSTC) at the central government level, with local governments handling day-to-day enforcement. But AI touches everything, Healthcare diagnostics, financial credit scoring, hiring algorithms, autonomous vehicles. So Article 2 delegates sector-specific matters to relevant industry regulators. The Ministry of Health handles medical AI, the Financial Supervisory Commission oversees lending algorithms, and so on. 

This distributed model avoids bottlenecks and ensures domain expertise shapes the rules. But how do you ensure consistency? That's where the guiding principles come in. 

What Exactly Is AI? The Statutory Definition 

Article 3 provides Taiwan's statutory definition, aligned with international standards: 

"The term 'artificial intelligence' refers to a system with the capacity for autonomous operation, which, through input or sensing and via machine learning and algorithms, can generate outputs such as predictions, content, recommendations, or decisions that influence physical or virtual environments." 

This definition draws from the US National AI Initiative Act, ISO/IEC 42001:2023, NIST's AI Risk Management Framework, and the EU AI Act. A recruitment tool using machine learning to rank candidates? That's AI. A generative model creating content? AI. A fraud detection system making real-time credit decisions? Definitely AI. 

Seven Guiding Principles: The North Star 

Article 4 establishes seven core principles that government must observe when promoting AI. Think of these as the North Star no matter which sector you're in, these principles guide the journey. 

1. Sustainable Development and Well-Being – Balance social fairness with environmental sustainability. Provide education to reduce digital divides, ensuring people can adapt as AI transforms work. 

2. Human Autonomy – Support human decision-making authority. Respect personality rights including name, portrait, and voice. Allow human oversight of automated decisions. High-stakes decisions like parole can't be fully automated without meaningful human review. 

3. Privacy Protection and Data Governance – Protect personal data privacy, prevent breaches, adopt data minimization, collect only what you need, keep it only as long as necessary. 

4. Cybersecurity and Safety – Design systems with security in mind. Establish cybersecurity measures preventing threats and attacks, ensuring system robustness. 

5. Transparency and Explainability – AI outputs must be appropriately disclosed or labeled. If an AI system denies your loan, you should understand why. 

6. Fairness and Non-Discrimination – Avoid algorithmic bias. AI shouldn't produce discriminatory outcomes against specific groups. 

7. Accountability – When things go wrong, someone must be responsible. You can't hide behind "the algorithm decided." 

These principles derive from the G7 Hiroshima Process, OECD AI Recommendation (2019), EU Ethics Guidelines for Trustworthy AI (2019), and Singapore's Model AI Governance Framework (2024). Taiwan is building on global consensus. 

What's Prohibited? High-Risk Applications 

Article 5 draws red lines. The government must prevent AI applications from: 

• Infringing upon people's life, body, freedom, or property 

  
  

• Undermining social order, national security, or ecological environment 

  
  

• Engaging in bias, discrimination, false advertising, or disseminating disinformation 

For AI products designated as high-risk, determined by sector authorities consulting with the Ministry of Digital Affairs (MODA), ear warnings must be displayed. This is like warning labels on cigarettes, alerting users that this AI system could significantly impact their rights or safety. The principle of best interests of the child guides these determinations. 

MODA must provide assessment and verification tools to help evaluate whether systems qualify as high-risk, developed consulting interest groups, industry, scholars, and legal experts. 

Coordination at the Top: National AI Strategic Committee 

Article 6 creates the National AI Strategic Committee, convened by the Premier and composed of scholars, experts, industry representatives, ministers, agency heads, and local leaders. This Committee coordinates national AI affairs and formulates the National AI Development Guidelines, Taiwan's national strategy. It meets at least annually, with ad-hoc meetings for emergencies. 

Why create another committee? Because AI governance requires breaking down silos. The Strategic Committee ensures finance regulators talk to healthcare regulators, and that industry voices inform policy without capturing it. 

Building the Ecosystem: Education, Budget, Innovation 

Articles 7-11 focus on building Taiwan's AI ecosystem—not just regulating what exists, but actively promoting beneficial development. 

Article 7 mandates continuous AI and ethics education across schools, industries, and public agencies, cultivating digital literacy. 

Article 9 requires governments to allocate generous budgets within their financial capacity. 

Article 10 specifies support mechanisms: subsidies, investments, incentives, tax and financial measures. An annual performance report system must publicly announce results, taxpayers deserve to know if investments deliver value. 

Article 11 encourages experimentation through innovation sandboxes, controlled environments where companies can test AI with regulatory flexibility. When regulations conflict, promoting new technologies takes precedence, consistent with Article 4 principles. This is Taiwan's bet: enable innovation within guardrails rather than stifle it. 

Data Governance: Opening, Sharing, Protecting 

Article 13 requires establishing mechanisms for data opening, sharing, and reuse to enhance data usability, regularly reviewing laws. The government must improve data quality and quantity while ensuring outputs represent Taiwan's diverse cultural values and protect intellectual property. 

Article 14 drills into personal data. Sector authorities must avoid unnecessary data collection and promote personal data protection by design and by default. 

GoTrust's data discovery platform addresses Article 14 by discovering and classifying personal data across systems, tagging sensitive attributes introducing bias, automating data minimization workflows, and maintaining audit-ready evidence of privacy-by-design. 

Protecting Workers: Labor Rights 

Article 15 confronts a hard truth: AI will displace some jobs. Taiwan's Act requires government to bridge skills gaps, enhance labour participation, ensure economic security, implement decent work principles, and provide employment counselling to those unemployed due to AI. Good governance means ensuring the transition is just. 

The Framework That Matters: Risk Classification 

Article 16 is arguably the Act's most consequential provision. MODA shall, referencing international standards like NIST, promote an AI risk classification framework interoperable with international frameworks, and assist sector authorities in establishing risk-based management regulations. 

Once MODA publishes the risk classification framework (expected mid-2026), sector authorities will use it to establish regulations for their industries. High-risk AI gets more scrutiny, testing, documentation. Lower-risk systems face lighter requirements. Sector authorities must assist industries in formulating industry guidelines and codes of conduct. For prohibited applications under Article 5, authorities must restrict or ban them. 

When Things Go Wrong: Liability and Remedies 

Article 17 tackles liability for high-risk AI. The government must clarify liability attribution and conditions, and establish remedy, compensation, or insurance mechanisms. 

These provisions don't apply to AI R&D before actual deployment, protecting academic research. However, once you're testing in real-world environments or providing products or services, liability attaches. This balances protecting research freedom with holding deployers accountable. 

The Clock Is Ticking: Implementation Deadlines 

Article 18 gives everyone two years. If existing laws are inconsistent or if no regulations exist, enactment, amendment, or repeal must be completed by 14 January 2028. 

The Legislative Yuan's Supplementary Resolutions set specific deadlines as set forth in the below table: :

These aren't suggestions, they're statutory deadlines. The clock started in January 2026. 

Article 19 applies these principles to government itself. When using AI to perform duties or provide services, agencies must conduct risk assessments, plan risk response measures, and establish usage regulations or internal controls. Government must practice what it preaches. 

Making Compliance Operational: GoTrust's Platform 

Statutory principles mean nothing without operational implementation. GoTrust's AI governance platform bridges the gap between legal obligation and organizational reality. 

1. Centralised AI Inventory (Articles 4, 16, 19): GoTrust provides a centralised inventory logging every AI use case, purpose, deployment context, and risk category. When MODA publishes its Article 16 framework, organisations can immediately map systems to regulatory tiers, identify which need Article 5 warnings, and prioritize remediation. 

   
   

2. Privacy-by-Design Automation (Article 14): GoTrust's data discovery performs PII discovery and data quality audits across databases, cloud storage, and SaaS platforms. It identifies sensitive attributes introducing bias, supporting Article 4's fairness principle and Article 14's data minimization. 

   
   

3. AI Impact Assessments (Articles 5, 17, 19): GoTrust's ISO 42001-aligned platform automates AIAs, DPIAs, and Ethical Reviews through pre-built templates. Auto-scoring tracks risk evaluation, maintaining audit-ready documentation for Article 17's liability attribution and Article 19's risk assessment mandate. 

   
   

4. Vendor Risk Management (Articles 4, 7, 17): Most organizations buy AI systems rather than build them. GoTrust's vendor risk management tracks third-party AI compliance, captures model declarations, and documents risk assurances. As sector regulators clarify Article 17 liability, this documentation demonstrates Article 4's accountability principle. 

Conclusion:  

Taiwan's Artificial Intelligence Basic Act represents principles-first legislation that balances enabling innovation with protecting fundamental rights. By establishing clear legislative purposes, defining AI, codifying seven guiding principles, designating competent authorities, and mandating risk frameworks within defined timelines, Taiwan created a foundation that can evolve as AI technology matures. 

For organizations operating across Asia-Pacific, the Act previews how other jurisdictions may approach AI regulation: principle-anchored, risk-based, sector-specific, and implementation-flexible. The strategy is proactive governance today, building automated inventories aligned with Article 16's coming risk framework, implementing privacy-by-design mechanisms satisfying Article 14, conducting impact assessments meeting Articles 5 and 17, maintaining audit-ready documentation, to scale compliance as Taiwan's sector-specific regulations crystallize through 2028. 

GoTrust's AI governance platform transforms the Act's statutory principles from abstract legal obligations into operational reality. It enables organizations to demonstrate responsible AI development before regulatory enforcement begins, building governance infrastructure that serves as the bridge between innovation and accountability. 

In a world where AI regulation is inevitable but specific rules remain uncertain, Taiwan's model offers a third way: not the EU's prescriptive approach, not America's laissez-faire stance, but a principles-driven framework that guides without stifling. For organizations committed to responsible AI, aligning with these principles isn't just regulatory compliance, it's good governance and good business.