Taiwan AI Compliance Requirements
Mandatory and recommended controls under EU AI Act + national rules, including the role of the local data-protection authority.
How AI law works in Taiwan
Taiwan's AI Basic Act (人工智慧基本法) was promulgated on 14 January 2026 and, under its own Article 20, took effect that same day. It is a framework statute rather than a compliance regime: 20 articles that bind the STATE rather than private deployers. Article 2 makes the National Science and Technology Council the central competent authority, with municipal and county governments competent locally, and leaves sector-specific matters to each sector regulator. Article 3 gives Taiwan a statutory definition of artificial intelligence — a system capable of autonomous operation which, through input or sensing and by means of machine learning and algorithms, produces predictions, content, recommendations or decisions that affect physical or virtual environments. Article 4 binds government AI policy to seven principles: sustainable development and well-being, human autonomy, privacy protection and data governance, security, transparency and explainability, fairness and non-discrimination, and accountability. Risk classification is delegated rather than set in the Act. Businesses should note what this Act does NOT do: it creates no offence, no regulator-imposed obligation on private AI deployers and no penalty of any kind — verified against all 20 articles, none of which contains a fine, penalty, criminal or sanction provision. Binding exposure in Taiwan therefore still runs through the Personal Data Protection Act and sector rules, with the delegated risk framework expected from the Ministry of Digital Affairs.
Applicable laws
- 📜 Artificial Intelligence Basic Act (人工智慧基本法) — promulgated 14 January 2026
EU AI Act requirements begin with system risk assessment. Your organization must evaluate every AI system against the EU AI Act's risk framework: prohibited systems (facial recognition in law enforcement, social credit scoring, subliminal manipulation), high-risk systems (hiring, benefits determination, law enforcement, biometric ID), limited-risk systems (chatbots), and minimal-risk systems (game AI, spam filters). The legal requirement is to classify your system correctly. Misclassification — for example, claiming that a hiring AI is minimal-risk when it is high-risk — is itself a compliance violation. High-risk classification triggers the heaviest compliance burden: conformity assessment, bias and fairness testing, documented risk mitigation, human oversight, transparency, and record-keeping. If you are uncertain whether a system is high-risk, the safe assumption is to treat it as high-risk and apply the full compliance framework.
Pre-deployment conformity assessment is the core requirement for high-risk systems. Before deploying a high-risk AI system (or immediately, if it is already deployed), you must complete a documented assessment covering: data quality — are the training and decision-making data representative of the population affected by the system, and do they contain known biases?; model performance — does the model perform equally well across demographic groups, or is accuracy lower for protected groups?; system explainability — can you explain to an affected individual why the system made a particular decision?; human oversight design — what process allows an individual to escalate the AI decision to human review?; and risk mitigation — what controls have you implemented to reduce the risk of discriminatory outcomes? This assessment must be documented in writing, reviewed by qualified personnel, and updated at least annually.
Bias and fairness testing is a specific requirement for high-risk systems. The EU AI Act does not prescribe a particular testing methodology, but requires that your organization conduct documented testing and be able to demonstrate that you have evaluated the system for discriminatory impact across protected characteristics (race, color, religion, national origin, sex, gender identity, sexual orientation, disability, age, etc.). Testing must include: hold-out test data not used in training, representative of the affected population; evaluation of decision-rate parity across groups (does the AI approve loans at the same rate for all genders, races, and age groups?); and performance parity testing (does the AI make accurate predictions equally well across all groups?). Document test results, identify any disparate impact, and implement mitigation (rebalance training data, adjust decision thresholds, redesign features, or limit the system's scope).
Transparency and human-rights mechanisms are mandatory for all systems, with intensity scaling to risk level. For limited-risk systems (chatbots), you must disclose that the individual is interacting with AI. For high-risk systems, transparency is much deeper: you must inform affected individuals before the AI system makes a decision about them, explain what data the system is using, describe how the system works (at a non-technical level accessible to the individual), and provide the individual with a clear, accessible process to request human review and appeal the AI decision. In employment and benefits contexts, individuals must be able to request re-evaluation by a human reviewer, and that human review must be genuine — a human who has authority to override the AI decision and the information needed to make an independent judgment.
Ongoing monitoring, record-keeping, and individual-rights response are permanent obligations. You must monitor every high-risk AI system's performance and decisions on an ongoing basis (not just at deployment). Maintain audit logs of every high-risk decision for at least three years, capturing inputs, decision outputs, confidence scores, human-review flags, and any human override. When an individual requests an explanation of an AI decision, you must respond within 30 days with accessible, non-technical information about how the system works and why it made that particular decision. When an individual requests appeal or human review, you must provide it. Failure to respond to individual rights requests is a documented compliance violation and a source of private civil liability.
Taiwan compliance requirements, ranked
Mandatory under EU AI Act + GDPR
Strongly recommended
Country context
More Taiwan resources
Other countries
Anchored to the primary government source (statute, bill text, or agency rule) and verified directly against it · Last verified Aug 31, 2026. See our methodology.
- ↗law.moj.gov.twhttps://law.moj.gov.tw/LawClass/LawAll.aspx?pcode=H0160093
- ↗law.moj.gov.twhttps://law.moj.gov.tw/ENG/LawClass/LawAll.aspx?pcode=H0160093