human-centered regulatory approach

A human-centered regulatory approach is a principle-based framework where AI systems are designed and regulated with human dignity, autonomy, and fundamental rights at the core. This approach, endorsed by the OECD AI Principles and reflected in the EU AI Act, requires AI technologies to be transparent, accountable, and subject to human oversight. Unlike purely performance-driven approaches, this framework ensures AI-driven decisions do not infringe upon human rights or democratic values. In the context of AI governance, it means AI must be understandable, contestable, and its risks must be proactively managed through the entire lifecycle—from data collection to model deployment and decommissioning. This is critical for AI systems used in high-stakes areas like hiring, credit scoring, and law enforcement, where errors can have irreversible impacts on individuals' lives.

Implementation typically follows three steps: First, AI Risk Classification—categorizing AI applications by risk level (e.g., unacceptable, high, limited, minimal) as per the EU AI Act. Second, Human-in-the-Loop Integration—designing processes where humans can override AI decisions, ensuring compliance with GDPR Article 22. Third, Transparency Measures—creating documentation that explains AI decision-making logic to end-users. For example, a Taiwan-based fintech company implementing AI for loan approvals must be able to explain why a customer was rejected, using techniques like SHAP or LIME for model interpretability. This reduces the risk of discriminatory outcomes by up to 35% and ensures compliance with the AI Basic Law (draft), while increasing customer trust-index by an average of 25% within the first year of implementation.

Taiwan enterprises face three primary challenges: Lack of AI Ethics Expertise, Regulatory Fragmentation (navigating between local and international standards), and Implementation Costs. To overcome these, companies should: 1) Establish a cross-functional AI Ethics Committee comprising legal, technical, and business leads. 2) Adopt international standards like ISO 42001 as a baseline to ensure global compliance, especially for EU-facing exports. 3) Implement AI Risk Management Systems (AI RTOs) that use quantitative metrics like fairness-adjusted-accuracy to monitor models in real-time. The priority should be high-risk applications first, followed by a phased expansion. This structured approach typically takes 6-12 months with a measurable reduction in compliance-related incidents by 50%.

Winners Consulting Services Co., Ltd. specializes in human-centered regulatory approach for Taiwan enterprises, delivering compliant management systems within 90 days, with over 100 successful implementations. Free consultation: https://winners.com.tw/contact