2026/01/27 星期二

UN Policy Chapter AI-Enabled Economic Governance and the Internalization of Life Costs

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日期:2026/01/14   IAE 

UN Policy Chapter

AI-Enabled Economic Governance and the Internalization of Life Costs

Reframing Profit, Growth, and Sustainability in the AI Era

Prepared for
United Nations System
(Economic Governance, AI Policy, Sustainable Development)

Author
Frank Chen（陳俊吉）
Founder, Global Charity Economicism
GCWPA × IAE Global

UN Policy Chapter｜AI × 經濟治理 × 生命成本（正式定稿版）。
已完全對齊 UN Policy Chapter 的語體與結構（中性、制度導向、可治理、可被多機構引用），可直接納入：

  • UN Policy White Paper（主文章節）

  • UNDP / DESA / UNEP / ECOSOC 專題報告

  • AI Governance × Sustainable Development 跨機構文件

  • ✔ UN-compatible policy language

  • ✔ Integrates AI, economics, and life value governance

  • ✔ Suitable for main chapter or thematic annex

  • ✔ Aligned with SDGs and prior UN policy frameworks

1. Policy Background

Artificial intelligence and big data technologies are rapidly transforming economic governance. Governments and markets now possess unprecedented capacity to measure, predict, and optimize economic activity. However, most AI-enabled economic systems remain optimized around price efficiency and profit maximization, rather than life preservation and social sustainability.

This chapter addresses a critical policy gap:
the systematic exclusion of life-related and social costs from economic decision-making, even in AI-augmented governance frameworks.

2. The Concept of Life Cost in Economic Governance

For policy purposes, Life Cost refers to:

The measurable loss or degradation of life, health, mental well-being, environmental integrity, and intergenerational sustainability resulting from economic activity.

Life costs include, but are not limited to:

  • Public health deterioration and medical burden

  • Occupational health and mental stress impacts

  • Environmental degradation affecting survival conditions

  • Long-term intergenerational risks

These costs are real, cumulative, and fiscally externalized when not accounted for in governance systems.

3. Structural Limitations of Traditional Economic Models

Traditional economic governance is based on models in which demand and profit are derived from price variables:

 

 

Q=F(P),P=AR=MR=MCQ = F(P), \quad P = AR = MR = MC

While analytically efficient, this framework systematically omits life costs, leading to:

  • Profit calculations detached from human and ecological impact

  • Social and environmental costs shifted to the public sector

  • Long-term fiscal instability masked by short-term gains

Over time, this creates a structural divergence between economic performance indicators and civilizational sustainability.

4. Why AI Changes the Policy Equation

AI and big data fundamentally alter the feasibility of economic governance:

  • Life, health, and environmental impacts can now be measured with high precision

  • Complex externalities can be modeled, forecasted, and priced

  • Policy simulations can test outcomes before implementation

Accordingly, the continued exclusion of life costs is no longer a technical limitation, but a governance choice.

5. AI-Enabled Internalization of Life Costs

This chapter proposes that AI be explicitly used to internalize life costs within economic governance frameworks.

Key mechanisms include:

  1. Life Cost Accounting Systems

    • AI-based estimation of health, environmental, and social impacts

  2. Dynamic Life Cost Adjustment

    • Real-time updating of cost coefficients as conditions change

  3. Policy-Linked Cost Signals

    • Translating life costs into fiscal, regulatory, or pricing instruments

These mechanisms enable governance systems to move beyond abstract averages toward real-world life impact measurement.

6. Reframing Profit in the AI Era

Under life-cost-aware governance, profit is redefined as:

Economic surplus remaining after the full internalization of life, social, and environmental costs.

This reframing does not eliminate profit, but restores its legitimacy by aligning private gain with public sustainability.

7. Implications for Economic Policy Instruments

AI-enabled life cost internalization can be operationalized through:

  • Environmental and life-value-based taxation

  • Health and safety cost adjustments

  • Preventive investment incentives

  • Intergenerational sustainability charges

These instruments shift governance from post-damage remediation to pre-damage prevention.

8. Alignment with UN Sustainable Development Goals

Life-cost-aware economic governance directly supports:

  • SDG 3 – Good Health and Well-Being

  • SDG 8 – Decent Work and Sustainable Growth

  • SDG 12 – Responsible Consumption and Production

  • SDG 13 – Climate Action

  • SDG 16 – Effective, Accountable Institutions

By internalizing life costs, AI governance strengthens policy coherence across SDGs.

9. Governance Safeguards and Ethical Considerations

To ensure legitimacy, AI-based life cost systems require:

  • Transparency in algorithms and data sources

  • Protection of individual rights and privacy

  • Clear separation between measurement and enforcement

  • Multistakeholder oversight

Life cost internalization must enhance human dignity, not replace human judgment.

10. Policy Conclusion

In the AI era, ignoring life costs is no longer an economic necessity but a governance failure.

By leveraging AI to internalize life costs, economic governance can reconcile efficiency with humanity, profit with survival, and growth with civilizational continuity.

This approach offers the United Nations system a practical pathway to align AI-enabled economic governance with the preservation of life and the sustainability of civilization.