AI入门

爱如火

Reading Notes: Chapter 5
Reading Time: 5 hours
Reading Task: Chapter 5 (pp. 136–175)
 

Summary
This chapter delves into emerging paradigms for global AI governance, focusing on participatory ethics, sovereignty conflicts, and adaptive regulatory frameworks. It builds on the tensions outlined in Chapter 4, proposing actionable solutions while critiquing existing models:

Participatory Ethics in Practice
Multi-Stakeholder Governance: The chapter introduces case studies like UNESCO’s Recommendation on AI Ethics (2021) and the EU-U.S. AI Code of Conduct (2023), emphasizing cross-sector collaboration among governments, corporations, and civil society.
Ethical Sandboxes: Pilot projects in Singapore and Canada test dynamic ethical adjustments, such as bias-correction algorithms in hiring AI, demonstrating how localized ethics can scale globally.
Grassroots Input: Examples include Kenya’s crowdsourced AI guidelines for agricultural drones, highlighting the integration of indigenous knowledge into ethical frameworks.

Sovereignty vs. Interoperability
“Ethical Sovereignty” Debates: Nations like China and the EU prioritize divergent values—China’s AI Governance Principles (2023) emphasize collective security, while the EU’s AI Act prioritizes individual rights. This clash complicates cross-border data flows, as seen in GDPR-compliance disputes with African health-tech platforms.
Neocolonial Risks: The chapter critiques “AI aid” programs by tech giants in developing nations, where data extraction often bypasses local consent frameworks, exacerbating digital dependency.

Adaptive Regulatory Mechanisms
Dynamic Compliance Tools: South Korea’s AI Impact Assessment System (2024) mandates real-time audits of public-sector AI, linking ethical performance to funding.
Quantum Ethics: The rise of quantum computing introduces new vulnerabilities, such as breaking existing encryption standards. Proposals for post-quantum privacy protocols aim to preemptively address these risks.

Labor and Autonomy Revisited
Agorithmic Coercion: Case studies on gig-economy platforms (e.g., Southeast Asia’s ride-hailing apps) reveal how predictive scheduling algorithms erode worker autonomy, prompting calls for algorithmic transparency mandates.
UBI Experiments: Finland’s AI-Driven Universal Basic Income Pilot (2024) tests fiscal policies to counter job displacement, though critics argue it risks legitimizing corporate evasion of labor responsibilities.
 

Critique

Narrative Strengths
Concrete Solutions: The chapter excels in bridging theory and practice, such as detailing Kenya’s participatory model and South Korea’s audit system.
Interdisciplinary Synthesis: It effectively connects quantum computing’s technical risks with Heideggerian critiques of technological enframing, though this linkage remains underdeveloped.

Theoretical Contributions
“Ethical Friction” Concept: Measures the resistance between global standards (e.g., GDPR) and local practices, quantified in delays (e.g., 6–18 months for compliance in Global South nations).
Critique of “Ethical Washing”: Exposes how corporations like Meta use ethics boards as PR tools while lobbying against stricter regulations.

Weaknesses
Overlooking Religious Frameworks: While addressing cultural diversity, the chapter neglects faith-based ethics, such as Islamic finance’s prohibition of AI-driven interest calculations.
Incomplete Tech Justice: Proposals for data reparations (e.g., taxing AI profits to fund Global South infrastructure) lack enforcement mechanisms.
 

Reflections

Policy Innovations
Global Ethics Tribunal: Inspired by the International Criminal Court, this body could adjudicate transboundary AI harms, though power imbalances (e.g., U.S.-China rivalry) pose implementation hurdles.
Open-Source Ethics Toolkits: Platforms like EthicsHub (launched by MIT in 2024) offer modular guidelines for SMEs, though adoption rates remain low in non-English-speaking regions.

Educational Reforms
Decolonial AI Curricula: Universities in Brazil and India now teach AI Ethics Through Indigenous Epistemologies, challenging Western-centric models.
Citizen Juries: Germany’s Public AI Audits (2025) involve laypersons in evaluating municipal surveillance systems, fostering democratic oversight.

Corporate Accountability

Algorithmic Impact Bonds: Proposed financial instruments tie corporate loans to ethical KPIs, penalizing violations with higher interest rates.
Whistleblower Protections: The chapter advocates for legal safeguards akin to GDPR’s Right to Explanation, enabling employees to expose unethical AI without retaliation.