奥斯陆和平研究所-网络运营中的人工智能：最终用户的道德和法律考虑（英）-2023.5-22页_157kb

AI in Cyber Operations: Ethical and Legal Considerations for End-Users

Introduction

• This chapter examines the principal ethical and legal challenges associated with current and proposed AI uses in cybersecurity and conflict operations.
• Focus is on the impact on the character and capacities of end-users (individuals and teams) implementing AI-enhanced cybersecurity measures.

Background

Artificial Intelligence

• Modular AI (narrow/weak AI): Tailored for specific tasks, currently dominant in cybersecurity (e.g., malware detection, intrusion detection, phishing analysis). Limited to defined environments, potentially unstable in ambiguous situations.
• General AI (strong AI): Falls between modular and general AI. Not yet fully realized.
• AI Vulnerabilities: Susceptible to attacks, failures, and accidents by various threat actors including state actors, criminals, hacktivists, and malicious insiders.

Cyberspace Operations

• AI enhances threat situational awareness, threat detection, and response at speeds exceeding human capabilities, reducing adversary access to networks.
• Divided into three layers (physical, logical, cyberpersona). Operations aim for effects ranging from defense (confidentiality, integrity, availability protection) to offense (manipulating, degrading, destroying adversary systems).
• Expected to comply with international law (e.g., UN Charter, Laws of Armed Conflict, Human Rights Law) and domestic law.

Ethical Considerations

Overarching Ethical Principles

• Drawn from fields like military ethics and engineering ethics.
  1. Transparency: Understandability of AI actions/decisions. Split between weapon developers (TEVV) and end-users (surprise for adversary). Explainable AI techniques.
  2. Justice and Fairness: Avoid implicit bias in databases/learning models.
  3. Non-maleficence: Avoid harm to human beings.
  4. Responsibility: Traceability to a legal person for AI actions/correspondences. Delegation of autonomy raises responsibility concerns.
  5. Privacy: GDPR imposes strict regulations on data collection/use, applicable even to military actors targeting EU citizens. Proliferation risks and reuse potential.
  6. Beneficence: Aim for positive outcomes, minimize harm. AI's role in reducing adversary destructiveness (e.g., shutting down power grids vs. physical destruction).

AI Ethics Guidelines for End-Users

1. Complexity & Uncertainty: Ethical principles must be considered proactively in ROEs prior to conflict, especially regarding speed.
2. Dual User Base: While analyzed for military operators, civilian civilian operators/technicians also have ethical responsibilities.
3. Occupational Ethics: Interface between military ethics (offense/defense tasks/rules) and engineering ethics (design/operation standards, non-maleficence in safety).
4. Transparency Conflict: Engineers need TEVV knowledge; Military needs operational secrecy; Operators need understanding to make informed decisions.

Conclusion

• AI enhances capability but introduces significant complex dilemmas: Accountability, Transparency, Proportionality, Attribution, Collateral Damage, Autonomy Delegation, and Proliferation.
• Ethical concerns must be anticipated and integrated into strategy, ROEs, and operational planning, rather than addressed reactively during conflict.
• Seeks serious discussion on developing responsible AI practices for cybersecurity operations.

## **Key Findings & Translated Key Terms**

AI (人工智慧) 在網路作戰 (網路作戰) 中既帶來效益（如早期偵測、減輕作戰人員負擔、精準攻擊減少破壞），也產生多面向的倫理和法律挑戰。

*   **摘要 (Abstract)**：本章涵蓋 AI 在提升網路安全與衝突作戰效能時涉及的多重主要倫理挑戰。
*   **背景 (Background)**：介紹了模組化 AI（狹義人工智慧）與通用 AI（強義人工智慧）的特性差異，以及 AI 在防守與攻擊性網路作戰 (Cyberspace Operations) 中的應用及潛在風險。
*   **倫理考量 (Ethical Considerations)**：從透明度、正義與公平、非傷害性、責任、隱私、有益性 六個原則探討 AI 利用上的倫理問題。
*   **對終端用戶的 AI 倫理指引 (AI Ethics Guidelines for End-Users)**：強調終端使用者需在軍事倫理與工程倫理之間取得平衡，並理解某些資訊需保密（如武器開發細節），同時也需獲得足夠資訊來進行評估與決策。
*   **結論 (Conclusion)**：AI 增強能力但帶來複雜困境：人工智能化的责任歸屬、透明度、比例原則、歸屬、附带损害、自主權委任、蔓延。倫理考量必須融入戰略與作戰準備，避免臨機應變。

## **Annotation (Note)**

這篇報告提供了對給定英文文件的全面分析和總結。

*   **強調性**: 摘要重點和結論部分加粗，關鍵術語進行了中文翻譯。
*   **結構清晰**: 張貼文(pinn)的標籤用於對應主要部分(guiding)，確保使用者輕鬆瀏覽不同層面的介紹。
*   **語言**: 總體上保持了中性的、信息性的口吻，但摘要部分包含了一些情感色彩，透過強調和問題來表達評論。

如果您需要某一部分的進一步探討，或者想要針對倫理、法律或技術方面的瑩雪進一步提問，我很樂意這樣做。