What kind of human control is necessary for AI applications within national security and defence? Digital ethics and security studies

国家安全和国防领域的人工智能应用需要什么样的人类控制？

• 批准号: 2593677
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2593677
• 关键词: What; kind; human; control; necessary

Artificial intelligence-enabled systems can vary in size, hardware and level of autonomy. The level of autonomy is typically classified according to the expected 'meaningful human control' (MHC) which is a metric reflecting the extent to which humans are required to intervene in a system's interactions with the real world. While the environment and scenarios of use may be relatively predictable in the civil domain, several issues arise from the development and deployment of AI-enabled systems in the security and defence domain. AI-enabled systems suffer from a range of technical limitations, ranging from lack of transparency, limited explicability, and susceptivity to adversarial attacks that create a range of ethical and legal issues -especially in International Humanitarian Law. After an initial review of the literature on Human Control of AI-enabled systems in the security and defence domain, which is heavily focused on Lethal Autonomous Weapons Systems (LAWS), it is clear that the MHC notion dominates the conversations and that existing approaches favour a one-size-fits-all solution to ensuring MHC. To avoid both "overly restrictive" and "overly permissive" approaches to MHC this research proposal seeks to establish the groundwork for a modular control framework that would: 1. Base itself on "unifying grounds" provided by ethical and legal principles. For example, the tenets of International Humanitarian Law, such as military necessity, proportionality, principles of distinction and precaution, serve as a good starting point. 2. Formulate a set of rules that would facilitate the operationalisation of such principles across different tasks and environments. This would include rules to assess the effect of various contexts vis-a-vis the level of autonomy and MHC required. 3. Present a war gaming model for the evaluation, verification and validation of such rules. This would also allow new rules to emerge through the discovery of eventual incompatibilities across certain contexts. Building on the work of the International Panel on Regulation of Autonomous Weapons, this research would analyse MHC across three levels of intervention: Control by design; Control in use; Training. In this framework, while each level of intervention would be addressed separately, they would all support each other. Breaking down AHC in such a way would allow me to identify context-agnostics control components and establish rules for the modification of control components according to the context of deployment. The framework would then establish a set of "if-then" rules that would change the level of autonomy given to AI-enabled systems and adapt MHC components.

支持人工智能的系统可以在大小、硬件和自主水平上有所不同。自主性水平通常根据预期的“有意义的人类控制”（MHC）进行分类，MHC是反映人类需要干预系统与真实的世界交互的程度的度量。虽然民用领域的环境和使用场景可能相对可预测，但在安全和国防领域开发和部署人工智能系统会产生一些问题。人工智能支持的系统受到一系列技术限制，从缺乏透明度，有限的可解释性，到对抗性攻击，这些攻击会产生一系列道德和法律的问题-特别是在国际人道主义法方面。在对安全和防御领域中人工智能系统的人类控制文献进行初步审查后，很明显，MHC概念主导了对话，现有方法有利于确保MHC的一刀切解决方案。为了避免“过度限制”和“过于宽容”的方法来MHC本研究建议旨在建立一个模块化的控制框架，将：1。立足于道德和法律的原则所提供的“统一基础”。例如，国际人道主义法的原则，如军事必要性、相称性、区分原则和预防原则，可以作为一个良好的起点。2.制定一套规则，促进在不同任务和环境中实施这些原则。这将包括评估各种环境相对于所需自主性和MHC水平的影响的规则。3.提出了一个战争游戏模型的评估，验证和确认这些规则。这也将允许通过发现某些情况下的最终不兼容性来产生新的规则。在自主武器管制国际小组工作的基础上，这项研究将分析MHC在三个干预层面的作用：设计控制;使用控制;培训。在这一框架内，虽然每一级的干预措施将分别处理，但它们都将相互支持。以这种方式分解AHC将允许我识别上下文不可知的控制组件，并根据部署的上下文建立修改控制组件的规则。然后，该框架将建立一套“如果-那么”规则，这些规则将改变赋予AI系统的自主权水平，并调整MHC组件。