Infra-Legalities: Global Security Infrastructures, Artificial Intelligence and International Law

基础法律：全球安全基础设施、人工智能和国际法

基本信息

批准号：
MR/T041552/1
负责人：
Gavin Sullivan
金额：
$ 124.24万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Fellowship
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=MR%2FT041552%2F1
关键词：
Infra Legalities Global Security Infrastructures

项目摘要

Terrorist risks and threats are increasingly identified and countered through new forms of data analytics made possible by rapid advances in machine learning (ML) and artificial intelligence (AI). Private actors, including social media platforms, airlines and financial institutions, now actively collaborate with states and international organisations (IOs) to implement ambitious data-led security projects to support global counterterrorism efforts. The UN Security Council (UNSC) has called on all states to intensify the exchange of information about suspected terrorists by building watchlists and sharing biometric data, using ML to predictively identify 'future terrorists' in advance. Social media platforms are using AI to detect extremist content online and regulate global data flows on an unprecedented scale. Passenger data from the aviation industry is analysed to identify suspicious 'patterns of behaviour' and control the movements of risky travellers. Financial data is mined by banks to spot suspicious transactions and terrorist 'associations'. These changes are all putting new and far-reaching global information infrastructure projects into motion. Yet the implications of these shifts for how international law is practiced, global security threats known and powerful actors held accountable remain uncertain. The data infrastructures underlying global governance have been largely neglected in legal scholarship. And whilst potential problems that AI poses (discrimination and privacy violations) are becoming clearer, solutions remain elusive - especially in the security domain, where secrecy is key and the inner workings of algorithms are 'black-boxed' even more than usual. Regulatory theorists argue that we urgently need to 'expand our frame of rights discourse to encompass our socio-technical architecture' to respond to the accountability challenges of AI (Yeung 2019). Data infrastructures, in other words, might provide the basis for reimagining how information and rights could be reconnected in our digital present. This project rethinks global security law from the 'infrastructure space' it is creating, focusing on (i) countering terrorism online and (ii) controlling the movements of 'risky' individuals. My hypothesis is that the most far-reaching changes to global security governance are not being written in the language of international law, or created through the formal powers of states and IOs, but built through new socio-technical infrastructures and the expertise they are enabling. Data infrastructures are critical for understanding how rights might be extended through AI. I develop the concept of 'infra-legalities' (or, the regulatory effects of data infrastructures) to analyse these shifts and develop a new approach for studying international law and regulation in the age of algorithmic global governance. Infrastructure is usually disregarded as an invisible substrate on which powerful actors act. It is rarely seen as something through which knowledge and governance can be created and shaped. Drawing from Science and Technology Studies, computer science and security studies, this project performs what Bowker and Star (1999) call an 'infrastructural inversion' by mapping the seemingly mundane governance work of data infrastructures in this domain. By 'following the data' - and tracing the socio-technical relations, norms, knowledge practices and power asymmetries that security infrastructures are enacting - a different method of studying global governance can emerge. States, IOs and tech platforms are all calling for the ethical development of AI. Different regulatory approaches are proposed with no consensus on how to mitigate the adverse effects of AI whilst embracing its vast potentialities. Studying the infra-legalities of global security law opens space for addressing these challenges and shaping current policy debates on security, trust and accountability in the age of AI and automation.

通过快速的机器学习（ML）和人工智能（AI）的快速进步，通过新形式的数据分析来确定和抵消恐怖的风险和威胁。包括社交媒体平台，航空公司和金融机构在内的私人参与者现在与州和国际组织（IOS）积极合作，以实施雄心勃勃的数据领导的安全项目，以支持全球反恐努力。联合国安理会（UNSC）呼吁所有州通过建立监视列表并共享生物识别数据来加强有关可疑恐怖分子的信息，并使用ML预测地确定“未来的恐怖分子”。社交媒体平台正在使用AI来在线检测极端主义内容，并以前所未有的规模调节全球数据流。分析了航空业的乘客数据，以确定可疑的“行为模式”并控制风险旅行者的运动。银行开采财务数据，以发现可疑交易和恐怖分子“协会”。这些变化都使新的和深远的全球信息基础架构项目开始了。然而，这些转变对如何实践国际法的含义，已知的全球安全威胁和强大的参与者负责。在法律奖学金中，全球治理基础的数据基础设施在很大程度上被忽略了。尽管AI构成的潜在问题（歧视和侵犯隐私）变得越来越清晰，但解决方案仍然难以捉摸 - 尤其是在安全领域，保密是关键的，并且算法的内部运作比平常更加“黑盒”。监管理论家认为，我们迫切需要“扩展我们的权利框架，以涵盖我们的社会技术建筑”，以应对AI的问责制挑战（Yeung 2019）。换句话说，数据基础架构可能为重新构想如何在我们的数字当前重新连接信息和权利提供基础。该项目从其创建的“基础设施空间”中重新考虑了全球安全法，重点是（i）在线抵抗恐怖主义和（ii）控制“有风险”的人的运动。我的假设是，全球安全治理的最深远的变化不是用国际法的语言写的，也没有通过国家和iOS的正式力量创建，而是通过新的社会技术基础设施及其实现的专业知识而建立的。数据基础架构对于了解如何通过AI扩展权利至关重要。我开发了“基础率”（或数据基础设施的监管效应）的概念，以分析这些转变并开发一种研究算法全球治理时代的国际法和监管的新方法。基础架构通常被视为强大参与者行动的无形基材。它很少被视为可以创建和塑造知识和治理的东西。从科学技术研究，计算机科学与安全研究中，该项目通过绘制该域中数据基础设施看似平凡的治理工作，将Bowker and Star（1999）称为“基础设施倒置”。通过“遵循数据”，并追踪安全基础设施正在制定的社会技术关系，规范，知识实践和权力不对称 - 研究全球治理的另一种方法可能会出现。各州，iOS和技术平台都在呼吁AI的道德发展。提出了不同的监管方法，没有关于如何减轻AI的不良影响的同时，同时接受其巨大潜力的不良影响。研究全球安全法的基础问题为应对这些挑战的空间开辟了空间，并塑造了有关AI和自动化时代的安全，信任和问责制的当前政策辩论。