Unlocking the Potential of AI for English Law

释放人工智能在英国法律中的潜力

• 批准号: ES/S010424/1
• 负责人: John Armour
• 金额: $ 168.48万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FS010424%2F1
• 关键词: Unlocking; Potential; AI; English; Law

The proposed research will explore the potential and limitations of using artificial intelligence (AI) in support of legal services. AI's capabilities have made enormous recent leaps; many expect it to transform how the economy operates. In particular, activities relying on human knowledge to create value, insulated until now from mechanisation, are facing dramatic change. Amongst these are professional services, such as law.Like other professions, legal services contribute to the economy both through revenues of service providers and through benefits provided to clients. For large business clients, who can choose which legal regime will govern their affairs, UK legal services are an export good. For small businesses and citizens, working within the domestic legal system, UK legal services affect costs directly. Yet unlike other professions, the legal system has a dual role in society. Beyond the law's role in governing economic order, the legal system is more fundamentally a structure for social order. It sets out rules agreed on by society, and also the limits of politicians' ability to enact these rules. Consequently, the stakes for AI's implementation in UK legal services are high. If mishandled, it could threaten both economic success and governance more generally. Yet if executed effectively, it is an opportunity to improve legal services not only for export but also for citizens and domestic small businesses. Our research seeks to identify how constraints on the implementation of AI in legal services can be relaxed to unlock its potential for good. One major challenge is the need for 'complementary' adjustments. Adopting a disruptive new technology like AI requires changes in skills, training, and working practices, without which the productivity gains will be muted. We will investigate training and educational needs for lawyers' engagement with technology and programmers' engagement with law. With private sector partners, we will develop education and training packages that respond to these needs for delivery by both universities and private-sector firms. We will investigate emerging business models deploying AI in law, and identify best practice in governance and strategy. Finally, we will compare skills training and technology transfer in the UK with countries such as the US, Hong Kong and Singapore, and ask what UK policymakers can learn from these competitors. To the extent that these issues are also faced by other high-value professional services, these parts of our results will also have relevance for them.However, the dual role of the legal system poses unique challenges that justify a research package focusing primarily on this sector. There are constitutional limits to how far law's operation can be adjusted for economic reasons: we term this second constraint 'legitimacy'. We will map how automation in dispute resolution might trigger constitutional legal challenges, how these challenges relate to types of dispute resolution technology and types of claim, and use the resulting matrix to identify opportunities for maximum benefit from automation in dispute resolution. A third constraint is the limits of technological possibility. AI systems rely on machine learning, which reaches answers by identifying patterns in very large amounts of data. Its limitations are the size of the datasets needed, and its inability to provide an explanation for how the answer was reached. This poses particular difficulties for law, where many applications require or benefit from reasons being given. We will explore the possibility for frontier AI technologies to deliver legal reasoning. The research will involve a mix of disciplinary inputs, reflecting the multi-faceted nature of the problem: Law, Computer Science, Economics, Education, Management and Political Economy. Working closely with private-sector partners will ensure our research benefits from insights into, and testing against, real requirements.

拟议的研究将探索使用人工智能（AI）支持法律的服务的潜力和局限性。人工智能的能力最近取得了巨大的飞跃;许多人预计它将改变经济的运作方式。特别是，依靠人类知识创造价值的活动，迄今为止与机械化绝缘，正面临着巨大的变化。其中包括法律等专业服务，与其他专业一样，法律的服务通过服务提供者的收入和向客户提供的利益对经济作出贡献。对于大企业客户来说，他们可以选择哪种法律的制度来管理他们的事务，英国的法律的服务是一种出口商品。对于在国内法律的体系内工作的小企业和公民来说，英国的法律的服务直接影响成本。然而，与其他职业不同的是，法律的系统在社会中具有双重作用。除了法律在管理经济秩序方面的作用之外，法律的体系更根本地是社会秩序的结构。它规定了社会商定的规则，也规定了政治家制定这些规则的能力限度。因此，在英国法律的服务中实施人工智能的风险很高。如果处理不当，它可能威胁到经济成功和更广泛的治理。然而，如果得到有效执行，这是一个改善法律的服务的机会，不仅对出口，而且对公民和国内小企业。我们的研究旨在确定如何放宽对人工智能在法律的服务中实施的限制，以释放其良好的潜力。一个主要的挑战是需要进行“补充性”调整。采用像人工智能这样的颠覆性新技术需要改变技能、培训和工作实践，否则生产力的提高将被抑制。我们将调查律师参与技术和程序员参与法律的培训和教育需求。我们将与私营部门合作伙伴一起，制定教育和培训一揽子计划，以满足大学和私营部门公司的这些需求。我们将研究在法律中部署人工智能的新兴商业模式，并确定治理和战略的最佳实践。最后，我们将比较英国与美国、香港和新加坡等国家的技能培训和技术转让，并询问英国政策制定者可以从这些竞争对手那里学到什么。在某种程度上，这些问题也面临着其他高价值的专业服务，我们的结果的这些部分也将与他们相关。然而，法律的系统的双重作用构成了独特的挑战，证明了一个研究包主要集中在这个部门。法律的运作在多大程度上可以因经济原因而调整，这是有宪法限制的：我们称第二种限制为“合法性”。我们将绘制争议解决自动化如何引发宪法法律的挑战，这些挑战如何与争议解决技术类型和索赔类型相关，并使用由此产生的矩阵来确定从争议解决自动化中获得最大利益的机会。第三个限制是技术可能性的限制。人工智能系统依赖于机器学习，它通过识别大量数据中的模式来获得答案。它的局限性是所需数据集的大小，以及它无法解释如何得出答案。这给法律带来了特别的困难，因为许多申请都要求提供理由，或从提供理由中获益。我们将探索前沿人工智能技术提供法律的推理的可能性。该研究将涉及学科投入的混合，反映了问题的多方面性质：法律，计算机科学，经济学，教育，管理和政治经济学。与私营部门合作伙伴密切合作将确保我们的研究受益于对真实的要求的洞察和测试。

项目成果

Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting

• DOI: 10.1609/aaai.v34i04.5705
• 发表时间: 2019-04
• 作者: Ralph Abboud;I. Ceylan;Thomas Lukasiewicz

Self-Driving Corporations?

自动驾驶公司？

• 发表时间: 2020
• 期刊: Harvard Business Law Review
• 作者: Armour, J

Online tribunal judgments and the limits of open justice

网上法庭判决和公开司法的局限性

• DOI: 10.1017/lst.2021.30
• 发表时间: 2021
• 期刊: Legal Studies
• 影响因子: 0.7
• 作者: Adams Z

Unlocking the potential of AI for English law

释放人工智能在英国法律中的潜力

• DOI: 10.1080/09695958.2020.1857765
• 发表时间: 2020
• 期刊: International Journal of the Legal Profession
• 影响因子: 0.6
• 作者: Armour J

AI-enabled business models in legal services: from traditional law firms to next-generation law companies?

• DOI: 10.1093/jpo/joaa001
• 发表时间: 2020-03-01
• 期刊: JOURNAL OF PROFESSIONS AND ORGANIZATION
• 影响因子: 2.2
• 作者: Armour, John;Sako, Mari
• 通讯作者: Sako, Mari