Unlocking the Potential of AI for English Law

拟议的研究将探讨使用人工智能（AI）支持法律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行方式。特别是依靠人类知识创造价值的活动，迄今为止与机械化隔绝，正面临着巨大的变化。其中包括专业服务，如法律。像其他职业一样，法律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。对于大型企业客户来说，英国的法律服务是一种出口商品，他们可以选择哪种法律制度来管理自己的事务。对于在国内法律体系内工作的小企业和公民来说，英国的法律服务直接影响到成本。然而，与其他职业不同的是，法律体系在社会中扮演着双重角色。除了法律在治理经济秩序方面的作用之外，法律制度从根本上说是一种社会秩序的结构。它列出了社会认同的规则，以及政治家制定这些规则的能力限制。因此，人工智能在英国法律服务领域的应用风险很高。如果处理不当，它可能会威胁到经济成功和更广泛的治理。然而，如果执行得当，不仅是为出口，而且是为公民和国内小企业改善法律服务的机会。我们的研究旨在确定如何放宽在法律服务中实施人工智能的限制，以释放其潜力。一个主要挑战是需要进行“补充性”调整。采用像人工智能这样的颠覆性新技术需要在技能、培训和工作实践方面做出改变，否则生产力的提高将会被抵消。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，制定满足这些需求的教育和培训方案，由大学和私营企业提供。我们将研究在法律中部署人工智能的新兴商业模式，并确定治理和战略方面的最佳实践。最后，我们将把英国的技能培训和技术转移与美国、香港和新加坡等国家进行比较，并询问英国的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，法律体系的双重作用带来了独特的挑战，证明了主要关注这一领域的一揽子研究计划是合理的。由于经济原因，法律的运作可以调整到什么程度，这是宪法上的限制：我们把这第二个限制称为“合法性”。我们将绘制争议解决自动化如何引发宪法法律挑战，这些挑战与争议解决技术类型和索赔类型之间的关系，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。第三个制约因素是技术可能性的局限性。人工智能系统依赖于机器学习，通过识别大量数据中的模式来获得答案。它的局限性在于所需数据集的大小，以及它无法解释答案是如何得到的。这给法律带来了特别的困难，因为许多申请需要或受益于给出的理由。我们将探索前沿人工智能技术提供法律推理的可能性。这项研究将涉及多种学科投入，反映出问题的多面性：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需求的洞察和测试。

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.