The paper explores the integration of artificial intelligence in legal practice, discussing the ethical and practical issues that arise and how it affects customary legal procedures. It emphasises the shift from labour-intensive legal practice to technology-enhanced methods, with a focus on artificial intelligence's potential to improve access to legal services and streamline legal procedures. This discussion importantly highlights the ethical challenges introduced by the integration of Artificial Intelligence, with a specific focus on issues of bias and transparency. These ethical concerns become particularly paramount in the context of sensitive legal areas, including but not limited to, child custody disputes, criminal justice, and divorce settlements. It underscores the critical need for maintaining ethical vigilance, advocating for developing and implementing AI systems characterised by a profound commitment to ethical integrity. This approach is vital to guarantee fairness and uphold transparency across all judicial proceedings. The study advocates for a "human in the loop" strategy that combines human knowledge and AI techniques to mitigate biases and guarantee individualised legal results to ensure AI functions as a complement rather than a replacement, the paper concludes by emphasising the necessity of preserving the human element in legal practices.
The employment of AI systems presents challenges for liability rules. This paper identifies these challenges and evaluates how liability rules should be adapted in response. The paper discusses the gaps in liability that arise when AI systems are unpredictable or act (semi)-autonomously. It considers the problems in proving fault and causality when errors in AI systems are difficult to foresee for producers, and monitoring duties of users are difficult to define. From an economic perspective, the paper considers what liability rules would minimise costs of harm related to AI. Based on the analysis of risks and optimal liability rules, the paper evaluates the recently published EU proposals for a Product Liability Directive and for an AI Liability Directive.
Emerging across many disciplines are questions about algorithmic ethics – about the values embedded in artificial intelligence and big data analytics that increasingly replace human decisionmaking. Many are concerned that an algorithmic society is too opaque to be accountable for its behavior. An individual can be denied parole or denied credit, fired or not hired for reasons she will never know and cannot be articulated. In the public sector, the opacity of algorithmic decisionmaking is particularly problematic both because governmental decisions may be especially weighty, and because democratically-elected governments bear special duties of accountability. Investigative journalists have recently exposed the dangerous impenetrability of algorithmic processes used in the criminal justice field – dangerous because the predictions they make can be both erroneous and unfair, with none the wiser. We set out to test the limits of transparency around governmental deployment of big data analytics, focusing our investigation on local and state government use of predictive algorithms. It is here, in local government, that algorithmically-determined decisions can be most directly impactful. And it is here that stretched agencies are most likely to hand over the analytics to private vendors, which may make design and policy choices out of the sight of the client agencies, the public, or both. To see just how impenetrable the resulting “black box” algorithms are, we filed 42 open records requests in 23 states seeking essential information about six predictive algorithm programs. We selected the most widely-used and well-reviewed programs, including those developed by for-profit companies, nonprofits, and academic/private sector partnerships. The goal was to see if, using the open records process, we could discover what policy judgments these algorithms embody, and could evaluate their utility and fairness. To do this work, we identified what meaningful “algorithmic transparency” entails. We found that in almost every case, it wasn’t provided. Over-broad assertions of trade secrecy were a problem. But contrary to conventional wisdom, they were not the biggest obstacle. It will not usually be necessary to release the code used to execute predictive models in order to dramatically increase transparency. We conclude that publicly-deployed algorithms will be sufficiently transparent only if (1) governments generate appropriate records about their objectives for algorithmic processes and subsequent implementation and validation; (2) government contractors reveal to the public agency sufficient information about how they developed the algorithm; and (3) public agencies and courts treat trade secrecy claims as the limited exception to public disclosure that the law requires. Although it would require a multi-stakeholder process to develop best practices for record generation and disclosure, we present what we believe are eight principal types of information that such records should ideally contain.
The time is ripe for the construction of a doctrinal legal discourse system with Chinese characteristics for criminal law in the stage of subjectivity awakening. The targeted discourse system should achieve at least the following two effects: namely legal effect and social effect. In order to achieve the desired effect, the process of the construction of a doctrinal legal discourse system with Chinese characteristics for criminal law requires the establishment of a general construction idea and specific issues of inquiry.The general construction idea consists of four parts: the historical investigation of China’s doctrinal legal discourse system with Chinese characteristics for criminal law, the identification and reference of foreign doctrinal legal discourse systems for criminal law, the clarification of the principles of China’s doctrinal legal discourse system with Chinese characteristics for criminal law, and the construction of China’s doctrinal legal discourse system with Chinese characteristics for criminal law. In each part, the theoretical issues that need to be concentrated on are clarified according to the general construction idea, so as to enhance the focus of the construction of the discourse system and finally complete the construction of the doctrinal legal discourse system with Chinese characteristics for criminal law.
在法律规范层面和司法实践层面,以物抵债协议面临分类错误、新旧给付关系难以确定等问题,《民法典合同编通则解释意见稿》第 28 条、第 29 条是以物抵债的最新规则发展,但尚有不足.对此,应坚持功能主义,明确以物抵债协议的真实性质,以现有民法理论为基础完善以物抵债协议的法律构造,并从协议签订日期与债务履行期的关系、新给付履行期与原给付履行期的关系以及当事人目的等多重维度完成以物抵债协议的类型化建构.清偿型以物抵债协议的法律构造为变更契约下的代物清偿,原给付和新给付共同保障基础债权的实现,且债务人应先履行新给付,同时需给债权人配置瑕疵担保责任请求权、原给付请求权和损害赔偿请求权等救济手段,协议下并不存在强制清算义务.担保型以物抵债协议与《民法典》第 388 条相契合,但应采取穿透式司法审判思维探究该类协议的真实担保意思,避免隐藏的意思表示,以区分不同情形选择适用《民法典》及司法解释中所确定的有关担保物权的规则.
