Artificial Intelligence in Law

Nikolskaia, Kseniia; Naumov, Victor B.

doi:10.1109/fareastcon50210.2020.9271095

Cited by 21 publications

(2 citation statements)

References 1 publication

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“…Miscommunication, insufficient specifications and plans, rigid contracts, changes in site conditions, non-payment, catch up profits, limited workforce, insufficient tools and equipment, ineffective supervision, notice requirements, constructive changes not acknowledged by owner, delays, and acceleration measures provoking claims and causing disputes. Therefore, Arditi and Phulket [54] proposed a tool to predict the outcome of litigation to minimise construction disputes caused by disagreements that are complicated to be settled without engaging in legal actions [54], [55].…”

Section: Types Of Judicial Decisionmentioning

confidence: 99%

A systematic literature review of machine learning methods in predicting court decisions

Rosili

Hassan

Zakaria

et al. 2021

IJ-AI

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<span>Envisaging legal cases’ outcomes can assist the judicial decision-making process. Prediction is possible in various cases, such as predicting the outcome of construction litigation, crime-related cases, parental rights, worker types, divorces, and tax law. The machine learning methods can function as support decision tools in the legal system with artificial intelligence’s advancement. This study aimed to impart a systematic literature review (SLR) of studies concerning the prediction of court decisions via machine learning methods. The review determines and analyses the machine learning methods used in predicting court decisions. This review utilised RepOrting Standards for Systematic Evidence Syntheses (ROSES) publication standard. Subsequently, 22 relevant studies that most commonly predicted the judgement results involving binary classification were chosen from significant databases: Scopus and Web of Sciences. According to the SLR’s outcomes, various machine learning methods can be used in predicting court decisions. Additionally, the performance is acceptable since most methods achieved more than 70% accuracy. Nevertheless, improvements can be made on the types of judicial decisions predicted using the existing machine learning methods.</span>

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Section: Types Of Judicial Decisionmentioning

confidence: 99%

A systematic literature review of machine learning methods in predicting court decisions

Rosili

Hassan

Zakaria

et al. 2021

IJ-AI

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“…The possibility of ethical regulation of digital technologies, including AI, is being discussed at various venues in the world and in Russia [1]. Many believe that ethical norms are much more perceived in the technical sphere than legal ones, and are more accessible [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Problems of ethical regulation of the use of artificial intelligence technologies

Minbaleev

Polyakova

Makarov³

2021

SHS Web Conf.

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The purpose of the article is to analyze the problem of ethical regulation of artificial intelligence technologies in a modern complex socio-cultural environment and active digital transformation of society. In the world today, the practice of private ethical initiatives is very common, associated with the joining of efforts of a number of companies to develop the use of artificial intelligence technologies and consolidate the basic principles of working with such technologies. The research used such scientific methods as dialectical, logical, historical, predictive, systems analysis, content analysis, as well as private scientific methods, such as comparative legal and the method of legal modeling. The study results in proposals for introducing ethical regulators into the general mechanism for regulating digital technologies, obtained on the basis of an analysis of the main directions and approaches to ethical regulation, as well as identifying key problems of ethical regulation in the field of artificial intelligence that have to be solved by society and the state. The authors support the position of researchers and governments of a number of states that normative regulation should take precedence over ethical, the tasks of any state should be to provide normative support for the use of artificial intelligence technologies and protect the rights of citizens. The novelty of the work lies in the conclusion that at the level of the Government of the Russian Federation today it is advisable to develop Model Rules for the use of artificial intelligence technologies in government and local authorities, as well as in their subordinate organizations. The rules can enshrine ethical principles and norms based on the provisions of acts of international organizations and recommendations of the professional expert community. The rules can also reflect recommendations for their use by non-state legal entities, individual citizens. It is concluded that such an approach would eliminate the possibility of numerous ethical codes and regulations from both the public and commercial sectors and would not be redundant.

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Does ChatGPT Pass the Brazilian Bar Exam?

Freitas,

Gomes

2023

Lecture Notes in Computer Science

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Artificial Intelligence in Law

Cited by 21 publications

References 1 publication

A systematic literature review of machine learning methods in predicting court decisions

A systematic literature review of machine learning methods in predicting court decisions

Problems of ethical regulation of the use of artificial intelligence technologies

Does ChatGPT Pass the Brazilian Bar Exam?

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