A survey conducted in April and May 2023 revealed that around 55 percent of the companies that do business in the European Union (EU) and the United Kingdom (UK) found it challenging to adapt to new or changing requirements of the General Data Protection Regulation (GDPR) or Data Protection Act 2018 (DPA). A further 45 percent of the survey respondents said it was challenging to increase the budget because of the changes in the data privacy laws.

A survey conducted in April and May 2023 revealed that around 35 percent of organizations in the United States and 40 percent of organizations in the United Kingdom pay higher costs for international data transfers due to data privacy regulations, but they also find it manageable. Furthermore, approximately 35 percent of respondents from both countries think the regulations encourage businesses by guaranteeing that the data will be safeguarded in other countries.

A survey conducted in April and May 2023 found that less than half of the surveyed organizations in the United States and the United Kingdom (UK) had completed selected actions to comply with state data privacy laws in the United States. Around 40 percent of the respondents had made a comparison of the United States' state-level privacy law frameworks. A further 30 percent said they were in the process of doing so. Furthermore, 41 percent of the respondents said they had updated privacy policies, while almost 30 percent were in the process of planning and conducting data assessments.

This dataset of historical poor law cases was created as part of a project aiming to assess the implications of the introduction of Artificial Intelligence (AI) into legal systems in Japan and the United Kingdom. The project was jointly funded by the UK’s Economic and Social Research Council, part of UKRI, and the Japanese Society and Technology Agency (JST), and involved collaboration between Cambridge University (the Centre for Business Research, Department of Computer Science and Faculty of Law) and Hitotsubashi University, Tokyo (the Graduate Schools of Law and Business Administration). As part of the project, a dataset of historic poor law cases was created to facilitate the analysis of legal texts using natural language processing methods. The dataset contains judgments of cases which have been annotated to facilitate computational analysis. Specifically, they make it possible to see how legal terms have evolved over time in the area of disputes over the law governing settlement by hiring.

A World Economic Forum meeting at Davos 2019 heralded the dawn of 'Society 5.0' in Japan. Its goal: creating a 'human-centred society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space.' Using Artificial Intelligence (AI), robotics and data, 'Society 5.0' proposes to '...enable the provision of only those products and services that are needed to the people that need them at the time they are needed, thereby optimizing the entire social and organizational system.' The Japanese government accepts that realising this vision 'will not be without its difficulties,' but intends 'to face them head-on with the aim of being the first in the world as a country facing challenging issues to present a model future society.' The UK government is similarly committed to investing in AI and likewise views the AI as central to engineering a more profitable economy and prosperous society.

This vision is, however, starting to crystallise in the rhetoric of LegalTech developers who have the data-intensive-and thus target-rich-environment of law in their sights. Buoyed by investment and claims of superior decision-making capabilities over human lawyers and judges, LegalTech is now being deputised to usher in a new era of 'smart' law built on AI and Big Data. While there are a number of bold claims made about the capabilities of these technologies, comparatively little attention has been directed to more fundamental questions about how we might assess the feasibility of using them to replicate core aspects of legal process, and ensuring the public has a meaningful say in the development and implementation.

This innovative and timely research project intends to approach these questions from a number of vectors. At a theoretical level, we consider the likely consequences of this step using a Horizon Scanning methodology developed in collaboration with our Japanese partners and an innovative systemic-evolutionary model of law. Many aspects of legal reasoning have algorithmic features which could lend themselves to automation. However, an evolutionary perspective also points to features of legal reasoning which are inconsistent with ML: including the reflexivity of legal knowledge and the incompleteness of legal rules at the point where they encounter the 'chaotic' and unstructured data generated by other social sub-systems. We will test our theory by developing a hierarchical model (or ontology), derived from our legal expertise and public available datasets, for classifying employment relationships under UK law. This will let us probe the extent to which legal reasoning can be modelled using less computational-intensive methods such as Markov Models and Monte Carlo Trees.

Building upon these theoretical innovations, we will then turn our attention from modelling a legal domain using historical data to exploring whether the outcome of legal cases can be reliably predicted using various technique for optimising datasets. For this we will use a data set comprised of 24,179 cases from the High Court of England and Wales. This will allow us to harness Natural Language Processing (NLP) techniques such as named entity recognition (to identify relevant parties) and sentiment analysis (to analyse opinions and determine the disposition of a party) in addition to identifying the main legal and factual points of the dispute, remedies, costs, and trial durations. By trailing various predictive heuristics and ML techniques against this dataset we hope to develop a more granular understanding as to the feasibility of predicting dispute outcomes and insight to what factors are relevant for legal decision-making. This will allow us to then undertake a comparative analysis with the results of existing studies and shed light on the legal contexts and questions where AI can and cannot be used to produce accurate and repeatable results.

As of February 2025, the largest fine issued for violation of the General Data Protection Regulation (GDPR) in the United Kingdom (UK) was more than 22 million euros, received by British Airways in October 2020. Another fine received by Marriott International Inc. in the same month was the second-highest in the UK and amounted to over 20 million euros.

Abstract copyright UK Data Service and data collection copyright owner.

The paper Udny Yule read to the Royal Statistical Society at the end of the nineteenth century (Yule, 1899) was a landmark in social statistics. He applied multiple regression analysis to a question of social policy, namely reforms to the 19th century system of poverty alleviation in England. To do this, Yule created a dataset from administrative and Census data. Yule’s original dataset was not preserved, but because his data were drawn from public sources, it is possible to reconstruct it, albeit with some slight differences from the original. This report provides a description of how the dataset was reconstructed and how it varies from the one used in the 1899 paper.

Contains claim details, as submitted by a provider, including: client details, profit and disbursement costs and category of Law. The database also contains contract & schedule information and various codes pertaining to each area of law (civil advice (non court) claims, Police Station advice claims and Magistrates Court claims.

This is because it would breach the first data protection principle as: a) it is not fair to disclose claimant personal details to the world and is likely to cause damage or distress. b) these details are not of sufficient interest to the public to warrant an intrusion into the privacy of the claimant. Please click the below web link to see the exemption in full. https://www.legislation.gov.uk/ukpga/2000/36/section/40 Breach of Patient confidentiality Please note that the identification of claimants is also a breach of the common law duty of confidence. A claimant who has been identified could make a claim against the NHSBSA or yourself for the disclosure of the confidential information. The information requested is therefore being withheld as it falls under the exemption in section 41(1) ‘Information provided in confidence’ of the Freedom of Information Act. Please click the below web link to see the exemption in full. https://www.legislation.gov.uk/ukpga/2000/36/section/41

Legal abortions: rates by Primary Care Organisation by age. Rates per 1,000 in age group. Age not stated have been distributed pro-rata across age group 20-24. Rates for under 16 are based on populations 13-15. Rates for all ages, under 18 and 35 and over are based on populations 15-44, 15-17 and 35-44 respectively.

External links:

https://www.gov.uk/government/statistics/report-on-abortion-statistics-in-england-and-wales-for-2012

https://www.gov.uk/government/collections/abortion-statistics-for-england-and-wales

United Kingdom UK: Rule of Law: Estimate data was reported at 1.679 NA in 2017. This records a decrease from the previous number of 1.692 NA for 2016. United Kingdom UK: Rule of Law: Estimate data is updated yearly, averaging 1.705 NA from Dec 1996 (Median) to 2017, with 19 observations. The data reached an all-time high of 1.890 NA in 2014 and a record low of 1.569 NA in 2005. United Kingdom UK: Rule of Law: Estimate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WGI: Country Governance Indicators. Rule of Law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.

United Kingdom UK: Law Prohibits or Invalidates Child or Early Marriage: 1=Yes; 0=No data was reported at 1.000 NA in 2017. This stayed constant from the previous number of 1.000 NA for 2015. United Kingdom UK: Law Prohibits or Invalidates Child or Early Marriage: 1=Yes; 0=No data is updated yearly, averaging 1.000 NA from Dec 2015 (Median) to 2017, with 2 observations. The data reached an all-time high of 1.000 NA in 2017 and a record low of 1.000 NA in 2017. United Kingdom UK: Law Prohibits or Invalidates Child or Early Marriage: 1=Yes; 0=No data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Policy and Institutions. Law prohibits or invalidates child or early marriage is whether there are provisions that prevent the marriage of girls, boys, or both before they reach the legal age of marriage or the age of marriage with consent, including, for example, a prohibition on registering the marriage or provisions stating that such a marriage is null and void.; ; World Bank: Women, Business and the Law.; ;

BackgroundThe COVID-19 pandemic brought global disruption to health, society and economy, including to the conduct of clinical research. In the European Union (EU), the legal and ethical framework for research is complex and divergent. Many challenges exist in relation to the interplay of the various applicable rules, particularly with respect to compliance with the General Data Protection Regulation (GDPR). This study aimed to gain insights into the experience of key clinical research stakeholders [investigators, ethics committees (ECs), and data protection officers (DPOs)/legal experts working with clinical research sponsors] across the EU and the UK on the main challenges related to data protection in clinical research before and during the pandemic.Materials and methodsThe study consisted of an online survey and follow-up semi-structured interviews. Data collection occurred between April and December 2021. Survey data was analyzed descriptively, and the interviews underwent a framework analysis.Results and conclusionIn total, 191 respondents filled in the survey, of whom fourteen participated in the follow-up interviews. Out of the targeted 28 countries (EU and UK), 25 were represented in the survey. The majority of stakeholders were based in Western Europe. This study empirically elucidated numerous key legal and ethical issues related to GDPR compliance in the context of (cross-border) clinical research. It showed that the lack of legal harmonization remains the biggest challenge in the field, and that it is present not only at the level of the interplay of key EU legislative acts and national implementation of the GDPR, but also when it comes to interpretation at local, regional and institutional levels. Moreover, the role of ECs in data protection was further explored and possible ways forward for its normative delineation were discussed. According to the participants, the pandemic did not bring additional legal challenges. Although practical challenges (for instance, mainly related to the provision of information to patients) were high due to the globally enacted crisis measures, the key problematic issues on (cross-border) health research, interpretations of the legal texts and compliance strategies remained largely the same.

Forecast: Number of Enterprises of Legal Services in the UK 2024 - 2028 Discover more data with ReportLinker!

This dataset is about book subjects and is filtered where the books is Competition law and policy in the EU and UK, featuring 10 columns including authors, average publication date, book publishers, book subject, and books. The preview is ordered by number of books (descending).

Coastal Legislative Layer [Polyline]. The Coastal Overview data layers identifies the lead authority for the management of discrete stretches of the English coast as defined by the Seaward of the Schedule 4 boundary of the Coastal Protection Act 1949. The data are intended as a reference for GIS users and Coastal Engineers with GIS capability to identify the responsible authority or whether the coast is privately owned. The information has been assigned from the following sources, listed in by preference: Shoreline Management Plans 1. Environment Agency’s RACE database. Consultation with Coastal Business User Group and Local Authority Maritime records where possible. A confidence rating is attributed based on where the data has been attributed from and the entry derived from the source data. The following data is intended as a reference document for GIS users and Coastal Engineers with GIS capability to identify the responsible authority and the assigned EA Coastal Engineer so as to effectively manage the coast for erosion and flooding. The product comprises 3 GIS layers that are based on the OS MasterMap Mean High Watermark, this layers is: Coastal Legislative Layer Polyline represents the predominant risk; flooding or erosion, which are assigned to each section of the coastline. Attribution statement: © Environment Agency copyright and/or database right 2016. All rights reserved. © Crown copyright and database rights 2009 Ordnance Survey 100024198

According to a survey conducted from January to February 2024 in the United Kingdom (UK), only 46 percent knew they had a right to ask a company or organization to delete personal information about them. A further 34 percent said they thought they could stop companies from sending them marketing communication but did not know that it was a legal right.

Tax avoidance and the law : understanding the UK General Anti-Abuse Rule is a book. It was written by Selina Keesoony and published by Routledge in 2022.

Land use-Law and legislation-England is a book subject. It includes 26 books, written by 12 different authors.