This book gives a comprehensive overview of the state of Artificial Intelligence (AI), especially machine learning (ML) applications in public service delivery in Estonia, discussing the manifold ethical and legal issues that arise under both European and Estonian law. Final conclusions and recommendations set out and analyze various policy options for the public sector, taking into account recent developments at the European level - such as the AIA proposal - as well as the experience of countries that have issued principles and guidelines or even laws for the use of ML in the public sector.

This book analyses the current legal situation and protection of vulnerable groups in Lithuania, Latvia, Estonia and Poland. In recent decades, national legislation in many European states has especially focused on vulnerable groups with the aim of securing their enhanced protection and social inclusion. This trend is also noticeable in North-Eastern Europe, where the legal frameworks are constantly being revised to address the needs of vulnerable parts of society, including women, children, the elderly, people with disabilities, and minorities, as well as prisoners and victims of crime. But despite these positive changes, many challenges persist. In this book, the authors provide a comprehensive, comparative analysis of legal regulations and practices intended to protect vulnerable groups in Lithuania, Latvia, Estonia and Poland, and in the process, share insights into the current situation and trends in this often-overlooked region. Part I introduces readers to the topic by defining the concept of vulnerable groups and elaborating on its understanding in the European and national contexts. Part II analyses the legal protection of groups characterised by inherent and/or circumstantial vulnerability, while Part III addresses specific crime-related vulnerability issues in the target region. In closing, Part IV puts the spotlight on three specific vulnerable groups in the discussed countries.

This Monograph explains the statistical theory behind the National Forest Inventory (NFI) data collection and compares different methods for modelling and inventory design. The author also explains how natural uncertainty in measurement and modelling can affects the results. Forests, as dynamic systems, are influenced by many unpredictable factors over time. Therefore, readers can use this book to develop the right framework of expectations, when using NFI data. The chapters give an outlook on traditional methods like sample plots, but also consider newer approaches like remote sensing. By merging these different techniqes, NFI datasets can become more reliable and facetted. One of the most contemporary developments in the field, is the use of continuous plots that offer live data at all times. Whether this data should be open to the public, is another discussion point that the author addresses.