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A simple model and a distributed architecture for realizing one-stop e-governmentIn this paper, we propose a generic model for one-stop e-government and a distributed architecture for its implementation. The model follows a very basic paradigm: the public administration is composed of an unstructured network of entities that upload and download information objects to/from each other and to/from service repositories in order to deliver client-centered services. The architecture is based on widely available technologies such as HTTP, SSL, XML and PKI and it supports the implementation of life events, single access points, concurrent providers and integrated delivery channels. We argue that the proposed architecture permits the interconnection of almost any kind of government body and that it establishes a common ground upon which new standardization levels can be built. As a starting point, we also define a set of general requirements for one-stop e-government. © 2006 Elsevier B.V. All rights reserved.
Regulating by Robot: Administrative Decision Making in the Machine-Learning EraMachine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere. A few administrative agencies have already begun to adopt this technology, while others have the clear potential in the near-term to use algorithms to shape official decisions over both rulemaking and adjudication. It is no longer fanciful to envision a future in which government agencies could effectively make law by robot, a prospect that understandably conjures up dystopian images of individuals surrendering their liberty to the control of computerized overlords. Should society be alarmed by governmental use of machine learning applications? We examine this question by considering whether the use of robotic decision tools by government agencies can pass muster under core, time-honored doctrines of administrative and constitutional law. At first glance, the idea of algorithmic regulation might appear to offend one or more traditional doctrines, such as the nondelegation doctrine, procedural due process, equal protection, or principles of reason-giving and transparency. We conclude, however, that when machine-learning technology is properly understood, its use by government agencies can comfortably fit within these conventional legal parameters. We recognize, of course, that the legality of regulation by robot is only one criterion by which its use should be assessed. Obviously, agencies should not apply algorithms cavalierly, even if doing so might not run afoul of the law, and in some cases, safeguards may be needed for machine learning to satisfy broader, good-governance aspirations. Yet in contrast with the emerging alarmism, we resist any categorical dismissal of a future administrative state in which key decisions are guided by, and even at times made by, algorithmic automation. Instead, we urge that governmental reliance on machine learning should be approached with measured optimism over the potential benefits such technology can offer society by making government smarter and its decisions more efficient and just.
Criminal law measures of ensuring the security of the crypto sphereIn the first issue of the Bratislava Law Review magazine for 2018, our article addressed the problem of legal regulation of relations related to the crypto sphere “Failure to repatiate funds in foreign currency from abroad and modern issues of currency regulation” was published. In December 2017, Bitcoin predicted the cost of $ 40 – $ 100 thousand. However, in 2018, the situation changed-the Bitcoin exchange rate began to lose from $ 0.5 to $ 1 thousand per day, and its market capitalization fell to $ 70 billion. The crisis of the crypto market has affected not only the capitalization of cryptocurrencies, but also the issues of legal regulation of relations associated with its use. Currently, only three countries – Sweden, the Netherlands and Japan – recognize cryptocurrency as a legal means of payment. In Spain, the cryptocurrency is classified as an electronic means of payment only in relation to the gaming business. The legislation of Germany, as well as Finland, allows to classify cryptocurrencies as financial instruments. In China, Singapore and Norway cryptocurrency is considered as a financial asset in the US – as property, i.e. developed countries are in no hurry to equate cryptocurrency to means of payment. In Russia, the use of cryptocurrencies is not regulated by any rules, but there is no legislation prohibiting the circulation of cryptocurrencies as means of payment. At the same time, the draft bill “On digital nancial assets”, designed to regulate financial relations in the crypto sphere, completely excludes the issues of mining and circulation of existing crypto-currencies. However, new electronic entities carry certain risks associated with their turnover. In this regard, many States seek to develop mechanisms to ensure the security of actions in the new crypto sphere of legal relations before the direct legalization of cryptocurrencies and other modern electronic entities. The purpose of the article is to analyze the approaches related to the security of the crypto sphere in modern society by criminal law measures taking into account foreign experience.
The Supreme Court and Information PrivacyAdvances in technology—including the growing use of cloud computing by individuals, agencies, and organizations to conduct operations and store and process records—are enabling the systematic collection and use of personal data by state and federal governments for a variety of purposes. These purposes range from battling crime and terrorism to assessing public policy initiatives and enforcing regulatory regimes. To aid these efforts, governments are promoting mandatory retention and reporting of data by online service providers and the expansion of laws that facilitate wiretaps to greater portions of the web. The legal framework for protecting individual privacy within this growing world of ‘big data’ is patchy and in critical ways outdated. Most of the current framework was erected in response to pronouncements by the Supreme Court over the years regarding the scope of constitutional privacy protections. Widespread agreement over the need for legislators to update the statutory regime has not yet produced results. Against this backdrop, the US Supreme Court has struggled in recent cases to articulate workable constitutional and statutory privacy norms that can help guide government, and individuals, in a world of digital and distributed data. An examination of the Court’s privacy jurisprudence over the past forty years offers a number of insights into how the Court, and policy-makers, may achieve a balance between privacy and data use that accords with constitutional norms, serves vital public policy goals, and secures greater public trust and support.
Big Data in the Insurance Industry: Leeway and Limits for Individualising Insurance ContractsWith the advent of big data analytics, the individualisation of mass market insurance policies has become commercially attractive. While this development would have positive economic effects, it could also undermine the principle of solidarity in insurance. This paper aims to outline the different regulatory approaches currently in place for dealing with this fundamental challenge by analysing the insurance, anti-discrimination and data protection laws of Switzerland and the U.S./California pertaining to health, renters and automobile insurance. It will be shown that the leeway for individualising insurance contracts is vanishingly small for (mandatory) health insurance on both sides of the Atlantic. By contrast, the two legal systems pursue different regulatory approaches with regard to the other two types of insurance. Renters and automobile insurance are predominantly governed by the freedom of contract principle in Switzerland, whereas in California sector specific regulations significantly limit the informational basis of insurance companies, thereby limiting the leeway for individualisation to a large extent. While Swiss anti-discrimination law hardly restricts the individualisation of insurance contracts, U.S. and California law prohibit such individualisation based on protected characteristics, in this way further restricting the remaining leeway. While privacy laws in the U.S. and California set some significant but rather specific limits for the individualisation of insurance contracts based on the use of personal data, the all-encompassing Swiss (and European) data protection law is clearly the most important barrier to individualisation in Switzerland. Namely, it remains unclear whether the processing of personal data for the purpose of individualising insurance contracts may be based on the legitimate interests of the insurer. As a consequence, insurance companies are advised to always obtain their customers’ consent for making individual offers based on big data analytics. The authors conclude that instead of indirectly hindering the individualisation of insurance contracts through data protection law, Swiss (and European) lawmakers should initiate a dialogue involving all stakeholders to determine which sectors of insurance should be dominated by the principle of solidarity and in which sectors and on what informational basis the individualisation of insurance contracts should be allowed.