Legal aspects of cloud security

Enterprise (large organisation) computing workloads are moving from ‘on-prem’ to ‘in-cloud’ increasingly quickly, and the cloud is forecast to account for almost half of enterprise IT by 2026, up from 10% today. But the benefits of the enterprise cloud need to be weighed against increasingly burdensome duties around cloud and data security. This comment piece provides a checklist of the sources of enterprise cloud security duties and a checklist of best practices to manage them.     

Legal aspects of text mining

“Text mining” covers a range of techniques that allow software to extract information from text documents. It is not a new technology, but it has recently received spotlight attention due to the emergence of Big Data. The applications of text mining are very diverse and span multiple disciplines, ranging from biomedicine to legal, business intelligence and security. From a legal perspective, text mining touches upon several areas of law, including contract law, copyright law and database law. This contribution discusses the legal issues encountered during the assembly of texts into so-called “corpora”, as well as the use of such corpora.     

Legal aspects of managing Big Data

Big Data is shorthand for the currently rapidly evolving techniques of gathering and analysing for competitive advantage vast unstructured and structured sets of digital data. Big Data is currently at an early stage of development, but many organisations will be embarking on Big Data projects in the next couple of years in order to be in a position to know more about their customers than their competitors. Central to the success of these projects will be four critical factors: (i) understanding the legal framework for Big Data and how it applies to the organisation concerned; (ii) effectively bringing together the organisation's IT and legal functions in the Big Data project; (iii) a clear understanding of the organisation's objectives for its Big Data operations; and (iv) a structured approach to the strategy, policy and process aspects of Big Data governance.     

Competition versus regulation: some empirical evidence

In response to dramatic rises in health care costs, policymakers have been debating the relative merits of regulatory and competitive strategies as a means of containing costs. One major activity espoused by proponents of competition is the growth of health maintenance organizations (HMOs) which, in their opinion, will result in the market better determining efficient levels of utilization and costs. Extending this argument, the larger the percent of the population in a market area who enroll in HMOs, the greater the market-forcing effect of HMOs in reducing overall hospital expenditures; that is, if HMOs are providing lower-cost care, then the fee-for-service system will be forced to reduce costs in order to be competitive. The authors studied the 25 largest SMSAs from 1971-1981, and controlling for environmental conditions in each market, they examined the impact of both HMO growth and regulatory activity on costs and utilization. They conclude that neither competition nor regulation had a significant impact in reducing overall hospital costs. While there may have been some impact in specific communities, no generalizable effect could be observed. However, the authors did find that increases in costs and utilization were essentially driven by supply factors such as the number of hospital beds or medical specialists in a given community.     

Pathological intoxication and alcohol idiosyncratic intoxication--Part II: Legal aspects

The law does not generally allow alcohol intoxication as a defense in a criminal matter. Among the exceptions may be pathological intoxication, or PI, or its current psychiatric correlate, alcohol idiosyncratic intoxication (AII). Because of the lack of specificity in the medical concept and the varying approaches by different authors, careful analysis and adherence to current standards are necessary. Relevant laws, particularly that of the model penal code, are reviewed, as are three cases which demonstrate the issues involved. Actual testimony is presented to illustrate possible misuse or inappropriate use of the concept.     

Legal aspects of withholding treatment from handicapped newborns: substantive issues

The controversy over nontreatment of handicapped newborns arises in a context of criminal and civil law, against which the current controversy has unfolded. This article examines the legal setting and background under traditional criminal and civil law concepts of nontreatment of handicapped newborns. It focuses on substantive principles of law, showing that nontreatment would be legally permitted when treatment could not be reasonably said to be in the interest of the patient involved, and that nontreatment could be considered criminal where treatment would serve patient interests. It then relates this analysis to procedural issues and the federal Baby Doe legislation and regulations that have recently emerged.     

Medical regulation of cognitive enhancement devices: some concerns

The authors present a cogent and detailed case for altering the Medical Devices Directive to allow regulation of cognitive enhancement devices (CEDs). Protection against significant risk of harm, especially for the vulnerable, and promotion of benefit through informed use of CEDs are all good features of the proposal. However, the pre-market approval process has limitations, which we explore. We raise the possibility of ‘risk compensation’ in response to the introduction of safety measures, which could alter its effectiveness. The proposal alludes to use of ‘formally trained practitioners,’ which provide a further tier of regulation for CEDs within the proposal. We consider some positive and negative implications of this aspect of the proposal that might warrant further consideration.     

Legal aspects of data cleansing in medical AI

Data quality is of paramount importance for the smooth functioning of modern data-driven AI applications with machine learning as a core technology. This is also true for medical AI, where malfunctions due to "dirty data" can have particularly dramatic harmful implications. Consequently, data cleansing is an important part in improving the usability of (Big) Data for medical AI systems. However, it should not be overlooked that data cleansing can also have negative effects on data quality if not performed carefully. This paper takes an interdisciplinary look at some of the technical and legal challenges of data cleansing against the background of European medical device law, with the key message that technical and legal aspects must always be considered together in such a sensitive context.