There has been relatively little empirical research into the causes of research misconduct. To begin to address this void, the authors collected data from closed case files of the Office of Research Integrity (ORI). These data were in the form of statements extracted from ORI file documents including transcripts, investigative reports, witness statements, and correspondence. Researchers assigned these statements to 44 different concepts. These concepts were then analyzed using multidimensional scaling and cluster analysis. The authors chose a solution consisting (...) of seven clusters: (1) personal and professional stressors, (2) organizational climate, (3) job insecurities, (4) rationalizations A, (5) personal inhibitions, (6) rationalizations B and, (7) personality factors. The authors discuss the implications of their findings for policy and for future research. (shrink)

Recommender systems are recently developed computer-assisted tools that support social and informational needs of various communities and help users exploit huge amounts of data for making optimal decisions. In this study, we present a new recommender system for assessment and risk prediction in child welfare institutions in Israel. The system exploits a large diachronic repository of manually completed questionnaires on functioning of welfare institutions and proposes two different rule-based computational models. The system accepts users’ requests via a simple graphical (...) interface, calculates the institutions’ profiles according to user preferences, and presents assessment scores, trends and comparative analyses of the corresponding data using assorted visual aids. Based on the analysis, the system offers three different strategies for objective assessment of the institutions’ functioning and risks. Qualitative and quantitative evaluation of the system’s effectiveness and accuracy demonstrates that it substantially improves the assessment process of a welfare institution. Moreover, it provides an effective tool for objective large-scale analysis of the institution’s overall state and trends, which were previously based primarily on the institution supervisors’ subjective judgment and intuition. In addition, the proposed recommender system has great practical and social impact as it may help identify and avert potential problems, malfunctions, flaws, risks and even tragic incidents in child welfare institutions, as well as increase their overall functioning levels. As a result, as a long-term social implication, the system may also help reduce inequality and social gaps in the Israeli society. (shrink)

Precaution is a relevant and much-invoked value in environmental risk analysis, as witnessed by the ongoing vivid discussion about the precautionary principle (PP). This article argues (i) against purely decision-theoretic explications of PP; (ii) that the construction, evaluation, and use of scientific models falls under the scope of PP; and (iii) that epistemic and decision-theoretic robustness are essential for precautionary policy making. These claims are elaborated and defended by means of case studies from climate science and conservation biology.

Recent attempts to develop and apply digital ethics principles to address the challenges of the digital transformation leave organisations with an operationalisation gap. To successfully implement such guidance, they must find ways to translate high-level ethics frameworks into practical methods and tools that match their specific workflows and needs. Here, we describe the development of a standardised risk assessment tool, the Principle-at-Risk Analysis (PaRA), as a means to close this operationalisation gap for a key level of the (...) ethics infrastructure at many organisations – the work of an interdisciplinary ethics panel. The PaRA tool serves to guide and harmonise the work of the Digital Ethics Advisory Panel at the multinational science and technology company Merck KGaA in alignment with the principles outlined in the company’s Code of Digital Ethics. We examine how such a tool can be used as part of a multifaceted approach to operationalise high-level principles at an organisational level and provide general requirements for its implementation. We showcase its application in an example case dealing with the comprehensibility of consent forms in a data-sharing context at Syntropy, a collaborative technology platform for clinical research. (shrink)

With the development of distributed networks, the remote controllability of the distributed energy objects and the vulnerability of user-side information security protection measures make distributed energy objects extremely vulnerable to malicious control by attackers. Hence, the large-scale loads may produce abnormal operation performance, such as load casting/dropping synchronously or frequent and synchronous casting and dropping, and hence, it can threaten the security and stable operation of the distribution networks. First, we analyze the security threats faced by industrial controllable load, civil (...) controllable load, and the gains and losses of attacks on the distribution networks. Considering the factors of cyber attacks, we propose a control model and cyber attack model in active distribution networks. And, three types of attacks that the target suffered are defined on the basis of “on” and “off” modes for control. Then, the controllable load was maliciously controlled as the research object, and a suitable scenario is selected. The impact of malicious control of the controllable load on the power supply reliability and power quality of the distribution networks are simulated and analyzed, and risk consequences for different types of attacks are provided. (shrink)

Mainstream risk analysis deviates in at least two important respects from the rationality ideal of mainstream economics. First, expected utility maximization is not applied in a consistent way. It is applied to endodoxastic uncertainty, i.e. the uncertainty (or risk) expressed in a risk assessment, but in many cases not to metadoxastic uncertainty, i.e. uncertainty about which of several competing assessments is correct. Instead, a common approach to metadoxastic uncertainty is to only take the most plausible assessment (...) into account. This will typically lead to risk-prone deviations from risk-neutrality. Secondly, risks and benefits for different persons are added to form a total value of risk. Such calculations are used to support the view that one should accept being exposed to a risk if it brings greater benefits for others. This is in stark contrast to modern Paretian welfare economics, that refrains from interindividual comparisons and does not require people to accept a disadvantage because it brings a larger advantage for others. (Published Online July 11 2006). (shrink)

The relatively new discipline of risk analysis promises to provide objective guidance in some of the most controversial issues in modern high‐technology societies. Four conditions are discussed that must be satisfied for this promise to be fulfilled. Since none of these conditions is satisfied, risk analysis does not keep its promise. In its attempts to reduce genuinely political issues to technocratic calculations, it neglects many of the factors that should influence decisions on risk acceptance. A (...) list of tentative guidelines is given for numerical decision support that encourages democratic decision‐making instead of trying to evade it. (shrink)

In recent years, risk management and analysis has attracted a great deal of attention from both researchers and practitioners. Enterprise risk management has become an important topic in today’s more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical sources. This survey and introductory article addresses computerized tools used for risk management and analysis. Risks are studied from perspectives of different disciplines, with a discussion of how various methods and tools (...) are used to optimize risk management. (shrink)

Risk analysis and regulatory systems are usually evaluated according to utilitarian frameworks, as they are viewed to operate “objectively” by considering the health, environmental, and economic impacts of technological applications. Yet, the estimation of impacts during risk analysis and the decisions in regulatory review are affected by value choices of actors and stakeholders; attention to principles such as autonomy, justice, and integrity; and power relationships. In this article, case studies of biotechnology are used to illustrate how (...) non-utilitarian principles are prominent in risk analysis and regulatory review and to argue that these relationships should be carefully considered as we consider nanotechnology oversight systems for its products. We argue that there are not distinct separations between “science-based” review systems, in which evaluations of the consequences of technological products are primarily considered, and principles of integrity, justice, non-maleficence, and autonomy. It should further be expected that, given research into fair treatment during decision-making processes, attention to ethics will affect how citizens assess emerging technologies. Finally, a more holistic approach for evaluating oversight systems for the products of nanotechnology is suggested, one which does not draw a sharp distinction between risk analysis, regulation, and respect for non-utilitarian values. (shrink)

A capability approach has been proposed to risk analysis, where risk is conceptualized as the probability that capabilities are reduced. Capabilities refer to the genuine opportunities of individuals to achieve valuable doings and beings, such as being adequately nourished. Such doings and beings are called functionings. A current debate in risk analysis and other fields where a capability approach has been developed concerns whether capabilities or actual achieved functionings should be used. This paper argues that (...) in risk analysis the consequences of hazardous scenarios should be conceptualized in terms of capabilities, not achieved functionings. Furthermore, the paper proposes a method for assessing capabilities, which considers the levels of achieved functionings of other individuals with similar boundary conditions. The capability of an individual can then be captured statistically based on the variability of the achieved functionings over the considered population. (shrink)

Digital currency is considered a form of currency which is used in the digital world such as digital forms or electronic devices. Several terms are synonyms for digital currency like digital money, electronic money, and cyber cash. Accurate prediction of the digital currency is an urgent necessity due to its impacts on the economic community. The electronic economy is very dangerous and must be approached with great caution, so as to avoid or minimize the risks that occur in such cases. (...) Deep neural network algorithm was improved to predict the Bitcoin price and then achieve the main goal of reducing financial risks to proceed with electronic business, and good estimation was achieved by using informative data such as transactions and currency return. The proposed method extracted features of related Bitcoin and used the informative ones. Transaction plan considered building nodes in terms of network. Development of deep learning algorithms opens the horizons for the development of electronic businesses that use digital currency. The proposed method achieved worthy results in terms of accuracy and correct prediction and offers the prospect of other research in this area. (shrink)

The articles included in this thesis centre on what can be called the normative basis of risk analysis. Since risk analyses are decision procedures, they should adhere to norms of rational decision-making, and this they do. Most risk analysis schemes are built on a notion of the decision theoretic maxim that the goal of every decision is to maximize expected utility. However, for some thirty years now this maxim has been called into question. The idea (...) is not that it is unreasonable in itself, but that the theoretical construct of which it is a consequence is in some way inappropriate. Idealizations of the theories are criticized for being too excessive. They do not properly cover cases where the decision maker has poor or, as it were, imprecise knowledge. These are situations where risks are not only about the consequences of the decision but also there are risks with the knowledge itself, epistemic risks. If it is important for a normative decision theory to be not only ideal as a theoretical construct, but to have, in addition, a prescriptive purpose, that theory should also be applicable to actual decision makers and to somehow deal with epistemic risks. The first two papers are about what kinds of decision theory there are, and how best to construe them. The first describes the differences between normative, descriptive and prescriptive decision theories. The second asks whether there is anything intrinsic to the theory that makes it normative or descriptive. Paper 3 asks on what grounds risk assessment is required to be separated from risk management in the risk analysis process. It is argued that the separation is there to ensure that epistemic values are held apart from non-epistemic values. The paper ends by arguing that, in efforts to improve risk management decision-making, it is more important to be explicit about scientific uncertainty than it is to separate sets of values. Paper 4 argues for a more complete decision-theoretic basis for risk analysis. The contrast here is with the bifurcated process of maximizing expected utility when sufficient knowledge is available and using the precautionary principle in cases where knowledge is more limited. Paper 5 investigates the notion of epistemic risk in detail. (shrink)

Discussions of socioeconomic liability and compensation must necessarily start from an understanding of the socioeconomic, legal, and scientific basis for identifying, assessing, managing, and apportioning blame for hazards related to innovations. Public discussions about the nature of the liability challenge related to genetically modified (GM) crops and other modified organisms have focused less on direct, traditional health, public safety, technical, or environmental failures (e.g., innovations that generate hazards directly for users or indirectly to bystanders) and more on socioeconomic concerns, such (...) as comingled product that offends product quality standards. This article examines the theoretical and legal underpinnings of the current risk analysis framework used in most Organization for Economic Cooperation and Development countries and uses it to assess two areas of significant controversy—the release of herbicide-tolerant canola and flax varieties in Western Canada. The article offers lessons for the management of liabilities arising from the introduction of GM crops. (shrink)

Some have characterized patients living with intractable pain as a vulnerable population in both clinical and research settings. Labeling the population as vulnerable, however, does not provide clarity regarding the potential risks that they face when they participate in research. Instead, research vulnerability for patients in pain is a function of an interaction between their pain conditions and elements of the research enterprise. Therefore, the identification of potential risks requires consideration not only of characteristics of patients with chronic pain, but (...) also consideration of features of researchers, the quality of institutional oversight, and the medical/social environment within which the research is conducted. This paper provides an analysis of those risks and provides some suggestions as to how the risks might be better managed. (shrink)

A key question for evidence-based medicine is how best to model the way in which EBM should‘[integrate] individual clinical expertise and the best external evidence’. We argue that the formulations and models available in the literature today are modest variations on a common theme and face very similar problems when it comes to risk analysis, which is here understood as a decision procedure comprising a factual assessment of risk, the risk assessment, and the decision what to (...) do based on this assessment, the risk management. Both the early and updated models of evidence-based clinical decisions presented in the writings of Haynes, Devereaux and Guyatt assume that EBM consists of, among other things, evidence from clinical research together with information about patients’ values and clinical expertise. On this A-view, EBM describes all that goes on in a specific justifiable medical decision. There is, however, an alternative interpretation of EBM, the B-view, in which EBM describes just one component of the decision situation and in which, together with other types of evidence, EBM leads to a justifiable clincial decision but does not describe the decision itself. This B-view is inspired by a 100-years older version of EBM, a Swedish standard requiring medical decision-making, professional risk-taking and practice to be in accordance with‘science and proven experience’. In the paper, we outline how the Swedish concept leads to an improved understanding of the way in which scientific evidence and clinical experience can and cannot be integrated in light of EBM. How scientific evidence and clinical experience is integrated influences both the way we do risk assessment and risk management. In addition, the paper sketches the as yet unexplored historical background to VBE and EBM. (shrink)

The concept of vulnerability has been the topic of considerable discussion in research bioethics, largely because of dissatisfaction with early constructions of the concept that were based on subpopulations of research subjects. These subpopulations have attributes likely to undermine their capacity to provide autonomous informed consent: persons who are relatively or absolutely incapable of protecting their own interests through negotiations for informed consent. Several subpopulations were seen as requiring special protections, including children, pregnant women, prisoners, racial minorities, the economically disadvantaged, (...) the very sick, and the institutionalized. Recent years have witnessed the identification of other subpopulations with attributes that could render them vulnerable, as well. For example, the Council for the International Organization of Medical Societies has named such potentially vulnerable groups as the homeless, nursing home residents, patients with incurable diseases, patients in the emergency department, employees, students, and members of communities who are unfamiliar with modern medicine. (shrink)

The potential negative impacts of biological pest control on non-target species have become the focus of a contentious debate. In this article, we use examples from both classical and augmentative biological control of fruit fly pests in Hawaii to address several important factors in assessing non-target risks of fruit fly parasitoids. Several fruit fly parasitoids have been introduced to Hawaii and contribute substantially to the reduction of pest populations in the state's farms and forests. However, an historical lack of host-specificity (...) testing of these parasitoids with non-target species has raised concerns about their impact on non-pest fruit flies, including some flies deliberately introduced for biological control of weeds and others that are endemic Hawaiian species. When developing protocols to assess risks of introduced fruit fly parasitoids, we need first to define an appropriate range of species against which host specificity should be tested. For assessing susceptibility of a non-target species to parasitoids, behavioral tests are as important as suitability tests. Experimental factors, such as host-exposure substrate, absence or presence of preferred hosts, and laboratory vs. natural conditions, are shown to affect the results of host-specificity tests and risk analysis. Still, assessing long-term, indirect ecological impacts of parasitoids and weighing potential risks and benefits in multiple dimensions (besides dollar values) remains a challenge to environmentalists, conservationists, applied ecologists, and biocontrol practitioners. (shrink)

The integration of ethics into the day-to-day work of research and innovation is an important but difficult challenge. However, with the Aachen method for identification, classification and risk analysis of innovation-based problems an approach from an engineering perspective is presented that enables the integration of ethical, legal and social implications into the day-to-day work of R&I practitioners. AMICAI appears in particular capable of providing a procedural guidance for R&I practitioners based on a method established in engineering science, breaking (...) down the object of consideration into partial aspects and prioritizing the innovation-based problems in dependence of potential risk. This enables the user to apply AMICAI continuously during all stages of the research and development process and to analyze and choose between certain sociotechnical alternatives. In this way, problems that affect ethical, legal, and social aspects can be understood, reflected and considered in the mostly technically focused R&D process. The paper gives a general guidance about AMICAI by describing principles and assumptions, providing the steps of analysis and application aids, giving an example application, explaining the necessary adjustments of AMICAI compared to the methodical basis of failure mode, effects, and criticality analysis and discussing the advantages and limits. AMICAI’s simple applications can stimulate interdisciplinary cooperation in the R&D process and be a starting point for the development of an “open RRI risk analysis platform” allowing society to evaluate innovation-based problems. (shrink)

For more than 10 years, Ulrich Beck has dominated discussion of risk issues in the social sciences. We argue that Beck's criticisms of the theory and practise of risk analysis are groundless. His understanding of what risk is is badly flawed. His attempt to identify risk and risk perception fails. He misunderstands and distorts the use of probability in risk analysis. His comments about the insurance industry show that he does not understand (...) some of the basics of that industry. And his assertions about the wrongness of allowing acceptable levels of exposure to toxic chemicals do not stand up to scrutiny. Key Words: Beck • risk analysis • risk perception • probability • insurance. (shrink)

Risks and benefit evaluation for controlled human infection studies, where healthy volunteers are deliberately exposed to infectious agents to evaluate vaccine efficacy, should be explicit, systematic, thorough, and non‐arbitrary. Decision analysis promotes these qualities using four steps: (1) determining explicit criteria and measures for evaluation, (2) identifying alternatives to the study, (3) defining the models used to estimate the measures for each alternative, and (4) running the models to produce the estimates and compare the alternatives. In this paper, we (...) describe how decision analysis might be applied by funders and regulators, as well as by others contemplating the use of novel controlled human infection studies for vaccine development and evaluation. (shrink)

Human resource management risks are due to the failure of employer organization to use relevant human resources reasonably and can result in tangible or intangible waste of human resources and even risks; therefore, constructing a practical early warning model of human resource management risk is extremely important for early risk prediction. The back propagation neural network is an information analysis and processing system formed by using the error back propagation algorithm to simulate the neural function and structure (...) of the human brain, which can handle complex and changeable things that do not have an obvious linear relationship between output results and input factors, so as to find the objective connection between the two. Based on the summary and analysis of previous research works, this article expounded the research status and significance of early warning for human resource management risks, elaborated the development background, current status, and future challenges of the BP neural network, introduced the method and principle of the BP neural network’s connection weight calculation and learning training, performed the risk inducement analysis, index system establishment, and network node selection of human resource management, constructed an early warning model of human resource management risk based on the BP neural network, conducted the risk warning model training and detection based on the BP neural network, and finally carried out a simulation and its result analysis. The study results show that the early warning model of human resource management risk based on the BP network is effective, and this trained and tested BP network risk warning model can be used to conduct early warning empirical research on human resource risks to prevent human resource risks, ensure enterprise’s benign operation, and at the same time play a role in supervision and promotion of market order rectification. (shrink)

This paper examines and analyzes five definitions of ‘existential risk.’ It tentatively adopts a pluralistic approach according to which the definition that scholars employ should depend upon the particular context of use. More specifically, the notion that existential risks are ‘risks of human extinction or civilizational collapse’ is best when communicating with the public, whereas equating existential risks with a ‘significant loss of expected value’ may be the most effective definition for establishing existential risk studies as a legitimate (...) field of scientific and philosophical inquiry. In making these arguments, the present paper hopes to provide a modicum of clarity to foundational issues relating to the central concept of arguably the most important discussion of our times. (shrink)

The paper re-expresses arguments against the normative validity of expected utility theory in Robin Pope (1983, 1991a, 1991b, 1985, 1995, 2000, 2001, 2005, 2006, 2007). These concern the neglect of the evolving stages of knowledge ahead (stages of what the future will bring). Such evolution is fundamental to an experience of risk, yet not consistently incorporated even in axiomatised temporal versions of expected utility. Its neglect entails a disregard of emotional and financial effects on well-being before a particular (...) class='Hi'>risk is resolved. These arguments are complemented with an analysis of the essential uniqueness property in the context of temporal and atemporal expected utility theory and a proof of the absence of a limit property natural in an axiomatised approach to temporal expected utility theory. Problems of the time structure of risk are investigated in a simple temporal framework restricted to a subclass of temporal lotteries in the sense of David Kreps and Evan Porteus (1978). This subclass is narrow but wide enough to discuss basic issues. It will be shown that there are serious objections against the modification of expected utility theory axiomatised by Kreps and Porteus (1978, 1979). By contrast the umbrella theory proffered by Pope that she has now termed SKAT, the Stages of Knowledge Ahead Theory, offers an epistemically consistent framework within which to construct particular models to deal with particular decision situations. A model by Caplin and Leahy (2001) will also be discussed and contrasted with the modelling within SKAT (Pope, Leopold and Leitner 2007). (shrink)

Recent discussions in the just war literature suggest that soldiers have a duty to assume certain risks in order to protect the lives of all innocent civilians. I challenge this principle of risk by arguing that it is justified neither as a principle that guides the conduct of combat soldiers, nor as a principle that guides commanders in the US military. I demonstrate that the principle of risk fails on the first account because it requires soldiers both to (...) violate their strict duty of obedience and loyalty and to exceed their special obligations to protect their fellow comrades, the state, the state's constituents and other protected civilians. I then illustrate that the principle of risk fails on the second account since it conflicts with the commander's primary obligation to protect and promote the welfare and lives of his or her soldiers. I conclude by arguing that we cannot reasonably expect soldiers and commanders to adhere to the principle of risk until there is a radical, institutional-level transformation of militaristic goals, values, strategies, policies, warrior codes and expectations of service members in the US Armed Forces. (shrink)

Public decisions on environmental risk have traditionally been weighed in terms of the principle of efficiency and its methodologies, such as cost-benefit and risk-benefit analysis. These original essays argue for moving beyond the market paradigm toward making policy that incorporates environmental values. Scholars representing a broad range of disciplines present a thorough analysis and methodological investigation of environmental risk and the potential for integrating environmental values into the policymaking process. They address the normative and theoretical (...) roots of environmental risk, describe the distinct domain that exists for environmental values as opposed to economic values, and look at the conflicts between economic and environmental values within the applied context of the NIMBY (not in my back yard) phenomenon. (shrink)

In this paper, we explore the interests of non-shareholder stakeholders in the context of a shareholder risk model. We first differentiate shareholders and nonshareholders with regard to the nature of their risks, their awareness of risks, their abilities to avoid risk, and their abilities to ensure compensation for risk. We then develop a model of measuring the risks facing stakeholders that addresses human risk magnitude and environmental risk magnitude. We conclude with implications for theory and (...) practice. (shrink)

A common finding in the study of emotion and decision making is the tendency for fear and anxiety to decrease risk taking. The current meta-analysis summarises the strength and variability of this...

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large (...) data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis. (shrink)

In this paper I present my reflections on the ethics of science as described by Merton and as actually practiced by scientists and technologists. This ethics was the subject of Kuipers' paper "'Default norms' in Research Ethics" (Kuipers 2001). There is an implicit assumption in this ethics, notably in Merton's norm of communism, that knowledge is always, or unconditionally good, and hence that scientific research, and the dissemination of its results, is unconditionally good. I will give here reasons why scientists (...) are not permitted to proceed, as they actually do, on the basis of this assumption. There is no factual or other binding justification for this assumption, and the activities it gives rise to frequently conflict with the broadly accepted ethical principle of restricted liberty. A recent discussion on the risks and hazards of science and on the issue of relinquishment is presented. What is shown in this paper is that the scientists and technologists participating in this discussion frequently violate core values of science relating to logical and empirical scrutiny and systematic criticism, as mentioned in Merton's norms of universalism, organized skepticism, and disinterestedness. It is concluded that, in order to live up to these values and in order to operate in agreement with broader ethical principles, science should stimulate open and critical discussion on the hazards and negative effects of science and technology, and on the present failure on the part of law and politics to control those hazards and negative effects. Science should also take the possibility of relinquishing certain themes of research seriously as long as such flaws in the systems of law and political decision-making persist. (shrink)

With the arrival of new methods of genome editing, especially CRISPR/cas 9, new perspectives on germline interventions have arisen. Supporters of germ line genome editing claim that the procedure could be used as a means of disease prevention. As a possible life-saving therapy, it provides benefits that outweigh its risks. Opponents of GGE claim that the medical and societal risks, especially the use of GGE for genetic enhancement, are too high. In our paper, we analyze the risks and benefits of (...) GGE. We show that the medical risk on an individual level might be reduced by further research in the near future so that they may be outweighed by the benefits. We also show that the societal risks of the procedure, i.e. genetic enhancement, are manageable by establishing a regulative framework before the GGE is implemented. Since the effects of modifying genes for the genepool of a given population are extremely difficult to model, the medical risks on the population level might be too high. (shrink)

An offshoot of decision analysis, risk-cost-benefit analysis (RCBA) dominates US policymaking regarding science and technology. In this paper a central normative presupposition of RCBA, called "the linearity assumption" is argued against. This is that there is a linear relationship between the actual probability of fatality and the value of avoiding a social risk or the cost of a social risk. The main object of this essay is to show that the presuppositions underlying the linearity assumption (...) are highly questionable. It is maintained that assessors ought to give more consideration to broadening their interpretations of "unit cost" and "societal risk" and to abandoning their claims about linearity. (shrink)

When is it morally acceptable to expose others to risk? Most moral philosophers have had very little to say in answer to that question, but here is a moral philosopher who puts it at the centre of his investigations.

In the age of big data, machine learning models are globally used to execute default risk prediction. Imbalanced datasets and redundant features are two main problems that can reduce the performance of machine learning models. To address these issues, this study conducts an analysis from the viewpoint of different balance ratios as well as the selection order of feature selection. Accordingly, we first use data rebalancing and feature selection to obtain 32 derived datasets with varying ratios of balance (...) and feature combinations for each dataset. Second, we propose a comprehensive metric model based on multimachine learning algorithms to select the best-derived dataset with the optimal balance ratio and feature combination. Finally, the convolutional neural network is trained on the selected derived dataset to evaluate the performance of our approach in terms of type-II error, accuracy, G-mean, and AUC. There are two contributions in this study. First, the optimal balance ratio is found through the classification accuracy, which changes the deficiency of the existing research that samples are imbalanced or the balance ratio is 1 : 1 and ensures the accuracy of the classification model. Second, a comprehensive metric model based on the machine learning algorithm is proposed, which can simultaneously find the best balance ratio and the optimal feature selection. The experimental results show that our method can noticeably improve the performance of CNN, and CNN outperforms the other four commonly used machine learning models in the task of default risk prediction on four benchmark datasets. (shrink)

There is no well-built theory on credit risk measurement and decision analysis for financial big data, and an effective and scientific evaluation system for them has not been formed. A review of them can contribute to grasping the abovementioned topics, understanding current issues, analyzing research problems, mastering research challenges, and predicting future research directions. Besides, this paper points out four research directions of credit risk measurement and decision analysis for financial big data. Moreover, this paper can (...) provide some guidance directions and insights for practitioners, researchers, financial institutions, and government departments who have an interest in complex decision-making in big data. (shrink)