Ethical Implications of Predictive Risk Intelligence

open access articleThis paper presents a case study on the ethical issues that relate to the use of Smart Information Systems (SIS) in predictive risk intelligence. The case study is based on a company that is using SIS to provide predictive risk intelligence in supply chain management (SCM), insurance, finance and sustainability. The pa-per covers an assessment of how the company recognises ethical concerns related to SIS and the ways it deals with them. Data was collected through a document review and two in-depth semi-structured interviews. Results from the case study indicate that the main ethical concerns with the use of SIS in predictive risk intelli-gence include protection of the data being used in predicting risk, data privacy and consent from those whose data has been collected from data providers such as so-cial media sites. Also, there are issues relating to the transparency and accountabil-ity of processes used in predictive intelligence. The interviews highlighted the issue of bias in using the SIS for making predictions for specific target clients. The last ethical issue was related to trust and accuracy of the predictions of the SIS. In re-sponse to these issues, the company has put in place different mechanisms to ensure responsible innovation through what it calls Responsible Data Science. Under Re-sponsible Data Science, the identified ethical issues are addressed by following a code of ethics, engaging with stakeholders and ethics committees. This paper is important because it provides lessons for the responsible implementation of SIS in industry, particularly for start-ups. The paper acknowledges ethical issues with the use of SIS in predictive risk intelligence and suggests that ethics should be a central consideration for companies and individuals developing SIS to create meaningful positive change for society

Defectors cannot be detected during"small talk" with strangers.

To account for the widespread human tendency to cooperate in one-shot social dilemmas, some theorists have proposed that cooperators can be reliably detected based on ethological displays that are difficult to fake. Experimental findings have supported the view that cooperators can be distinguished from defectors based on "thin slices" of behavior, but the relevant cues have remained elusive, and the role of the judge's perspective remains unclear. In this study, we followed triadic conversations among unacquainted same-sex college students with unannounced dyadic one-shot prisoner's dilemmas, and asked participants to guess the PD decisions made toward them and among the other two participants. Two other sets of participants guessed the PD decisions after viewing videotape of the conversations, either with foreknowledge (informed), or without foreknowledge (naïve), of the post-conversation PD. Only naïve video viewers approached better-than-chance prediction accuracy, and they were significantly accurate at predicting the PD decisions of only opposite-sexed conversation participants. Four ethological displays recently proposed to cue defection in one-shot social dilemmas (arms crossed, lean back, hand touch, and face touch) failed to predict either actual defection or guesses of defection by any category of observer. Our results cast doubt on the role of "greenbeard" signals in the evolution of human prosociality, although they suggest that eavesdropping may be more informative about others' cooperative propensities than direct interaction

Seasonal Climate Forecasts and Risk Management Among Georgia Farmers

Recent increases in the scientific robustness of seasonal climate forecasts have not led to substantial changes in farmers’ risk management strategies of actors, largely because there is poor integration of scientific forecasting into farmers’ decision-making processes. The goal of the research presented here is to explore the potentials and constraints for farmers’ application of seasonal climate forecasts through an analysis of the cultural contexts of their decision-making and information use. Semi-structured interviews were conducted with 38 farmers in southern Georgia, examining their approaches, risk-management, to livelihood goals and strategies, and interactions with weather and climate information. Findings indicate that farmers’ management of risks associated with climate variability is embedded within a broad array of social factors, including subjective construction of social and personal identities, goals, and values. These cultural contexts affect the ways that farmers interpret and might apply seasonal climate forecasts to agricultural decisions. These findings indicate that, rather than simply acting as a technical information input, seasonal climate forecasts and forecasters must gradually work theirway into farmers’ trusted social networks before their potential as risk management tools will be realized. Furthermore, while seeking to produce scientific information to support farmers’ adaptive practices, scientists themselves must adapt their own practices to better fit a coproduction of knowledge approach

Extending the design process into the knowledge of the world

Research initiatives throughout history have shown how a designer typically makes associations and references to a vast amount of knowledge based on experiences to make decisions. With the increasing usage of information systems in our everyday lives, one might imagine an information system that provides designers access to the ‘architectural memories’ of other architectural designers during the design process, in addition to their own physical architectural memory. In this paper, we discuss how the increased adoption of semantic web technologies might advance this idea. We briefly discuss how such a semantic web of building information can be set up, and how this can be linked to a wealth of information freely available in the Linked Open Data (LOD) cloud

Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods

Commercialization of non-timber forest products (NTFPs) has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed

De facto capital mobility, equality, and tax policy in open economies

This paper attempts at giving theoretical and empirical answers to the remaining puzzles in the literature on tax competition: the persistently high tax rates on mobile capital and the large variation in domestic tax systems. I argue that governments face a political trilemma, in which they cannot maintain the politically optimal level of public good provision, reduce capital taxes to competitive levels and implement a political support-maximizing mix of tax rates on capital and labour simultaneously. In particular, while legal restriction on capital flows have been eliminated by virtually all OECD countries, de facto capital mobility falls short of being perfect. Limits to full capital mobility result from ownership structures: the higher the concentration of capital, the higher the de facto mobility of capital and the lower the equilibrium tax rate. Second, the demand for the provision of public goods further constraints governments’ choices of the capital tax rate. If revenue from taxation of mobile factors declines, politicians cannot necessarily cut back spending without losing political support. Policy makers, accordingly, do not face a simple optimization problem when deciding on capital taxation. Rather, they have to choose a tax system which allows them to supply an appropriate level of public goods. Policy makers finally face a trade-off resulting from the redistributive conflict between capital-owners and workers. This conflict does not resemble a mere zero-sum game, because lower levels of capital taxation are likely to improve aggregate welfare, but the decision on capital taxation also cannot be analyzed in isolation from the distributive effects of reducing taxes on mobile factors. This political logic of tax competition generates important predictions which are tested empirically for 23 OECD countries over 30 years within a spatial econometrics framework