Homo Datumicus : correcting the market for identity data

Effective digital identity systems offer great economic and civic potential. However, unlocking this potential requires dealing with social, behavioural, and structural challenges to efficient market formation. We propose that a marketplace for identity data can be more efficiently formed with an infrastructure that provides a more adequate representation of individuals online. This paper therefore introduces the ontological concept of Homo Datumicus: individuals as data subjects transformed by HAT Microservers, with the axiomatic computational capabilities to transact with their own data at scale. Adoption of this paradigm would lower the social risks of identity orientation, enable privacy preserving transactions by default and mitigate the risks of power imbalances in digital identity systems and markets

Epistemological Foundations for Neuroeconomics

Neuroeconomics is an emerging field crossing neuroscientific data, the use of brain-imaging tools, experimental and behavioral economics, and an attempt at a better understanding of the cognitive assumptions that underlie theoretical predictive economic models. In this paper the authors try two things: 1) To assess the epistemological biases that affect Neuroeconomics as it is currently done. A number of significant experiments are discussed in that perspective. 2) To imagine an original way - apart from what is already being done - to run experiments in brain-imaging that are relevant to the discussion of rationality assumptions at the core of economic theory.Neuroeconomics, Rationality Assumptions, Abduction

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

Divorce: Causes and Effects on Children

This paper investigates “Divorce: Causes and Effects on Children.” Worthy of note is that the fact that, divorce is not an uncommon experience in human history. It is experienced by couples irrespective of their social, religious, academic, political, economic, etc. status. One of the most hit in the saga of divorce are children born into the wedlock where divorce is experienced. The effects of this divorce on children are most often not well considered by the parents who embark on taking the status of divorcees. This becomes the onus of this paper using sociological and psychoanalytical approaches to the study of human institutions to study these effects on children, though not without looking at the causes of divorce. The paper reveals that the effects of divorce on children often are emotional, psychological, economical and religious spheres among others and recommends ways in which these effects can be minimized among children

Marginal contribution, reciprocity and equity in segregated groups: Bounded rationality and self-organization in social networks

We study the formation of social networks that are based on local interaction and simple rule following. Agents evaluate the profitability of link formation on the basis of the Myerson-Shapley principle that payoffs come from the marginal contribution they make to coalitions. The NP-hard problem associated with the Myerson-Shapley value is replaced by a boundedly rational 'spatially' myopic process. Agents consider payoffs from direct links with their neighbours (level 1) which can include indirect payoffs from neighbours' neighbours (level 2) and up to M-levels that are far from global. Agents dynamically break away from the neighbour to whom they make the least marginal contribution. Computational experiments show that when this self-interested process of link formation operates at level 2 neighbourhoods, agents self-organize into stable and efficient network structures that manifest reciprocity, equity and segregation reminiscent of hunter gather groups. A large literature alleges that this is incompatible with self-interested behaviour and market oriented marginality principle in the allocation of value. We conclude that it is not this valuation principle that needs to be altered to obtain segregated social networks as opposed to global components, but whether it operates at level 1 or level 2 of social neighbourhoods. Remarkably, all M>2 neighbourhood calculations for payoffs leave the efficient network structures identical to the case when M=2.

Trust and corruption: escalating social practices?

Escalating social practices spread dynamically, as they take hold. They are selffulfilling and contagious. This article examines two central social practices, trust and corruption, which may be characterized as alternative economic lubricants. Corruption can be a considerable instrument of flexibility while trust may be an alternative to vigilance (or a collective regime of sanctions). Rational equilibrium explanations and psychological accounts of trust and corruption are rejected in favour of a model open to multiple feed-backs. Although there can be too much trust and too little corruption, and (unsurprisingly) too little trust and too much corruption, a state is unattainable in which these forces are in balance. Practices of trust alone can form stable equilibria, but it is claimed that such states are undesirable for economic and moral reasons. By contrast, practices of corruption are inherently unstable. Implications for strategies of control in organizational relations are drawn

Neuroeconomics: Using Neuroscience to Make Economic Predictions

Neuroeconomics seeks to ground economic theory in detailed neural mechanisms which are expressed mathematically and make behavioural predictions. One finding is that simple kinds of economising for life-and-death decisions (food, sex and danger) do occur in the brain as rational theories assume. Another set of findings appears to support the neural basis of constructs posited in behavioural economics, such as a preference for immediacy and nonlinear weighting of small and large probabilities. A third direction shows how understanding neural circuitry permits predictions and causal experiments which show state-dependence of revealed preference – except that states are biological and neural variables

Formal certification and compliance for run-time service environments

With the increased awareness of security and safety of services in on-demand distributed service provisioning (such as the recent adoption of Cloud infrastructures), certification and compliance checking of services is becoming a key element for service engineering. Existing certification techniques tend to support mainly design-time checking of service properties and tend not to support the run-time monitoring and progressive certification in the service execution environment. In this paper we discuss an approach which provides both design-time and runtime behavioural compliance checking for a services architecture, through enabling a progressive event-driven model-checking technique. Providing an integrated approach to certification and compliance is a challenge however using analysis and monitoring techniques we present such an approach for on-going compliance checking