No App is an Island: Collective Action and Sustainable Development Goal-Sensitive Design.

The transformation to the Digital Society presents a challenge to engineer ever more complex socio-technical systems in order to address wicked societal problems. Therefore, it is essential that these systems should be engineered with respect not just to conventional functional and non-functional requirements, but also with respect to satisfying qualitative human values, and assessing their impact on global challenges, such as those expressed by the UN sustainable development goals (SDGs). In this paper, we present a set of sets of design principles and an associated meta-platform, which focus design of socio-technical systems on the potential interaction of human and artificial intelligence with respect to three aspects: firstly, decision-support with respect to the codification of deep social knowledge; secondly, visualisation of community contribution to successful collective action; and thirdly, systemic improvement with respect to the SDGs through impact assessment and measurement. This methodology, of SDG-Sensitive Design, is illustrated through the design of two collective action apps, one for encouraging plastic re-use and reducing plastic waste, and the other for addressing redistribution of surplus food. However, as with the inter-connectedness of the SDGs, we conclude by arguing that the inter-connectedness of the Digital Society implies that system development cannot be undertaken in isolation from other systems

No App is an Island: Collective Action and Sustainable Development Goal-Sensitive Design

The transformation to the Digital Society presents a challenge to engineer ever more complex socio-technical systems in order to address wicked societal problems. Therefore, it is essential that these systems should be engineered with respect not just to conventional functional and non-functional requirements, but also with respect to satisfying qualitative human values, and assessing their impact on global challenges, such as those expressed by the UN sustainable development goals (SDGs). In this paper, we present a set of sets of design principles and an associated meta-platform, which focus design of socio-technical systems on the potential interaction of human and artificial intelligence with respect to three aspects: firstly, decision-support with respect to the codification of deep social knowledge; secondly, visualisation of community contribution to successful collective action; and thirdly, systemic improvement with respect to the SDGs through impact assessment and measurement. This methodology, of SDG-Sensitive Design, is illustrated through the design of two collective action apps, one for encouraging plastic re-use and reducing plastic waste, and the other for addressing redistribution of surplus food. However, as with the inter-connectedness of the SDGs, we conclude by arguing that the inter-connectedness of the Digital Society implies that system development cannot be undertaken in isolation from other systems

Does My Smart Device Provider Care About My Privacy? Investigating Trust Factors and User Attitudes in IoT Systems

With the wide spread of IoT devices, smart systems gain more and more control over personal data and daily lives of their users. This control, however, can easily be misused, either by system providers themselves acting in bad faith, or by external attackers. Implementing proper measures towards security and privacy protection of smart systems, therefore, becomes of critical importance. In this paper we present a study to investigate beliefs among end users, whether the smart system providers are both capable and motivated to implement such measures. For this purpose, we conduct an online survey of 98 participants from the UK, which we analyse using quantitative and qualitative methods. Our results show that users’ trust in proper security and privacy protection in smart systems is influenced by a multitude of factors such as information about concrete technologies and privacy policies of the systems, but also information about the company such as its reputation or geographical location. We conclude that transparency by companies, regarding both the technologies behind the concrete system and the general practices of the company itself, is a crucial factor in ensuring end user confidence

Values, axial currencies, and computational axiology: digital currencies can do more than buy stuff

Eleven to twelve thousand years ago, early humans lived in small communities with no discernible hierarchy. The "agrarian revolution" resulted in communities growing on such a scale that mechanisms of self-organization - e.g., for monitoring, keeping order, and ensuring a "satisfactory" allocation of resources - were no longer efficient or effective. However, the concurrent "cognitive" revolution resulted in the faculty of imagination, in particular, the imagination of rules, to solve such problems

Knowledge management for self-organised resource allocation

Many instances of socio-technical systems in the digital society and digital economy require some form ofself-governance. Examples include community energy systems, peer production systems, participatory sensingapplications, and shared management of communal living areas or workspace. Such systems have severalfeatures in common, of which three are that they arerule-oriented,self-organisingandvalue-sensitive, and inoperation, this combination of features entails self-modification of the rules in order to satisfice a changeableset of values. This presents a fundamental dilemma for systems design. On the one hand, the system mustbe sufficiently unrestricted (resilient, flexible) to enable a diverse group but with a shared set of congruentvalues to achieve their joint purposes in collective action situations. On the other hand, it must be sufficientlyrestricted (stable, robust) to prevent a subset of the group from exploiting self-determination ‘against itself’ andusurp control of the system for the benefit of their own narrow interests. To address this problem, we considera study of classical Athenian democracy which investigates how the governance model of the city-stateflourished. The work suggests that exceptionalknowledge management, i.e. making information available forsocially productive purposes, played a crucial role in sustaining its democracy for nearly 200 years, by creatingprocesses for aggregation, alignment and codification of knowledge. We therefore examine the propositionthat some properties can be generalised to resolve the rule-restriction dilemma by establishing a set ofdesignprinciplesintended to make knowledge management processes open, inclusive, transparent and effective inself-governed social technical systems. We operationalise three of these principles in the context of a collectiveaction situation, namely self-organised common-pool resource allocation, and present the results of a series ofexperiments showing how knowledge management processes can be used to obtain robust solutions for theperception of fairness, allocation decision and punishment mechanisms. By applying this operationalisationof the design principles for knowledge management processes as a complement to institutional approaches togovernance, we demonstrate empirically how it can satisfice shared values, distribute power fairly, and apply“common sense” in dealing with rule violations. We conclude by arguing that this approach to the designof socio-technical systems can provide a balance between restricted and unrestricted self-modification ofconventional rules, and can thus provide the foundations for sustainable and democratic self-governance insocio-technical systems

A Noninvasive Brain-Computer Interface for Real-Time Speech Synthesis: The Importance of Multimodal Feedback.

We conducted a study of a motor imagery brain-computer interface (BCI) using electroencephalography to continuously control a formant frequency speech synthesizer with instantaneous auditory and visual feedback. Over a three-session training period, sixteen participants learned to control the BCI for production of three vowel sounds (/ textipa i/ [heed], / textipa A/ [hot], and / textipa u/ [who'd]) and were split into three groups: those receiving unimodal auditory feedback of synthesized speech, those receiving unimodal visual feedback of formant frequencies, and those receiving multimodal, audio-visual (AV) feedback. Audio feedback was provided by a formant frequency artificial speech synthesizer, and visual feedback was given as a 2-D cursor on a graphical representation of the plane defined by the first two formant frequencies. We found that combined AV feedback led to the greatest performance in terms of percent accuracy, distance to target, and movement time to target compared with either unimodal feedback of auditory or visual information. These results indicate that performance is enhanced when multimodal feedback is meaningful for the BCI task goals, rather than as a generic biofeedback signal of BCI progress

Improving Novelty Search with a Surrogate Model and Accuracy Objectives to Build High-Performing Ensembles of Classifiers

Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using gradient descent to train evolved architectures during the search can be computationally prohibitive. We have proposed a method to overcome this limitation by using a surrogate model which estimates the behavioural distance between two neural network architectures, required to calculate novelty scores. This has demonstrated a speedup of 10 times over previous work, significantly improving on previous reported results on three benchmark datasets from Computer Vision—CIFAR-10, CIFAR-100, and SVHN. This method makes an explicit search for diversity considerably more tractable for the same bounded resources. Here we investigate a range of search methods that span the full spectrum of favouring accuracy, diversity, or different combinations of both. Surprisingly, we show that multiple unique combinations between a diversity metric and accuracy give rise to similar results. This enables us to posit the existence of a diversity-accuracy duality in ensembles of classifiers, which suggests that there might not be a need to find a trade-off between the two