The increased use of automated systems in the public sector has led to two types of processes, fully automated decision making and humans making decisions assisted by automated decision support systems (ADSS). While having a human in the loop is often motivated by having them act as a “safeguard” for imperfect automated systems, humans themselves are not perfect decision makers. Automation bias, a tendency to agree with the recommendations of automated systems even when they are wrong, is one problem facing humans using ADSS. Mainly found in monitoring tasks such as autopilots, it has also been studied in clinical decision support systems. The aim of this systematic review is to investigate whether automation bias poses a risk for ADSS in the public sector, and to identify possible moderators. Thirteen studies were included. By doing a narrative synthesis of the included studies I found mixed results for the existence of automation bias. While there is a lack of strong evidence for automation bias, even low levels could result in consequences for the public sector as these are decisions that impact citizens' everyday life. A number of moderators are identified and suggestions for system designers are made. / En ökning av automatiserade system inom offentlig sektor har lett till två typer av processer, helt automatiserade beslut och människor som tar beslut stödda av automatiserade beslutsstöd. Att ha en människa i processen är ofta motiverat av att använda dem som ett skydd mot bristfälliga automatiserade system, men människor är i sig själva inte perfekta beslutstagare. Automation bias, en tendens att följa rekommendationer från automatiserade system även när de är inkorrekta, är ett problem för människor som använder automatiserade system. Det har främst studerats i autopiloter, men också i kliniska beslutsstöd. Syftet med denna systematiska litteraturöversikt var att undersöka om automation bias är en risk för automatiserade beslutsstöd i offentlig sektor, och att identifiera möjliga moderatorer. Tretton studier inkluderades. Genom att genomföra en narrativ syntes fann jag blandade slutsatser gällande automation bias. Samtidigt som det finns begränsade starka bevis för automation bias, kan även de nivåerna resultera i konsekvenser för offentlig sektor då de tar beslut som påverkar befolkningens vardag. Ett antal moderatorer identifierades och förslag till systemdesigners presenteras.

Yes / The race against ‘Digital Darwinism’ in public sector had caused failures of several high profile large-scale Digitally Enabled Service Transformation (DEST) projects. While technical and managerial issues are often emphasised as the factors underpinning such failures, the vital role of key actors and the interplay between these actors and structures is underplayed when examining the causes of DEST failure. To enable a richer understanding of DEST, this paper proposes an analytical lens combining Institutional Theory (IT) and Structuration Theory (ST) to explore the case of ‘Universal Credit’, a very large and ambitious DEST project in the UK. Analysis reveals that the institutional actors and structures played significant roles in the transformation process. Albeit governing the actors’ actions, institutional structures are shaped through actions that are influenced by knowledge, power and norms. Hence, recognising and addressing these subliminal factors are critical to promote actions that can facilitate DEST success. The contributions of this case study are two-folds. Theoretically, it provides a distinctive conceptual approach to study DEST; and practically, the lessons help in signposting better managerial practices.

No / "Enabling Multichannel Participation through ICT Adaptations for Participatory Budgeting ICT-enabled platform” (EMPATIA) is a multi-channel participatory budgeting (PB) platform that represents a significant social innovation process of democratic deliberation and decision-making, involving citizens within complex public-institution structures. EMPATIA was targeted to deliver socio-economic and political benefits, such as enhancing citizen-government engagement, increasing public value through PB process, promoting ‘inclusiveness’ among the marginalized groups of citizens, and impeding political discontent that underpins distrust and skepticism towards the government. The attainment of these benefits will be driven by the EMPATIA's performance. Hence, a performance measurement tools is needed to enable assessment of EMPATIA, empirically. With an aim to propose an integrated performance evaluation metrics, this study presents a set of assessment criteria for multi-channel digitally enabled PB service platforms – especially EMPATIA. Findings from a qualitative, multi-strategies research approach suggest that the metrics should include five key technical and non-technical performance indicators, to be used as basis for the development of future evaluation instruments. Of major signposts, the metrics would inform key performance aspects to be considered during the PB platform development, and evaluated to indicate the PB platform performance.

Yes / Purpose – Blockchain is one of the most significant emerging technologies that is set to transform many aspects of industry and society. However, it has several major technical, social, legal, environmental and ethical complexities that offer significant challenges for mainstream use within the public sector. The Covid-19 pandemic has compelled many public sector employees to work remotely, highlighting a number of challenges to blockchain adoption within the Indian context signifying the pertinence of this research topic in the post-pandemic era. This study offers insight to researchers and policymakers alike on how such challenges are interdependent within this important subject. Design/methodology/approach – We explored 16 unique sets of challenges selected from the literature and gathered data from nine experts from government settings, healthcare and education sectors and academia who have significant knowledge and experience of blockchain implementation and use in their respective organisations. The implementation of Interpretive Structural Modelling (ISM) and MICMAC provided a precise set of driving, linkage and dependent challenges that were used to formulate the framework. Findings – The developed ISM framework is split into six different levels. The results suggest that the bottom level consists of challenges such as ‘Lack of standards (C9)’ and ‘Lack of validation (C10)’ form the foundation of the hierarchical structure of blockchain adoption. However, the topmost level consists of a highly dependent challenge termed ‘adoption of blockchain in the public sector (C16)’. The research filters the selected set of five challenges to develop a parsimonious model and formulated six propositions to examine the impact of ‘lack of standard (C9)’, ‘lack of validation (C10)’ on ‘security issues (C3)’ and ‘privacy concerns (C2)’, which eventually determine individuals’ ‘reluctance to use blockchain technology (C12)’. Originality/Value – This research fills a key gap in exiting research by exploring the key challenges in blockchain adoption within the public sector by developing a valuable framework to model this important topic. To the best of our knowledge, this is the first paper to address these challenges and develop a parsimonious model for challenges of blockchain adoption in the public sector settings.