The Paradox of Human Expertise: Why Experts Can Get It Wrong

Expertise is correctly, but one-sidedly, associated with special abilities and enhanced performance. The other side of expertise, however, is surreptitiously hidden. Along with expertise, performance may also be degraded, culminating in a lack of flexibility and error. Expertise is demystified by explaining the brain functions and cognitive architecture involved in being an expert. These information processing mechanisms, the very making of expertise, entail computational trade-offs that sometimes result in paradoxical functional degradation. For example, being an expert entails using schemas, selective attention, chunking information, automaticity, and more reliance on top-down information, all of which allow experts to perform quickly and efficiently; however, these very mechanisms restrict flexibility and control, may cause the experts to miss and ignore important information, introduce tunnel vision and bias, and can cause other effects that degrade performance. Such phenomena are apparent in a wide range of expert domains, from medical professionals and forensic examiners, to military fighter pilots and financial traders

An Exploratory Study of Patient Falls

Debate continues between the contribution of education level and clinical expertise in the nursing practice environment. Research suggests a link between Baccalaureate of Science in Nursing (BSN) nurses and positive patient outcomes such as lower mortality, decreased falls, and fewer medication errors. Purpose: To examine if there a negative correlation between patient falls and the level of nurse education at an urban hospital located in Midwest Illinois during the years 2010-2014? Methods: A retrospective crosssectional cohort analysis was conducted using data from the National Database of Nursing Quality Indicators (NDNQI) from the years 2010-2014. Sample: Inpatients aged ≥ 18 years who experienced a unintentional sudden descent, with or without injury that resulted in the patient striking the floor or object and occurred on inpatient nursing units. Results: The regression model was constructed with annual patient falls as the dependent variable and formal education and a log transformed variable for percentage of certified nurses as the independent variables. The model overall is a good fit, F (2,22) = 9.014, p = .001, adj. R2 = .40. Conclusion: Annual patient falls will decrease by increasing the number of nurses with baccalaureate degrees and/or certifications from a professional nursing board-governing body

From Negative to Positive Algorithm Rights

We consider this issue here and suggest that the current calls for a negative right to be free from AI could very well transform over time into positive claims that demand the use of algorithmic tools by government officials. In Part I, we begin by sketching the current landscape surrounding the adoption of AI by government. That landscape is characterized by strong activist and scholarly voices expressing a pronounced aversion to the use of digital algorithms—and taking a decidedly negative rights tone. In Part II, we show that, although aversion to complex technology might be understandable, that aversion is neither inevitable nor impossible to overcome. We offer several examples of advanced technologies and analytic techniques that in the past have emerged in the face of significant criticism, but which have come to be widely accepted. In fact, there now exists an affirmative expectation—even at times a legal one—that government should use these technologies when making consequential decisions affecting people’s interests. Given the possibility of legal and, more broadly, public insistence on the use of at least certain kinds of advanced technologies, we put forward in Part III a set of factors that may help lead eventually to widespread acceptance of algorithmic technologies similar to the acceptance of the technologies discussed in Part II. We suggest that a path forward exists that might build a general acceptance of the use of algorithmic tools by governmental entities, a path that would represent a shift from present-day calls for negative-rights protections against AI to eventual positive-rights expectations that good government practices routinely involve the use of AI. This abstract has been taken from the authors\u27 introduction

From Negative to Positive Algorithm Rights

Artificial intelligence, or “AI,” is raising alarm bells. Advocates and scholars propose policies to constrain or even prohibit certain AI uses by governmental entities. These efforts to establish a negative right to be free from AI stem from an understandable motivation to protect the public from arbitrary, biased, or unjust applications of algorithms. This movement to enshrine protective rights follows a familiar pattern of suspicion that has accompanied the introduction of other technologies into governmental processes. Sometimes this initial suspicion of a new technology later transforms into widespread acceptance and even a demand for its use. In this paper, we show how three now-accepted technologies—DNA analysis, breathalyzers, and radar speed detectors—traversed a path from initial resistance to a positive right that demands their use. We argue that current calls for a negative right to be free from digital algorithms may dissipate over time, with the public and the legal system eventually embracing, if not even demanding, the use of AI. Increased recognition that the human-based status quo itself leads to unacceptable errors and biases may contribute to this transformation. A negative rights approach, after all, may only hamper the development of technologies that could lead to improved governmental performance. If AI tools are allowed to mature and become more standardized, they may also be accompanied by greater reliance on qualified personnel, robust audits and assessments, and meaningful oversight. Such maturation in the use of AI tools may lead to demonstrable improvements over the status quo, which eventually might well justify assigning a positive right to their use in the performance of governmental tasks

Blockchain technology to improve supply chain management - a systematic literature review

This study followed the systematic literature review approach to analyse how blockchain technology can improve supply chain management and to promote a future research agenda. The search was carried out at Web of Science Core Collection between September 2019 and February 2020 by using the keywords “blockchain” AND “supply chain” OR “blockchain” AND “logistics” in the title. In this review 127 studies were identified for screening and a final sample of 67 studies met the inclusion criteria and were analysed to answer the research questions. After examining the selected studies, our findings uncover a range of approaches showing how blockchain can enhance the supply chain management and point out which sectors are most likely to benefit from its implementation. This study contributes to the existing literature by systematising the most relevant information on blockchain implementation in supply chains. In addition, the findings of this study also provide managers and researchers with insights about the likely consequences of blockchain adoption in various sectors. Although there are already some literature reviews on blockchain technology in the supply chain management, this is one of the first studies that brings together the main issues focused on the consequences of blockchain adoption in the supply chain management.A gestão da cadeia de abastecimento está a passar por um processo de digitalização das suas operações justificada pela Quarta Revolução Industrial (Indústria 4.0) que prevê a adoção de novas tecnologias com o objetivo de reduzir custos operacionais, aumentar a eficiência da cadeia de abastecimento e agregar valor aos produtos e serviços. Ferramentas tecnológicas como a internet das coisas (IoT), identificação por radiofrequência (RFID) e Big Data, estão a ser utilizadas na melhoria dos controlos de produção, compra, procura, na tomadas de decisões dos gestores, entretanto, a recente tecnologia blockchain tem chamado atenção de pesquisadores e especialistas devido ao seu potencial transformador nos negócios e principalmente na gestão da cadeia de abastecimento. Por este motivo, este estudo propõe uma revisão sistemática de literatura com o objetivo de analisar como a tecnologia blockchain pode melhorar a gestão da cadeia de abastecimento e propor uma agenda de investigação para o futuro. A pesquisa foi realizada na base de dados Web of Science Core Collection entre setembro de 2019 e fevereiro de 2020 usando as palavras-chave "blockchain" E "supply chain" OU "blockchain" E "logistics" no título. O critério de seleção dos artigos considerou apenas estudos revistos por pares, anais de conferência e livros nos idiomas inglês, espanhol, francês e português. A seleção dos estudos ocorreu em duas etapas. Na primeira etapa, foram analisados títulos e resumos. Na segunda etapa, foi realizada a leitura integral dos estudos que não foram excluídos na primeira fase. Os critérios de exclusão foram: artigos de revisão de literatura, relatórios, estudos focados em informações técnicas, estudos que enfatizaram outras tecnologias (IoT, RFID), gestão financeira da cadeia de abastecimento e/ou estudos relacionados com bitcoins. Os artigos que preencheram um desses critérios foram excluídos com justificativa. Embora tenhamos excluído artigos de revisão de literatura, esses documentos ainda foram utilizados para identificar estudos-chave que não haviam sido capturados da base de dados Web of Science. Por fim, nesta revisão foram identificados 127 estudos para triagem e uma amostra final de 67 estudos atendeu aos critérios de inclusão e foram analisados para responder às perguntas da pesquisa. As perguntas a que a pesquisa teve por objetivo responder foram: quais os benefícios e riscos da tecnologia blockchain; quais os setores que já adotaram a tecnologia blockchain na gestão da cadeia de abastecimento e sua fase de implementação; quais as características das empresas que utilizam a tecnologia; quais são os fatores facilitadores e barreiras para a adoção da tecnologia blockchain nas empresas; qual a influência da tecnologia blockchain na garantia da sustentabilidade da cadeia de abastecimento dentro da estratégia organizacional e dos níveis operacionais; como avaliar o desempenho da tecnologia blockchain na gestão da cadeia de abastecimento. Os estudos selecionados apontam que a partir de 2017 houve um aumento expressivo de estudos relacionados ao uso da tecnologia blockchain na cadeia de abastecimento. Os Estados Unidos, China e Índia são os países com a maior percentagem de publicações sobre o tema e representam aproximadamente 44% do total. Os estudos foram publicados em jornais especializados em sistema de produção e processos, engenharia industrial, tecnologia, gestão, logística, cadeia de abastecimento e sustentabilidade. Quanto aos benefícios e riscos da adoção da tecnologia blockchain, os estudos indicam que a transparência dos dados, rastreabilidade e a redução dos custos operacionais são um dos maiores benefícios da adoção da tecnologia blockchain na cadeia de abastecimento, enquanto a escalabilidade e interoperabilidade foram identificados com os maiores riscos/limitações da implantação da tecnologia. No que tange aos fatores facilitadores da adoção da tecnologia blockchain, a gestão de topo apresenta-se como agente principal no incentivo à adoção do blockchain nas organizações, além disso, a perceção de utilização da tecnologia pelos funcionários também influencia o sucesso de implantação da tecnologia blockchain. Outras características que afetam a adoção da tecnologia são a infraestrutura das empresas, políticas governamentais e a cultura do país, entretanto esses fatores tendem a ter níveis diferentes de acordo com o país onde a empresa está instalada. No que diz respeito aos fatores que dificultam a implantação do blockchain nas organizações, são apontados a falta de conhecimento da tecnologia blockchain e dos seus potenciais benefícios, a existência de um número reduzido de aplicações do blockchain nas empresas, a coordenação e comprometimento dos parceiros de negócios na resolução de problemas e no tratamento de dados, fatores externos, como a legislação e incentivos governamentais. Após examinar os estudos selecionados, a nossa análise revela uma série de abordagens que mostram como a blockchain pode melhorar a gestão da cadeia de abastecimento e identifica os setores mais propensos a retirar benefícios de sua implementação. A indústria de alimentos e a indústria farmacêutica são apontados como os setores com maior vantagem na adoção do blockchain devido a criticidade dos seus produtos, a procura crescente por informações referente a proveniência dos bens e seu alto valor agregado. O perfil das organizações que adotaram a tecnologia blockchain são geralmente multinacionais de grande e médio porte, com capilaridade de parceiros de negócios, grande volume de produção e alto valor agregado aos seus bens. Quanto a sustentabilidade, a tecnologia blockchain pode influenciar, através da transparência e rastreabilidade dos produtos, na redução da produção de lixo e das emissões de carbono no meio ambiente, no controlo das leis e práticas laborais, evitando-se trabalho escravo e, relacionado com as questões económicas, redução dos custos com auditorias, controlo de pedidos de compra, produção e procura. Os indicadores de performance, de acordo com os estudos revistos, podem ser melhorados com a utilização da tecnologia blockchain, promovendo novas métricas sustentáveis baseadas na rastreabilidade e na transparência dos dados. Apesar da fase inicial da tecnologia blockchain, alguns estudos propõem indicadores que avaliam a eficiência da cadeia de abastecimento após a adoção do blockchain, como o tempo de processamento das transações, a utilização de recursos (água, energia elétrica) e níveis de emissão de carbono. Embora já existam algumas revisões de literatura sobre a tecnologia blockchain na gestão da cadeia de abastecimento, este é um dos primeiros estudos que reúne questões importantes focadas nas consequências da adoção do blockchain na gestão. Além disso, os resultados deste estudo fornecem implicações para a gestão e para a teoria sobre as prováveis consequências da adoção de blockchain em vários setores da economia

Preface

DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018.DAMSS-2018 is the jubilee 10th international workshop on data analysis methods for software systems, organized in Druskininkai, Lithuania, at the end of the year. The same place and the same time every year. Ten years passed from the first workshop. History of the workshop starts from 2009 with 16 presentations. The idea of such workshop came up at the Institute of Mathematics and Informatics. Lithuanian Academy of Sciences and the Lithuanian Computer Society supported this idea. This idea got approval both in the Lithuanian research community and abroad. The number of this year presentations is 81. The number of registered participants is 113 from 13 countries. In 2010, the Institute of Mathematics and Informatics became a member of Vilnius University, the largest university of Lithuania. In 2017, the institute changes its name into the Institute of Data Science and Digital Technologies. This name reflects recent activities of the institute. The renewed institute has eight research groups: Cognitive Computing, Image and Signal Analysis, Cyber-Social Systems Engineering, Statistics and Probability, Global Optimization, Intelligent Technologies, Education Systems, Blockchain Technologies. The main goal of the workshop is to introduce the research undertaken at Lithuanian and foreign universities in the fields of data science and software engineering. Annual organization of the workshop allows the fast interchanging of new ideas among the research community. Even 11 companies supported the workshop this year. This means that the topics of the workshop are actual for business, too. Topics of the workshop cover big data, bioinformatics, data science, blockchain technologies, deep learning, digital technologies, high-performance computing, visualization methods for multidimensional data, machine learning, medical informatics, ontological engineering, optimization in data science, business rules, and software engineering. Seeking to facilitate relations between science and business, a special session and panel discussion is organized this year about topical business problems that may be solved together with the research community. This book gives an overview of all presentations of DAMSS-2018

Assessing the impact of e-learning on decision-making to reduce health risks: Perceptions from UCT's pesticide risk management cohort

Includes bibliographical referencesThere is a need to build the capacity of professionals in low- to middle- income countries (LMICs) in order to reduce pesticide risks on human and environmental health. To address these risks, the University of Cape Town (UCT) introduced the Post Graduate Diploma in Pesticide Risk Management (DPRM). This programme utilises a mixed teaching mode including an e-learning component which includes virtual seminars/discussion forums. The DPRMs' discussion forum aimed to strengthen skills in managing and reducing pesticide risks. Due to the shortage of skilled professionals in LMICs, e-learning can facilitate the on-going training and skills development in pesticide management to address pesticide related challenges. The study focus was on evaluating the impact of the DPRMs' e-learning Discussion Forum bi-monthly sessions on the decision-making processes of professionals in LMICs working in pesticide risk management. The sample for this study was obtained from a population of working professionals, who either completed or were currently enrolled for the DPRM programme (N=37). Twenty-two participants completed the online questionnaire anonymously. These participants were employed by governments, non-governmental organizations (NGOs), research institutes and private companies in Africa and Fiji. This mini-dissertation is divided into four parts. The protocol (Part A) provides the study justification and describes the methodology for collecting the data and the analysis thereof. The literature review (Part B) describes e-learning and how it relates to capacity building of pesticide risk management (PRM) professionals in LMICs countries. It looks at the challenges of implementing and maintaining successful capacity building and the role e-learning plays. The manuscript of a journal ready article (Part C) presents the research findings on the perceived effectiveness of the e-learning based DPRM discussion forum and whether it aided PRM professionals in making better decisions. There are four appendices (Part D) which include the questionnaire, consent form, ethical approval and instructions for writing the manuscript. The study found that participants reported improved application of information gained through e-learning in a practical and effective manner, thereby improving their skills for real world scenarios. Overall benefits acknowledged by participants included establishing a knowledge resource, improved communication with colleagues and stakeholders, as well as improved ability for knowledge application in their work and pesticide use in context. An important finding was that just over half of respondents (55%) felt that they were able to contribute to policy change in their countries as a result of the discussion forum. Unfortunately, no statistical significance could be established between variables due to the limited sample size. It is recommended that a follow-up study with a larger sample be conducted, to establish whether the discussion forum has a long-term and sustainable impact in decision- making processes and policy implementation

Technology management in the effective implementation of change

Organizational fitness is often achieved by making changes in business operations. These changes frequently involve the use of a new technology. The effective implementation of change is achieved by examining the benefits and challenges of technology management when making decisions. Important elements for consideration in technology management are technology evaluation, integration, planning, implementation, training, and change. A solution is proposed to combine and encompass all the elements of technology management to allow for the positive aspects and avoid the negative aspects of change implementation. The tool consists of principles to be addressed for each element