Machine Learning System Development in Information Systems Development Praxis

Advancements in hardware and software have propelled machine learning (ML) solutions to become vital components of numerous information systems. This calls for research on the integration and evaluation of ML development practices within software companies. To investigate these issues, we conducted expert interviews with software and ML professionals. We structured the interviews around information systems development (ISD) models, which serve as conceptual frameworks that guide stakeholders throughout software projects. Using practice theory, we analyzed how software professionals perceive ML development within the context of ISD models and identified themes that characterize the transformative impact of ML development on these conceptual models. Our findings show that developer-driven conceptual models, such as DevOps and MLOps, have been embraced as common frameworks for developers and management to understand and guide the ML development processes. We observed ongoing shifts in predefined developer roles, wherein developers are increasingly adopting ML techniques and tools in their professional work. Overall, our findings underscore that ML technologies are becoming increasingly prominent in software projects across industries, and that the incorporation of ML development in ISD models is an ongoing, largely practice-driven, process

INTEGRATING MACHINE LEARNING WITH SOFTWARE DEVELOPMENT LIFECYCLES: INSIGHTS FROM EXPERTS

This paper examines the challenges related to integrating machine learning (ML) development with software development lifecycle (SDLC) models. Data-intensive development and use of ML are gaining popularity in information systems development (ISD). To date, there is little empirical research that explores the challenges that ISD practitioners encounter when integrating ML development with SDLC frameworks. In this work we conducted a series of expert interviews where we asked the informants to reflect upon how four different archetypal SDLC models support ML development. Three high level trends in ML systems development emerged from the analysis, namely, (1) redefining the prescribed roles and responsibilities within development work; (2) the SDLC as a frame for creating a shared understanding and commitment by management, customers, and software development teams: and (3) method tailoring. This study advances the body of knowledge on the integration of conceptual SDLC models and ML engineering

MMP-13 Regulates Growth of Wound Granulation Tissue and Modulates Gene Expression Signatures Involved in Inflammation, Proteolysis, and Cell Viability

Proteinases play a pivotal role in wound healing by regulating cell-matrix interactions and availability of bioactive molecules. The role of matrix metalloproteinase-13 (MMP-13) in granulation tissue growth was studied in subcutaneously implanted viscose cellulose sponge in MMP-13 knockout (Mmp13−/−) and wild type (WT) mice. The tissue samples were harvested at time points day 7, 14 and 21 and subjected to histological analysis and gene expression profiling. Granulation tissue growth was significantly reduced (42%) at day 21 in Mmp13−/− mice. Granulation tissue in Mmp13−/− mice showed delayed organization of myofibroblasts, increased microvascular density at day 14, and virtual absence of large vessels at day 21. Gene expression profiling identified differentially expressed genes in Mmp13−/− mouse granulation tissue involved in biological functions including inflammatory response, angiogenesis, cellular movement, cellular growth and proliferation and proteolysis. Among genes linked to angiogenesis, Adamts4 and Npy were significantly upregulated in early granulation tissue in Mmp13−/− mice, and a set of genes involved in leukocyte motility including Il6 were systematically downregulated at day 14. The expression of Pdgfd was downregulated in Mmp13−/− granulation tissue in all time points. The expression of matrix metalloproteinases Mmp2, Mmp3, Mmp9 was also significantly downregulated in granulation tissue of Mmp13−/− mice compared to WT mice. Mmp13−/− mouse skin fibroblasts displayed altered cell morphology and impaired ability to contract collagen gel and decreased production of MMP-2. These results provide evidence for an important role for MMP-13 in wound healing by coordinating cellular activities important in the growth and maturation of granulation tissue, including myofibroblast function, inflammation, angiogenesis, and proteolysis

How to explain AI systems to end users: a systematic literature review and research agenda

Purpose Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users. Design/methodology/approach The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review. Findings The authors' synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases. Research limitations/implications Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent. Originality/value This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.</p

Adverse consequences of emotional support seeking through social network sites in coping with stress from a global pandemic

This study explores how using social networking sites (SNSs) to cope with stressors induced by a global pandemic (in this case, COVID-19) can have negative consequences. The pandemic has imposed particular stressors on individuals, such as the threats of contracting the virus and of unemployment. Owing to the lockdowns and confinements implemented to limit the spread of the pandemic, SNS use has surged worldwide. Drawing on Lazarus and Folkman's theory of stress and coping, we consider COVID-19 obsession to be an adverse emotional response to the stressors brought about by the pandemic and emotional support seeking through SNS as a coping strategy. Furthermore, we identify SNS exhaustion as an adverse outcome of this form of coping. Finally, we analyze the intention to reduce SNS use as a corrective behavioral outcome to mitigate the negative effect of SNS-mediated coping. The findings indicate that: 1) the threat of the COVID-19 disease and the threat of unem-ployment drive COVID-19 obsession; 2) COVID-19 obsession contributes to emotional support seeking through SNS; 3) emotional support seeking through SNS exerts a positive effect on SNS exhaustion; 4) SNS exhaustion contributes to the intention to reduce SNS use. Our results advance Information Systems (IS) research by focusing on the use of Information Technology (IT) to cope with stressors that are essentially not IT-related; such research is largely absent from previous literature. Furthermore, our paper contributes to the increasing amount of literature on IT-mediated coping with stressors and reduced social media use

Trends and Trajectories in the Software Industry: implications for the future of work

In this study, we explore prominent contemporary technology trajectories in the software industry and how they are expected to influence the work in the software industry. Consequently, we build on cultural lag theory to analyze how technological changes affect work in software development. We present the results from a series of expert interviews that were analyzed using the Gioia method. Moreover, we identify a set of technology trends pertinent to software development from which we derive four main changes affecting the future of work in software development: (1) a shift toward scalable solutions, (2) increased emphasis on data, (3) convergence of IT and non-IT industries, and (4) the cloud as the dominant computing paradigm. Accordingly, this study contains insights into how technology (as an element of material culture) influences non-material culture, as exemplified by the work involved in software development

Trends and Trajectories in the Software Industry : implications for the future of work

In this study, we explore prominent contemporary technology trajectories in the software industry and how they are expected to influence the work in the software industry. Consequently, we build on cultural lag theory to analyze how technological changes affect work in software development. We present the results from a series of expert interviews that were analyzed using the Gioia method. Moreover, we identify a set of technology trends pertinent to software development from which we derive four main changes affecting the future of work in software development: (1) a shift toward scalable solutions, (2) increased emphasis on data, (3) convergence of IT and non-IT industries, and (4) the cloud as the dominant computing paradigm. Accordingly, this study contains insights into how technology (as an element of material culture) influences non-material culture, as exemplified by the work involved in software development.publishedVersionPeer reviewe

How to explain AI systems to end users : a systematic literature review and research agenda

Purpose: Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users. Design/methodology/approach: The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review. Findings: The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases. Research limitations/implications: Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent. Originality/value: This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.publishedVersionPeer reviewe

Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

Neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer was introduced several years ago. Despite the evidence supporting its use in clinical practice, only a minority of patients who undergo radical cystectomy receive preoperative chemotherapy. In addition, recommendations and methods to detect patients who would benefit the most from NAC are still unclear. The European Association of Urology (EAU) guidelines panel on muscle-invasive and metastatic bladder cancer recommends the use of cisplatin-based NAC for T2-T4a, cN0 M0 bladder cancer if the patient has a performance status ≥2 and if the renal function is not impaired, but the American Urological Association, for example, does not have any guideline recommendations on this topic at all. In this review we describe the current literature supporting NAC in association with radical cystectomy in muscle-invasive urothelial carcinoma of the bladder. Evidence acquisition was made searching the Medline database for original articles published before 1st February 2014, with search terms: “neoadjuvant chemotherapy”, “radical cystectomy”, and “invasive bladder cancer”