Data Science for Social Good

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Abbasi, Ahmed; Chiang, Roger; Xu, Jennifer

Abstract: Data science has been described as the fourth paradigm of scientific discovery. ... Expand

Abstract: Data science has been described as the fourth paradigm of scientific discovery. The latest wave of data science research, pertaining to machine learning and artificial intelligence (AI), is growing exponentially and garnering millions of annual citations. However, this growth has been accompanied by a diminishing emphasis on social good challenges-our analysis reveals that the proportion of data science research focusing on social good is less than it has ever been. At the same time, the proliferation of machine learning and generative AI has sparked debates about the sociotechnical prospects and challenges associated with data science for human flourishing, organizations, and society. Against this backdrop, we present a framework for "data science for social good" (DSSG) research that considers the interplay between relevant data science research genres, social good challenges, and different levels of sociotechnical abstraction. We perform an analysis of the literature to empirically demonstrate the paucity of work on DSSG in information systems (and other related disciplines) and highlight current impediments. We then use our proposed framework to introduce the articles appearing in the JAIS special issue on data science for social good. We hope that this editorial and the special issue will spur future DSSG research and help reverse the alarming trend across data science research over the past 30-plus years in which social good challenges are attracting proportionately less attention with each passing day. Collapse

Topics: societal evaluation criteria digital dashboard productivity social media pandemic

Methods: word embedding literature study literature sample longitudinal research design science

How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Abdel-Karim, Benjamin; Pfeuffer, Nicolas; Carl, K. Valerie; Hinz, Oliver

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelli ... Expand

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of MLbased decision support systems and also enriches theories on human-AI augmentation. Collapse

Topics: artificial intelligence decision making decision support system algorithmic transparency recommender system

Methods: cognitive walkthrough survey theory development qualitative interview Student's t-test

Theories: learning theory information systems theory theory of abduction

Responsible Digital Innovation in Dark: Toward Access-Control-Transparency Theory

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Abhari, Kaveh; Xiao, Bo; Eisenberg, David

Abstract: As the world moves ever forward into a digital future, the need for responsible ... Expand

Abstract: As the world moves ever forward into a digital future, the need for responsible digital innovation (RDI) becomes increasingly urgent. This paper presents the access-control-transparency (ACT) theory, a simple yet powerful framework for guiding designers and developers in creating digital artifacts that embody the principles of responsible design. With a focus on promoting access, control, and transparency, this theory aims to address the dark side of digital innovation and ensure that new technologies are developed in a way that considers their impact on individuals, communities, and society. The paper also explores avenues for future research, including the impact of ACT-driven design principles on organizational and societal outcomes, the role of individual and organizational values in the RDI process, and the incorporation of human-centric design and ongoing reflection into the ACT theory. Collapse

Topics: innovation management digital innovation access control

Methods: theory development synthesis design artifact

A taxonomy of data governance decision domains in data marketplaces

2023 | Electronic Markets | Citations: 0

Authors: Abraham, Rene; Schneider, Johannes; vom Brocke, Jan

Abstract: Commercializing data and data-related services has gained in importance in recen ... Expand

Abstract: Commercializing data and data-related services has gained in importance in recent years. Driven by digitalization and the Internet-of-Things (IoT), companies and individuals continuously generate vast amounts of data. Data marketplaces have emerged to support these data providers in selling their data to different data consumers. However, data marketplaces face challenges in different data governance decision domains that inhibit their adoption. To get a better understanding of how data marketplaces counteract these challenges, this paper develops a taxonomy of data governance decision domains in data marketplaces. We used a taxonomy development method to inspect 13 data marketplaces from eight countries. The resulting taxonomy shows an overview of mechanisms concerning data quality, data security, data architecture, metadata, data lifecycle, data storage, and data pricing. We discuss common instantiation patterns, highlight gaps, and propose possible solutions. The taxonomy sets a foundation for further research and theory-building on data marketplaces. Practitioners can use the taxonomy to develop customized data governance strategies for data marketplaces. Collapse

Topics: data governance price management system development method computer data storage website

Methods: design artifact data modeling design methodology design science company material

Know the Knowledge of Your Students: A Flexible Analytics Tool for Student Exercises

2023 | DESRIST | Citations: 0

Authors: Aguirre Reid, Sören; Kammer, Frank; Schüller, Daria; Siepermann, Markus; Wölfer, Jonas

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practi ... Expand

Abstract: Intelligent tutoring systems (ITS) have the power to influence lecturers’ practices in the classroom and to improve students’ learning. Many ITS provide standardized analytical methods to evaluate classroom performance or the results of the exercises. But they lack more sophisticated, flexible and individual analyses. This paper presents an e-learning Analytics Tool (EAT) for an ITS that provides a dashboard with key figures and a flexible analytics board (FAB). This enables lecturers to analyze students’ performance in detail and identify misconceptions. For instance, the FAB allows us to classify student solutions, reveal conceptual errors in exercises, and analyze each part of an exercise. By this, common mistakes can be identified, and tailored feedback can be given to the students. Following the design science approach, the platform is designed in a general way so that it can be used for different types of exercises (e.g., Math, Excel, SQL). To assess the artifact, we conducted group interviews with German University lecturers from various courses. The results show that lecturers require a good overview of the submitted student solutions to provide timely feedback. They also appreciate the flexible analytics tool for detailed analyses of student solutions to understand student mistakes better. The employed architecture allows general analyses of exercises and the content of students’ solutions. In addition, the EAT is not bound to a specific kind of exercise, but can cope with different kinds like SQL and Excel. Collapse

Topics: digital dashboard structured query language database system online learning system perceived usefulness

Methods: group interview design science design artifact survey qualitative interview

Responsible innovation with digital platforms: Cases in India and Canada

2023 | Information Systems Journal | Citations: 6

Authors: Ahuja, Suchit; Chan, Yolande E.; Krishnamurthy, Rashmi

Abstract: Marginalized communities globally encounter grand challenges such as lack of acc ... Expand

Abstract: Marginalized communities globally encounter grand challenges such as lack of access to education, healthcare, and sustained livelihoods. Several initiatives to address these complex, global problems have resulted in fragmented solutions. Recognizing this, there have been several calls for the study of responsible innovation (RI) to address grand challenges. Digital platforms such as AirBnB, Uber and so forth have now become commonplace and are known to generate economic value but also face criticism for being exploitative and exclusive. Only a handful of studies show how similar platforms can innovate responsibly to serve marginalized communities by generating simultaneous economic and social value. To address this gap, our study examines the cases of two platforms that orchestrated ecosystems consisting of individuals from marginalized communities, government agencies, and other entities to provide physical, digital and societal solutions based on principles of RI. We contribute to the RI and IS literatures to show how RI solutions can be fostered through digital platforms to address grand challenges. The article provides empirical evidence of all four dimensions of the RI framework—anticipation, reflexivity, inclusion, and responsiveness - and their operationalization through digital platforms. This research lays the foundation for future studies at the intersection of RI and digital platforms literature. The study also provides practice insights on developing digital platform solutions for marginalized communities to address grand challenges and is useful to policymakers to formulate appropriate interventions. It pushes the theoretical and practice boundaries of our understanding of RI and digital platforms. Collapse

Topics: digital platform mobile application social media innovation management business model

Methods: qualitative interview theory development case study triangulation archival research

Theories: theory of economic development

Blockchain Use Case in Ballistics and Crime Gun Tracing and Intelligence: Toward Overcoming Gun Violence

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Akello, Patricia; Vemprala, Naga; Lang Beebe, Nicole; Raymond Choo, Kim-Kwang

Abstract: In the United States and around the world, gun violence has become a long-standi ... Expand

Abstract: In the United States and around the world, gun violence has become a long-standing public safety concern and a security threat, due to violent gun-related crimes, injuries, and fatalities. Although legislators and lawmakers have attempted to mitigate its threats through legislation, research on gun violence confirms the need for a comprehensive approach to gun violence prevention. This entails addressing the problem in as many ways as possible, such as through legislation, new technological advancements, re-engineering supply, and administrative protocols, among others. The research focuses on the technological, supply, and administrative aspects, in which we propose a manner of managing gun-related data efficiently from the point of manufacture/sale, as well as at points of transfers between secondary sellers for the improvement of criminal investigation processes. Making data more readily available with greater integrity will facilitate successful investigations and prosecutions of gun crimes. Currently, there is no single and uniform platform for firearm manufacturers, dealers, and other stakeholders involved in firearm sales, dissemination, management, and investigation. With the help of Blockchain technology, gun registry, ownership, transfers, and, most importantly, investigations, when crimes occur, can all be managed efficiently, breaking the cycle of gun violence. The identification of guns, gun tracing, and identification of gun owners/possessors rely on accuracy, integrity, and consistency in related systems to influence gun crime investigation processes. Blockchain technology, which uses a consensus-based approach to improve processes and transactions, is demonstrated in this study as a way to enhance these procedures. To the best of our knowledge, this is the first study to explore and demonstrate the utility of Blockchain for gun-related criminal investigations using a design science approach. Collapse

Topics: blockchain criminality smart contract Ethereum access control

Methods: design artifact design science design process case study simulation

Knowledge contributions in design science research: Paths of knowledge types

2023 | Decision Support Systems | Citations: 0

Authors: Akoka, Jacky; Comyn-Wattiau, Isabelle; Prat, Nicolas; Storey, Veda C.

Abstract: Design science research addresses important, complex real-world problems. Althou ... Expand

Abstract: Design science research addresses important, complex real-world problems. Although well-accepted as part of research in information systems, initiating or progressing a design science research project still requires effort to describe how knowledge creation emerges and its underlying dynamics. Given the existing body of knowledge on design science research, it should be possible to learn from that knowledge to progress future work. This paper analyzes design science research projects to identify and make explicit their knowledge contributions while recognizing the plurality of a project's knowledge contributions with respect to a project's knowledge scope and knowledge goals. The construct of a path of knowledge types is introduced that represents how knowledge con­ tributions are dynamically created throughout a project. These paths form the basis for the derivation of seven design science research strategies, which lead to guidelines for initiating or progressing a project. This effort is compared to other research that analyzes the growing body of work in design science with respect to knowledge contributions and project classifications. Collapse

Topics: knowledge type decision support system IT project management innovation management anonymity

Methods: design science literature sample literature study design artifact design principle

Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities

2023 | Information Systems Frontiers | Citations: 0

Authors: Alahakoon, Damminda; Nawaratne, Rashmika; Xu, Yan; De Silva, Daswin; Sivarajah, Uthayasankar; Gupta, Bhumika

Abstract: The emerging information revolution makes it necessary to manage vast amounts of ... Expand

Abstract: The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications. Collapse

Topics: artificial intelligence smart city big data cloud computing distributed system

Methods: computational algorithm experiment unsupervised learning machine learning longitudinal research

Accepting the Familiar: The Effect of Perceived Similarity with AI Agents on Intention to Use and the Mediating Effect of IT Identity

2023 | HICSS | Citations: 0

Authors: Alawi, N.; De Vreede, T.; De Vreede, G.

Abstract: With the rise and integration of AI technologies within organizations, our unde ... Expand

Abstract: With the rise and integration of AI technologies within organizations, our understanding of the impact of this technology on individuals remains limited. Although the IS use literature provides important guidance for organization to increase employees' willingness to work with new technology, the utilitarian view of prior IS use research limits its application considering the new evolving social interaction between humans and AI agents. We contribute to the IS use literature by implementing a social view to understand the impact of AI agents on an individual's perception and behavior. By focusing on the main design dimensions of AI agents, we propose a framework that utilizes social psychology theories to explain the impact of those design dimensions on individuals. Specifically, we build on Similarity Attraction Theory to propose an AI similarity-continuance model that aims to explain how similarity with AI agents influence individuals' IT identity and intention to continue working with it. Through an online brainstorming experiment, we found that similarity with AI agents indeed has a positive impact on IT identity and on the intention to continue working with the AI agent. Collapse

Topics: artificial intelligence usage intention behavioral intention brainstorming usability

Methods: chatbot experiment survey descriptive statistic statistical hypothesis test

Theories: social psychology theory