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

Examining the case of French hesitancy toward IDaaS solutions: Technical and social contextual factors of the organizational IDaaS privacy calculus

2023 | Information & Management | Citations: 0

Authors: Abdalla Mikhaeil, Christine; James, Tabitha L.

Abstract: Identity-as-a-service (IDaaS) is a cloud security service to which companies can ... Expand

Abstract: Identity-as-a-service (IDaaS) is a cloud security service to which companies can outsource the identity and access management (IAM) functions that administer their employee’s access to organizational resources. Engaging with the information systems (IS) privacy literature, our qualitative analysis develops a framework for an organiza­ tional privacy calculus that informs French organizational consumers’ decisions to pursue IDaaS solutions. We collect data from employees of a multinational IDaaS provider operating in Europe but headquartered in the US. Our case study reveals the organizational privacy calculus associated with transferring control of a primary security control to a multinational cloud service provider. Collapse

Topics: cloud computing information privacy concern marketing management privacy internet of things

Methods: qualitative interview case study company material single case study personal interview

Theories: privacy calculus theory

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

Maintaining or Altering the Status Quo in the Nonmarket Arena: Theory and Evidence from Government Contract Disputes

2023 | Organization Science | Citations: 0

Authors: Abdurakhmonov, Mirzokhidjon; Hasija, Dinesh; Ridge, Jason W.; Hill, Aaron D.

Abstract: We develop a theory that considers important differences in competition in the p ... Expand

Abstract: We develop a theory that considers important differences in competition in the political arena based on whether firms are attempting to maintain or alter the status quo. Particularly, we argue that although investing resources and time to build relationships with politicians and government officials fosters trust, solidarity, and reciprocity, likely producing desired outcomes for both firms attempting to maintain the status quo and those trying to alter it, such relationships are more strongly positive for firms maintaining the status quo. As the effectiveness of relational strategies may differ based on firms’ political strategies and firm characteristics, we then theorize that the effects of a more relational approach on ”winning” these desired outcomes for firms seeking to maintain or alter the status quo will be moderated by (1) prior targeting in the political arena where the competition unfolds and (2) a firm’s social reputation. Specifically, we argue that knowledge and relationships from prior targeting in a political domain where competition unfolds, and a firm’s better social reputation will strengthen the effect of a more relational approach on securing desired outcomes for both firms seeking to maintain and alter the status quo. We expect the moderating effect for a firm’s targeting and social reputation will be stronger for firms seeking to maintain the status quo compared with firms seeking to alter the status quo. Our study contributes to corporate political activity literature and notably to the research on political markets by advancing a more nuanced but realistic understanding of interfirm rivalry for governmental outcomes. Collapse

Topics: resource allocation database system competitive advantage legal context anonymity

Methods: theory development statistical hypothesis test chi squared test cluster analysis Compustat

Theories: resource based view of the firm

Introduction to the Minitrack on Explainable Artificial Intelligence (XAI)

2023 | HICSS | Citations: 0

Authors: Abedin, B.; Meske, C.; Rabhi, F.; Klier, M.

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task perform ... Expand

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task performance of humans in various domains. However, most AI systems are still "black boxes" that are difficult to comprehend -not only for developers, but also for users and decision-makers. Explainable Artificial Intelligence (XAI) is aimed at intelligent systems that are highly performant to enable their users to understand, appropriately trust, and scrutinize them. Collapse

Topics: explainable artificial intelligence artificial intelligence

Methods: experiment structured literature research

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

Input control and its signalling effects for complementors' intention to join digital platforms

2023 | Information Systems Journal | Citations: 2

Authors: Adam, Martin; Croitor, Evgheni; Werner, Dominick; Benlian, Alexander; Wiener, Martin

Abstract: Existing information systems (IS) research on platform control has largely focus ... Expand

Abstract: Existing information systems (IS) research on platform control has largely focused on examining how input control (i.e., the mechanisms used to control platform access) affects complementors' intentions and behaviours after their decision to join a digital platform. Yet, our understanding of how input control is perceived before this decision and how such perceptions influence prospective complementors' intention to join a platform is still nascent. In this regard, our study views input control as a salient signal that shapes prospective complementors' expected benefits and costs (i.e., their performance and effort expectancy), and ultimately their decision to join a digital platform. Drawing on signalling theory and the antecedent-benefit-cost (ABC) framework, we conducted a randomized online experiment in the context of donation-based crowdfunding. The experiment results offer empirical support for this view by showing that input control has distinct and complex signalling effects for prospective complementors. In particular, our findings reveal curvilinear and competing signalling effects, with perceived input control increasing both performance expectancy (at a decreasing rate) and effort expectancy (at an increasing rate). Also, we find that performance expectancy linearly increases prospective complementors' intention to join a platform, whereas effort expectancy linearly decreases their intention to do so. These findings imply that the overall relationship between perceived input control and intention to join follows an inverted U-shape curve, which means that neither a low nor a high, but a moderate degree of perceived input control maximizes prospective complementors' intention to join. In sum, the results of our study provide novel and important insights into the signalling role that perceived input control plays in shaping prospective complementors' decision to join a digital platform. Collapse

Topics: digital platform crowdsourcing crowdfunding behavioral intention digital ecosystem

Methods: experiment mediation analysis survey survey design theory development

Theories: signaling theory

Value Creation Tradeoff in Business Ecosystems: Leveraging Complementarities While Managing Interdependencies

2023 | Organization Science | Citations: 0

Authors: Agarwal, Shiva; Kapoor, Rahul

Abstract: Complementary assets play an important role in shaping an innovation’s commercia ... Expand

Abstract: Complementary assets play an important role in shaping an innovation’s commercialization success. In this paper, we broaden the locus of complementarities to examine the role of complementary technologies residing in the business ecosystems that are becoming an important source of value creation for innovating firms. We argue that, on one hand, complementary technologies help innovations create more value for their users. On the other hand, they can also limit the focal innovation’s value creation by exposing them to performance bottlenecks as the underlying technological architecture of the ecosystem evolves. We further extend the notion of specialization of complementary assets to ecosystems by considering complementary technologies that are specialized to a focal ecosystem and those that are available across multiple ecosystems. We highlight that, although the complementary technologies that are specialized to an ecosystem facilitate greater value creation, they are more likely to subject the focal innovation to performance bottlenecks. Evidence from 244,034 apps launched by software developers for Apple’s iPhone ecosystem during 2008–2015 offers strong support for our framework. In summary, the study sheds light on the value creation tradeoff for firms innovating in business ecosystems—the opportunities associated with leveraging complementarities and the challenges associated with managing technological interdependencies. Funding: S. Agarwal was funded by the McCombs School of Business at The University of Texas at Austin [Research Excellence Grant]. Collapse

Topics: mobile application innovation management value creation Apple iPhone iOS

Methods: statistical hypothesis test instrumental variables estimation cross sectional research proportional hazards model robustness check

ETHICAL GUIDELINES FOR BLOCKCHAIN SYSTEMS

2023 | European Conference On Information Systems | Citations: 0

Authors: Agerskov, Signe; Pedersen, Asger; Beck, Roman

Abstract: Enterprise architects and IT systems developers must often decide ad hoc how to ... Expand

Abstract: Enterprise architects and IT systems developers must often decide ad hoc how to identify, assess and mitigate ethical issues of autonomous, rule-based systems based on blockchain technology. As blockchain systems are decentralized and immutable, developers must assess ethical risks, not only on an individual level but also on a network level along the life-cycle stages of a blockchain system. These ethical issues should be addressed and ideally mitigated by clearly defined norms and values that are intentionally incorporated in a blockchain system. As a reference for a normative system, we have chosen the European Union and its ethical values to discuss them in the context of ethical issues emerging from blockchain systems. This paper presents a top-down approach that establishes ethical guidelines for blockchain systems based on ethical issues mapped against European values. Collapse

Topics: blockchain smart contract data encryption privacy supply chain management

Methods: literature sample literature study case study computational algorithm triangulation

Applying Reflexivity to Artificial Intelligence for Researching Marginalized Communities and Real-World Problems (CC BY-NC-ND 4.0)

2023 | HICSS | Citations: 0

Authors: Aguilar, N.; Landau, A.; Mathiyazhagan, S.; Auyeung, A.; Dillard, S.; Patton, D.

Abstract: Despite advances in artificial intelligence (AI), ethical principles have been ... Expand

Abstract: Despite advances in artificial intelligence (AI), ethical principles have been overlooked, harming marginalized communities. These flaws are due to a lack of critical insight into the complex positionality of the researcher, power dynamics between scholars and the communities being studied, and the structural impact on real-world problems when AI systems appear to be accurate but ethically fail. Reflexivity is a process that yields a better understanding of community-specific nuances, areas requiring local expertise, and the potential consequences of scholastic interventions for real-world problems (i.e., social, environmental, or socioeconomic). The paper builds on the five stages of social work reflexivity that can be applied to AI researchers and provided questions that can be asked in order to increase privacy, accountability, and fairness. We discuss the effective implementation of reflexivity in research, detail the stages of social work reflexivity and highlight key questions for AI researchers to ask throughout the research process. Collapse

Topics: artificial intelligence privacy unintended consequence

Methods: natural language processing image processing case study