D&L: A Natural Language Processing Based Approach for Protecting Sensitive Information from Shoulder Surfing Attacks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aldossari, Marran; Zhang, Dongsong

Abstract: Despite the increasing attention and research effort, how to protect sensitive ... Expand

Abstract: Despite the increasing attention and research effort, how to protect sensitive information from shoulder surfing attacks is still under studied. Existing methods for protecting sensitive textual content on users' screens from shoulder surfing attacks have various limitations, including ineffectiveness, insufficient protection of sensitive information, low usability, and high cognitive workload. To address those limitations, this paper proposes, develops, and evaluates a new solution called "detection and labeling" (D&L), which uses NLP techniques to automatically detect and label sensitive information in the textual content. The labeled and hidden sensitive information is then read to users through their headphones upon their clicking a label. Evaluation results demonstrate that D&L improves protection, enhances usability, reduces users' cognitive workload, and allows faster browsing speed compared to the baseline methods. Collapse

Topics: electronic mail laptop computer usability privacy perceived ease of use

Methods: survey parametric test experiment Tukey HSD for post poc analysis ANOVA

DataOps as a Prerequisite for the Next Level of Self-Service Analytics – Balancing User Agency and Central Control

2023 | International Conference on Business Informatics | Citations: 0

Authors: Baars, Henning

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated ... Expand

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated between more central, efficiency-oriented, professionalized approaches and decentral, agility-oriented, user-driven ones. This paper investigates whether and how to alleviate that tradeoff by combining an agility-oriented self-service analytics approach with the professionalization-driven DataOps concept: DataOps aims at transferring ideas from DevOps to the realm of analytics, namely a mutual integration of Development and Operations and a high degree of professionalization and automation. A case study with a series of interviews and a workshop led to insights into the viability of such a combination. These inspire a theoretical concept for capturing the economics behind the approaches that is considering the (opportunity) costs of the components "user agency" and "central control". The concept has been evaluated with representatives from the case study. Based on the results, I argue that the discussed combination can push BIA solutions towards fine-tuned federated environments. Collapse

Topics: devops artificial intelligence mlops data management data integration

Methods: qualitative interview case study literature study machine learning survey

Algorithmic Transparency: Concepts, Antecedents, and Consequences – A Review and Research Framework

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

Authors: Bitzer, Tobias; Wiener, Martin; Cram, W. Alec

Abstract: The widespread and growing use of algorithm-enabled technologies across many as ... Expand

Abstract: The widespread and growing use of algorithm-enabled technologies across many aspects of public and private life is increasingly sparking concerns about the lack of transparency regarding the inner workings of algorithms. This has led to calls for (more) algorithmic transparency (AT), which refers to the disclosure of information about algorithms to enable understanding, critical review, and adjustment. To set the stage for future research on AT, our study draws on previous work to provide a more nuanced conceptualization of AT, including the explicit distinction between AT as action and AT as perception. On this conceptual basis, we set forth to conduct a comprehensive and systematic review of the literature on AT antecedents and consequences. Subsequently, we develop an integrative framework to organize the existing literature and guide future work. Our framework consists of seven central relationships: (1) AT as action versus AT as perception; factors (2) triggering and (3) shaping AT as action; (4) factors shaping AT as perception; as well as AT as perception leading to (5) rational-cognitive and (6) affective-emotional responses, and to (7) (un-)intended behavioral effects. Building on the review insights, we identify and discuss notable research gaps and inconsistencies, along with resulting opportunities for future research. review of the literature on AT. Not only has such an endeavor, to our knowledge, not yet been undertaken; but more importantly, we expect that such a review will reveal critical research gaps and inconsistencies and inform future research in the area. In particular, we aim to extend past work and contribute to the extant body of knowledge by (1) strengthening the conceptual foundations of AT; (2) reviewing the AT literature in a systematic manner; and (3) deriving a research framework. In doing so, our study offers a more nuanced conceptualization of AT, including the explicit distinction between AT as action and AT as perception, and delineates AT from related concepts. Moreover, following established guidelines (e.g., vom Brocke et al., 2015;Okoli & Schabram, 2010;Paré et al., 2015;Webster & Watson, 2002) and drawing on a review sample of 50 studies (published between 2002 and 2021), our study offers a comprehensive review and synthesis of prior research on the antecedents and consequences of AT. Finally, we propose an integrative framework to organize existing and guide future work. Collapse

Topics: database system algorithmic transparency artificial intelligence website digital service

Methods: computational algorithm literature study synthesis mixed method archival research

Managing Customer Data in Data-driven Service Innovation: A Framework of Data Principles

2023 | International Conference on Business Informatics | Citations: 0

Authors: Blöcher, Katharina; Reinhold, Olaf; Alt, Rainer

Abstract: While customer data has been collected in enterprise systems since decades, the ... Expand

Abstract: While customer data has been collected in enterprise systems since decades, the emerging consumer technologies create new sources of data. Although the need to co-create services with customers has been recognized, a systematic approach of how to include this sensitive source of innovation in the service innovation process is still lacking. This research explores the potential of data governance practices for data-driven service innovation. Data principles for the governance of customer data are collected and assessed by practioners in order to provide conceptual support for organizations and to facilitate the service innovation process. The results of this research integrate data principles of different research streams and offer a framework of data principles that can be applied in the design and management of data-driven services. Collapse

Topics: innovation management business process innovation data governance database system data management

Methods: qualitative interview personal interview archival research theoretical contribution synthesis

Theories: dominant logic

Is There More Than Pokémon Go? -Exploring the State of Research on Causal Modeling in the Field of Augmented Reality

2023 | HICSS | Citations: 0

Authors: Bräker, J.; Semmann, M.

Abstract: The paper explores how scholars apply causal modeling to gain an understanding ... Expand

Abstract: The paper explores how scholars apply causal modeling to gain an understanding of augmented reality as innovative technology and its potential for application. To do so, we conducted a structured literature review and applied a graph database-driven approach to analyze how scholars research augmented reality. Such an approach enables in-depth analysis of the body of knowledge that is not accessible in traditional ways of exploring literature. The results help to understand where we as a community stand and how directions for future research can help reshape the understanding of augmented reality and its application. Collapse

Topics: augmented reality smart device graph database perceived usefulness Neo4j

Methods: structural equation modeling structured literature research literature study literature sample synthesis

Theories: technology acceptance model cue utilization theory extended unified theory of acceptance and use of technology

PRACTICAL SUPPORT FOR UNLEARNING – A SYSTEMATIC REVIEW TO ORGANIZE THE FIELD

2023 | European Conference On Information Systems | Citations: 0

Authors: Di Maria, Marco; Walter, David; Schoormann, Thorsten; Knackstedt, Ralf

Abstract: Organizations are increasingly concerned with the continuous reassessment and r ... Expand

Abstract: Organizations are increasingly concerned with the continuous reassessment and redesign of their products, processes, and business models to remain competitive in uncertain environments. Thereby, mental models, routines, and behaviors of individuals and entire organizations need to be updated to fit changing demands and environmental factors. 'Unlearning' is a promising approach to achieve this because it allows knowledge to be refined and adapted to novel situations. Unlearning established ways of thinking and doing effectively poses, however, several challenges that could be mitigated by an appropriate tool support. By following a qualitative systematic review of literature from Information Systems and adjacent disciplines, we identified and synthesized existing tools and guidance to assist individuals, teams, and organizations in unlearning. With our study, we contribute to an integrated overview of practical support for unlearning based on a sample of 41 papers as well as useful guidance for practitioners, designers, and researchers. Collapse

Topics: knowledge type change management agile software development organizational context IS discipline

Methods: literature sample design artifact literature study structured literature research synthesis

Automized Assessment for Professional Skills – A Systematic Literature Review and Future Research Avenues

2023 | International Conference on Business Informatics | Citations: 0

Authors: Freise, Leonie Rebecca; Bretschneider, Ulrich

Abstract: ... Expand

Abstract: Collapse

Topics: knowledge base soft skill

Methods: structured literature research computational algorithm literature study cluster analysis natural language processing

Theories: organizational behavior theory

Augmenting the Framework for Design Science Research Goals and Evaluation Criteria with Aspects of Society 5.0

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Greinacher, Janick; Nerlich, Jan-Christoph; Schäffer, Thomas

Abstract: In the field of information systems, new technologies are giving rise to a wide ... Expand

Abstract: In the field of information systems, new technologies are giving rise to a wide range of new research topics that present researchers with new challenges. Innovations, such as artificial intelligence, have an enormous impact on society, in addition to technological progress towards automation, above all or precisely because of this. In this context, Society 5.0 was initiated to establish criteria for research and its artifacts. In this paper, evaluation criteria of a Society 5.0 are identified, which should be considered for Design Science Research artifacts in the future. Through a comprehensive literature review, 14 evaluation criteria and a new DSR goal were identified and integrated into the existing framework of Hevner et al. (2018). The paper provides researchers with an augmented DSR evaluation framework with aspects of Society 5.0. Collapse

Topics: evaluation criteria industry 4.0 artificial intelligence societal evaluation criteria

Methods: literature study design artifact design science qualitative content analysis synthesis

Task delegation from AI to humans: A principal-agent perspective

2023 | International Conference on Information Systems | Citations: 0

Authors: Guggenberger, Tobias; Lämmermann, Luis; Urbach, Nils; Walter, Anna; Hofmann, Peter

Abstract: Increasingly intelligent AI artifacts in human-AI systems perform tasks more au ... Expand

Abstract: Increasingly intelligent AI artifacts in human-AI systems perform tasks more autonomously as entities that guide human actions, even changing the direction of task delegation between humans and AI. It has been shown that human-AI systems achieve better results when the AI artifact takes the leading role and delegates tasks to a human rather than the other way around. This study presents phenomena, conflicts, and challenges that arise in this process, explored through the theoretical lens of principalagent theory (PAT). The findings are derived from a systematic literature review and an exploratory interview study and are placed in the context of existing constructs of PAT. Furthermore, this article paper identifies new causes of tensions that arise specifically in AI-to-human delegation and calls for special mechanisms beyond the classical solutions of PAT. The paper thus contributes to the understanding of autonomous AI and its implications for human-AI delegation. Collapse

Topics: artificial intelligence human computer interaction human AI collaboration explainable artificial intelligence software developer

Methods: qualitative interview personal interview structured literature research qualitative coding computational algorithm

Theories: lemon market theory agency theory

Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing

2023 | Group Decision and Negotiation | Citations: 0

Authors: Gimpel, Henner; Graf-Seyfried, Vanessa; Laubacher, Robert; Meindl, Oliver

Abstract: Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, ... Expand

Abstract: Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these limits by supporting the facilitation of crowdsourcing. However, AI’s potential for macro-task crowdsourcing facilitation needs to be better understood for this to happen. Here, we turn to affordance theory to develop this understanding. Affordances help us describe action possibilities that characterize the relationship between the facilitator and AI, within macro-task crowdsourcing. We follow a two-stage, bottom-up approach: The initial development stage is based on a structured analysis of academic literature. The subsequent validation & refinement stage includes two observed macro-task crowdsourcing initiatives and six expert interviews. From our analysis, we derive seven AI affordances that support 17 facilitation activities in macro-task crowdsourcing. We also identify specific manifestations that illustrate the affordances. Our findings increase the scholarly understanding of macro-task crowdsourcing and advance the discourse on facilitation. Further, they help practitioners identify potential ways to integrate AI into crowdsourcing facilitation. These results could improve the efficiency of facilitation activities and the effectiveness of macro-task crowdsourcing. Collapse

Topics: crowdsourcing artificial intelligence affordance user experience usability

Methods: qualitative interview literature study literature sample personal interview natural language processing

Theories: theory of affordance