AIS Electronic Library (AISeL)
Not a member yet
72426 research outputs found
Sort by
WHO IS DRIVING AI-ENABLED TRANSFORMATION? TOWARDS A TAXONOMY OF CHIEF AI OFFICERS
No full textAs the application and use of Artificial Intelligence (AI) becomes more widespread, businesses are looking for approaches and mechanisms to successfully leverage AI’s full potential for service and product innovation as well as organizational transformation. However, many companies have difficulties establishing appropriate governance structures to support their AI initiatives and ambitions. In our study, we examine the emergence of the Chief AI Officer (CAIO), as a potential building block for an organization’s AI governance. We analyze 40 CAIOs of large firms. Based on information found in press statements, company websites, and articles we iteratively derive a taxonomy of the CAIO containing 10 dimensions and 37 characteristics. We present the first empirically grounded characterization of the CAIO role. Our systematic analysis and classification facilitate a comprehensive understanding of the responsibilities and configurations of the CAIO, and further offer a foundation for further research on executive leadership
WHEN VOICE ASSISTANTS SOUND FAIR: ALIGNING VOICE INTERACTION DESIGN WITH FAIRNESS PRINCIPLES
No full textVoice Assistants (VAs) offer convenient, hands-free user interfaces that can help companies better serve their customers. However, without graphical interfaces, VAs are limited in the amount of information they can transmit, introducing new challenges regarding the fairness of VA output as perceived by users (e.g., based on opaque outputs). Previous studies have developed general Voice User Interface (VUI) design guidelines to optimize VA-user interactions, but they lack a focus on fairness. We follow a systematic multiphase process in which we first employ 18 semi-structured expert interviews to connect 4 fairness principles with established VUI design guidelines to achieve VUI fairness rules. We then identify concrete VUI design characteristics using a Systematic Literature Review (SLR) to operationalize these rules. Our integrative design framework for fair VUIs not only shows VUI fairness rules but also provides practitioners with the appropriate design characteristics to explicitly influence the fairness of their VAs
BLOCKCHAIN IN CONTINUING EDUCATION – TAXONOMY FOR A NEXT-GENERATION TEACHING PLATFORM
No full textThe constantly growing educational technology market and rising demand for comprehensive, lifelong learning in rapidly digitizing environments, offer significant potential for implementing decentralized blockchain systems in the context of continuing education. However, the continuing education sector underutilizes the promised value. This paper develops a multi-layer taxonomy based on a systematic literature review and expert interviews, which contributes to systematically delineating possible augmentations of continuing education management using blockchain-based technology. Applications include fraud prevention, intellectual property protection, efficient and secure data exchange by tokenizing personal documents and developing interoperable, smart educational institutions using smart contracts and IoT. The taxonomy incorporates descriptive knowledge and prescriptive guidance to researchers in educational technology, implementers, and instructors in continuing education, as well as institutional decision-makers on the benefits of blockchain, such as decentralized governance, data security, immutability, and anonymity, leveraged throughout the phases of educational program development in an institutional or company-internal context
Just Relax! – The Impact of Immersive Technology on Human Well-Being in Stressful Situations
No full textHuman well-being plays a vital role in individuals\u27 lives and further impacts their effectiveness. As virtual reality enables individuals to immerse themselves in virtual worlds, it plays an increasingly important role as an access device to improve the quality of individuals’ lives. However, a comprehensive understanding of the impact of immersive technologies on individual well-being and their effect on cognitive performance under stressful situations remains unexplored. In a between-subjects experiment involving 41 participants, we evaluated the impact of VR immersion vs. non-immersive natural environments on relaxation, affective states, mental workload, and cognitive performance. Our findings indicate that VR-based relaxation enhances relaxation levels, improves positive affect, and reduces negative affect and mental workload. Furthermore, the VR group demonstrated better cognitive performance scores compared to the non-VR group. The results underscore the value of integrating VR for mental health interventions and workplace stress management, paving the way for further research
Architecture Interoperability through Semantic Modelling: Domain-driven data specification in public procurement
Full text linkThis paper explores the persistent challenges in achieving interoperability within public procurement, emphasizing the critical transitions between organizational, semantic, and technical layers. While existing general frameworks such as the Framework for Interoperable Service Architecture Development (FISAD) and the European Interoperability Framework (EIF) provide structured approaches to interoperability, they often lack mechanisms for effectively translating domain-driven requirements into technical data standard specifications. To address this gap, the paper examines Simple Semantic Modeling in XML (SeMoX) as a method to enhance interoperability by bridging these layers. Drawing from a Design Science Research approach, the study integrates SeMoX into FISAD, creating a holistic architectural framework that incorporates data standardization as a core enabler of interoperability. Practical use cases, including SeMoX\u27s application in public procurement, demonstrate its effectiveness. The paper concludes with an analysis of SeMoX’s contributions and outlines future research directions to evaluate its scalability and potential in developing interoperable, holistic architectures
Protecting Children from Violent Short Videos: A Child-Attentive Multimodal Multitask Learning Approach
No full textShort video platforms, such as TikTok, have gained immense popularity, but also contain harmful content like violence, threatening minors’ mental health. This paper proposes a Child-Attentive Multimodal Multitask Learning (CAMML) method for accurate violent short video detection. Unlike existing methods that neglect text cues, correlations with other harmful content, and children’s unique cognitive characteristics, CAMML integrates visual, auditory, and text modalities. It features a child-specific attention mechanism and a multi-task learning approach, jointly training violent video classification alongside tasks like detecting unpleasant and obscene content. Experiments on the MOB dataset that targets malicious and benign content in children’s videos demonstrate CAMML’s superior performance, achieving a 90.02% AUC. The method provides a robust solution for filtering violent content, fostering a clear online environment for children
Impacts of AI-Based Search on User Engagement: Evidence from Stack Overflow’s OverflowAI
No full textWith rapid advancements in AI-based search, digital knowledge-sharing platforms are experiencing a profound transformation. Traditional Q&A sites like Stack Overflow are integrating AI tools to enhance search precision and streamline information retrieval, yet little is known about how these innovations affect user engagement. Motivated by this gap, we investigate the impact of Stack Overflow’s OverflowAI using a quasi-experimental design that compares the post-launch period in 2023 with a control period from 2022. Our analysis reveals that OverflowAI is associated with an approximately 18% increase in post view counts and a 3% increase in vote counts, with heterogeneous effects across technical topics. These findings underscore the potential of AI-driven search to not only improve the relevance of retrieved information but also to foster greater community interaction. Our results provide valuable insights for platform managers and developers in optimizing content curation and engagement strategies in digital knowledge ecosystems
DeltaHedge: A Multi-Agent Framework for Portfolio Options Optimization
No full textIn volatile financial markets, balancing risk and return remains a significant challenge. Traditional approaches often focus solely on equity allocation, overlooking the strategic advantages of options trading for dynamic risk hedging. This work presents DeltaHedge, a multi-agent framework that integrates options trading with AI-driven portfolio management. By combining advanced reinforcement learning techniques with an ensembled options-based hedging strategy, DeltaHedge enhances risk-adjusted returns and stabilizes portfolio performance across varying market conditions. Experimental results demonstrate that DeltaHedge outperforms traditional strategies and standalone models, underscoring its potential to transform practical portfolio management in complex financial environments. Building on these findings, this paper contributes to the fields of quantitative finance and AI-driven portfolio optimization by introducing a novel multi-agent system for integrating options trading strategies, addressing a gap in the existing literature
Perceived digital inclusion at work: Conceptualization and measurement
No full textArtificial intelligence is reshaping work and social interactions, making digital inclusion more critical than ever, particularly in its impact on social engagement and job performance. While digital inclusion has been widely examined in the literature, there is a lack of understanding on conceptualizing and operationalizing perceived digital inclusion at work. Existing measures mainly focus on infrastructure, access, and digital skills, which overlook how individuals perceive their own inclusion in AI-driven digital ecosystems. This study introduces perceived digital inclusion at work as a distinct construct and develops a measurement scale to assess individuals\u27 subjective experiences of digital inclusion in the work context. Our findings provide actionable insights for promoting equitable digital inclusion in the workplace and enhancing AI adoption. The validated perceived digital inclusion scale contributes to the advancement of digital inclusion research, providing policymakers, organizations, and scholars with a rigorous instrument to guide future digital inclusion strategies, policies, and interventions
How do We Conceptualize the Elderly Digital Divide?
Full text linkWhen considering the elderly digital divide in China, limited progress has been made in conceptualizing this problem. Despite the existing research representing a laudable body of work, we argue that a majority of these studies measure the digital divide in an overly simplistic manner, which belies its complexity. In addition, what underpins these studies is an assumption that an elderly person does or does not experience a digital divide. However, it has been argued that a clearer understanding of this problem is held back by this assumption. Therefore, it has been suggested that rather than viewing the digital divide as a dichotomy, it should be viewed as a continuum between the extremes. To explore this continuum, we advance the Life Course Perspective, which, through four principles, offers a framework for examining the digital divide. Through a discussion of the principles, with examples, we illustrate its potential for conceptualizing this problem