Generative AI

Business & Information Systems Engineering, Год журнала: 2023, Номер 66(1), С. 111 - 126

Опубликована: Сен. 12, 2023

The term "generative AI" refers to computational techniques that are capable of generating seemingly new, meaningful content such as text, images, or audio from training data. widespread diffusion this technology with examples Dall-E 2, GPT-4, and Copilot is currently revolutionizing the way we work communicate each other. In article, provide a conceptualization generative AI an entity in socio-technical systems models, systems, applications. Based on that, introduce limitations current agenda for Business & Information Systems Engineering (BISE) research. Different previous works, focus context information and, end, discuss several opportunities challenges unique BISE community make suggestions impactful directions

Язык: Английский

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What is the Metaverse and who seeks to define it? Mapping the site of social construction

Journal of Information Technology, Год журнала: 2023, Номер 38(3), С. 239 - 266

Опубликована: Фев. 10, 2023

The Metaverse has become a buzz-phrase among tech businesses. Facebook’s rebranding to Meta is symptomatic of this. Many firms and other actors are trying shape visions the Metaverse, leading confusion about term’s meaning. We use social construction technology (SCOT) theory disentangle conflicting notions proposing that what will relies on collective sensemaking processes. point out similarities differences between various concepts presented in public media link them individual actors’ monetary, political, or motives. describe tensions occur because interests. As an emerging phenomenon, opportunities exist reorient it toward humanist values rather than singular However, complexity processes requires considerate approach premature conclusions Metaverse’s characteristics. analysis presents as new, continually evolving sociotechnical calls for research explores dynamic, moving target.

Язык: Английский

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Digitalization and artificial knowledge for accountability in SCM: a systematic literature review

Journal of Enterprise Information Management, Год журнала: 2023, Номер 37(2), С. 606 - 672

Опубликована: Фев. 3, 2023

Purpose In this study, the authors examine artificial knowledge as a fundamental stream of management for sustainable and resilient business models in supply chain (SCM). The study aims to provide comprehensive overview digitalization key enablers improvement SCM accountability performance towards UN 2030 Agenda. Design/methodology/approach Using SCOPUS database Google Scholar, analyzed 135 English-language publications from 1990 2022 chart pattern production dissemination literature. data were collected, reviewed peer-reviewed before conducting bibliometric analysis systematic literature review support future research agenda. Findings results highlight that are linked further identifies main issues achieving models. Based on results, develop conceptual framework increase performance, especially times sudden crises when resilience is imperative. Research limitations/implications add extant by examining theory perspective. suggest different strategic perspectives significantly promote digitization development. Notably, fostering diverse peer exchange relationships can help stimulate act palliative mechanism builds digital strengthen drive possibilities. Practical implications This offers valuable guidance practitioners, managers policymakers re-thinking, re-formulating re-shaping organizational processes meet Agenda, mainly introducing transformation training education programs. doing so, firms should focus not simply but also cultural enhance Originality/value is, authors' best knowledge, among first conceptualize SCM. It integrates with institutional theory, legitimacy stakeholder theoretical foundations SCM, based firms' responsibility fulfill development goals under UN's

Язык: Английский

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Digital governance: A conceptual framework and research agenda

Journal of Business Research, Год журнала: 2023, Номер 162, С. 113777 - 113777

Опубликована: Март 30, 2023

The rapid expansion of digital technologies has paved the way for new forms organizing, facilitated by increased data and knowledge exchange between individuals organizations. However, this poses major challenges designing effective governance mechanisms. This paper highlights critical role in facilitating digitally enabled relationships. To end, we propose a typology analog, augmented, automated modes, each associated with specific control, coordination, incentive, trust Additionally, provide heuristic determining optimal choice via interplay transactivity (i.e., contributors, connections, consistency an network) corresponding costs. Our study advances literature defining as distinct form outlining key mechanisms choices era. Finally, identify avenues future research field.

Язык: Английский

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Navigating Bias and Fairness in Digital AI Systems

Advances in human and social aspects of technology book series, Год журнала: 2024, Номер unknown, С. 127 - 156

Опубликована: Окт. 17, 2024

In an era where AI advancements permeate various facets of daily life, ranging from healthcare decision-making to personalized content delivery, the potential for biases exacerbate societal inequalities has become a pressing concern. The chapter commences by defining and scrutinizing forms bias in artificial intelligence, elucidating their tangible effects through compelling case studies. Subsequently, it explores theoretical foundations fairness AI, considering conceptual frameworks such as distributive justice procedural while addressing challenges operationalizing these principles. section delves into methods tools identifying measuring datasets algorithms, introducing metrics benchmarks assess outcomes. Strategies best practices mitigating are examined, encompassing approaches data preprocessing, algorithmic adjustments, post-hoc corrections.

Язык: Английский

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Perceived algorithmic fairness: An empirical study of transparency and anthropomorphism in algorithmic recruiting

Information Systems Journal, Год журнала: 2024, Номер 34(2), С. 384 - 414

Опубликована: Янв. 15, 2024

Abstract Despite constant efforts of organisations to ensure a fair and transparent personnel selection process, hiring is still characterised by systematic inequality. The potential algorithms produce objective decision outcomes has attracted the attention academic scholars practitioners as conceivable alternative human decision‐making. However, applicants do not necessarily consider an algorithm fairer than maker. This study examines conditions under which perceive establishes theoretical foundation algorithmic fairness perceptions. We further propose investigate transparency anthropomorphism interventions strategies actively shape these In online application scenario with eight experimental groups ( N = 801), we analyse determinants for perceptions impact proposed interventions. Embedded in stimulus‐organism‐response framework drawing from organisational justice theory, our reveals four dimensions (procedural, distributive, interpersonal, informational justice) that determine results show mainly affect interpersonal justice, highlighting importance critical individual choices.

Язык: Английский

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Ethics-based AI auditing: A systematic literature review on conceptualizations of ethical principles and knowledge contributions to stakeholders

Information & Management, Год журнала: 2024, Номер 61(5), С. 103969 - 103969

Опубликована: Май 1, 2024

This systematic literature review synthesizes the conceptualizations of ethical principles in AI auditing and knowledge contributions to stakeholders auditing. We explain how discusses fairness, transparency, non-maleficence, responsibility, privacy, trust, beneficence, freedom/autonomy. Conceptualizations vary along social/technical- process/outcome-oriented dimensions. The main ethics-based are system developers deployers, wider public, researchers, auditors, users, regulators. provides three types stakeholders: 1) guidance; 2) methods, tools, frameworks; 3) awareness empowerment.

Язык: Английский

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Algorithms as co‐workers: Human algorithm role interactions in algorithmic work

Information Systems Journal, Год журнала: 2022, Номер 33(2), С. 232 - 267

Опубликована: Май 7, 2022

Abstract In algorithmic work, algorithms execute operational and management tasks such as work allocation, task tracking performance evaluation. Humans interact with one another to accomplish so that the algorithm takes on role of a co‐worker. Human–algorithm interactions are characterised by problematic issues absence mutually co‐constructed dialogue, lack transparency regarding how outputs generated, difficulty over‐riding directive – conditions create clarity for human worker. This article examines human–algorithm in work. Drawing theoretical framing organisational roles, we theorise sender taker. We explain is multi‐role entangled while taker experiences algorithm‐driven conflict ambiguity. Further, records all human's actions, it ignorant cognitive reactions undergoes what conceptualise ‘broken loop learning’. The empirical context our study taxi driving (in United States) exemplified companies Uber. draw from data include interviews 15 Uber drivers, netnographic 1700 discussion threads among drivers two popular online forums, analysis Uber's web pages. Implications IS scholarship, practice policy discussed.

Язык: Английский

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Algorithmic fairness in business analytics: Directions for research and practice

Production and Operations Management, Год журнала: 2022, Номер 31(10), С. 3749 - 3770

Опубликована: Авг. 22, 2022

The extensive adoption of business analytics (BA) has brought financial gains and increased efficiencies. However, these advances have simultaneously drawn attention to rising legal ethical challenges when BA inform decisions with fairness implications. As a response concerns, the emerging study algorithmic deals outputs that may result in disparate outcomes or other forms injustices for subgroups population, especially those who been historically marginalized. Fairness is relevant on basis compliance, social responsibility, utility; if not adequately systematically addressed, unfair systems lead societal harms also threaten an organization's own survival, its competitiveness, overall performance. This paper offers forward‐looking, BA‐focused review fairness. We first state‐of‐the‐art research sources measures bias, as well bias mitigation algorithms. then provide detailed discussion utility–fairness relationship, emphasizing frequent assumption trade‐off between two constructs often mistaken short‐sighted. Finally, we chart path forward by identifying opportunities scholars address impactful, open are key effective responsible deployment BA.

Язык: Английский

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A review of the literature on the metaverse: definition, technologies, and user behaviors

Internet Research, Год журнала: 2023, Номер 34(1), С. 129 - 148

Опубликована: Сен. 11, 2023

Purpose As a sociotechnical system, the metaverse has sparked heated discussion. However, concerns abound that concept is “old wine in new bottle” used for capital hype. The mixed definitions of and unclear relationships between its technical features user behaviors have greatly impeded design application. Therefore, authors aim to sort out definition properties, analyze various contexts unveil mechanisms leading behaviors. Design/methodology/approach conduct literature review on definition, of/in metaverse. Findings First, identify two main categories find conceptualization. Second, present technologies diverse Third, summarize effect from perspective. Originality/value features, their theoretical foundations. Based these findings, propose framework unveiling how social elements affect In conclusion, study offers research agenda future studies.

Язык: Английский

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