Organization and Management Theory OMT

Call for papers: Organising and Working in Times of (G)AI: Ethnographic Assemblages in Modern Institutions for Journal of Organizational Ethnography

Introduction
This special issue calls for an innovative focus on generative artificial intelligence (GAI) within organisational cultures by exploring how AI impacts ethnographic methodology and offers critical analysis on the representation of empirical research findings in the times of AI. We seek to foster a more human-centric perspective concerning AI adaptation within diverse institutions. By investigating the experience of researchers and workers whose daily practices encounter disruptions due to the influx of AI technologies, this issue will lay the foundation for insightful explorations that extend beyond the technological dimension.

The rise of artificial intelligence (AI) promises to be one of the most significant technological shifts in our lifetimes (von Krogh, 2018). The rapid advancements in AI have prompted widespread adoption of transformative technologies by organisations across numerous sectors. Despite vastly different epistemic approaches to reaching 'intelligence' (Balasubramanian et al., 2022), AI is imbued with the promise to be able to complement humans' cognitive abilities, leading to streamlined processes, enhanced efficiency, and increased innovation (Jarrahi, 2018; Raisch & Krakowski, 2021). However, the implementation of AI also raises critical questions about its consequences on individuals, work institutions, societal structures, and human-AI interactions (e.g., Brynjolfsson & McAfee, 2014; Hitt & Brynjolfsson, 1996; Lebovitz et al., 2022; Susskind & Susskind, 2015).

The evolution of web technologies has transitioned us from Web 1.0 to Web 4.0, characterised by the integration of humans and AI within a collaborative web. Generative AI (GAI), a specific aspect of AI able to create texts, images, and other media in response to prompts, is perceived as a significant tool reshaping organisations (Bender et al., 2021; Stolker-Walker & Van Noorden, 2023). The latest large language models (LLM), such as, GPT-4.5, LaMDA and BLOOM, possess advanced capabilities such as data analysis, autonomous content creation, coding, web connectivity, and the generation of multi-modal media. GAI's rapid and versatile performance empowers it to efficiently handle complex creative and analytical tasks, influencing how people work, communicate, produce, synthesise, and critically assess knowledge and delivery of services (Haase & Hanel, 2023; Jovanovic & Campbell, 2022; Kanitz et al., 2023; Pelau et al., 2021). As this technology reshapes modern workforces, there is a pressing need to expand our understanding of how AI impacts organisational culture, and how researchers navigate and represent this new technological era.

Aims and Objectives
First, we call for papers framing the process of studying institutions integrating AI, exploring evolving ethnographic methodologies for human and AI collaborations. How will AI impact ethnography within phenomenologically complex research 'fields', and what challenges or opportunities arise in terms of epistemic standpoints, ethics, data interpretation, and research dissemination?

Secondly, we invite critical analyses of empirical research or speculative essays on AI's relationship with human actors in organisations. Key considerations: How does AI affect human workers? How do institutions change with AI and how is this captured in ethnography? What new dynamics form between humans and technology, influencing decision-making, governance, and policy? Ultimately, we seek to question the future visions for workforces and institutions.

List of topic areas

·      Ethnographic methodology and empirical research on AI adoption, integration, and collaboration within organisations, as well as ethical and practice implications.

·      The role, and ethnographic representation, of human-AI decision-making and relational processes within organisations.

·      The social and epistemological limitations of (G)AI in organisational research settings.

·      The implications and limitations of transparency and technological explainability of AI.

·      Novel concepts and empirical lenses to theorise (G)AI in organisational settings, especially speculative future qualitative studies of organisations.

·      Responsibility, accountability, ethics, and, justice around (G)AI

·      Issues and possibilities around the power and politics of (G)AI

Key deadlines
Closing date for abstracts submissions: 1st November, 2023
Opening date for manuscripts submissions: 1st November, 2023
Closing date for manuscripts submission: 1st May, 2024 

Submissions and questions
Email for abstract submissions and informal inquiries: 
Landon B. Kuester (landon.kuester@manchester.ac.uk) and Bas W. Becker (b.w.becker@vu.nl)