Revising the ‘science of the organisation’: theorising AI agency and actorhood

Abstract

Artificial intelligence is a central technology underpinning the fourth industrial revolution, driving dramatic changes in contemporary cyber-physical systems and challenging existing ways of theorising organisations and management. AI agency and the rise of the artificially intelligent agent are both fundamentally different and yet increasingly similar to human agency in terms of intentionality and reflexivity. As 'Child AI' emerges-AI that is created by other AI-the early human design and interaction becomes increasingly distant and removed. These developments, while seemingly futuristic, change the human-technology interface through which we organise. In this essay, we explore understandings of AI agency, capability, and governance, and present implications for organisatonal theorising in sociomateriality, actor-network theory, institutional theory and the behavioral theory of the firm. We contribute to a growing and reflexive research agenda that can accommodate and regenerate theorising around this significant technological advancement.

Digital Technology and Voice: How Platforms Shape Institutional Processes Through Visibilization

“…Different features of platforms can significantly impact institutional arrangements. In this way, insights from our study speak to recent calls to examine and theorize the interplay between technology and (de-)institutionalization (Logue & Grimes, 2021;van Rijmenam & Logue, 2020). Our findings illustrate how this interplay is not only shaped by technological affordances but also by unintended consequences that may be rooted in platform features.…”

Algorithms as work designers: How algorithmic management influences the design of jobs

“…In sum, AI algorithms, largely powered by machine learning, differ from previous automated decision-making devices in their high level of autonomy (requiring little human input), their self-learning capacities, their potential for interconnectedness, and their ability to handle massive and heterogeneous data in order to perform description, prediction, and prescription tasks (Makarius et al, 2020;Murray et al, 2020). As we elaborate in this review, these attributes of AI algorithms mean they have the potential to impact work design in new, and often more extreme, ways (van Rijmenam & Logue, 2021).…”

“…Artificial intelligence algorithms can either be pre-programmed or powered by machine learning technologies (Leicht-Deobald et al, 2019;Wang & Siau, 2019;Wong, 2019). Machine learning refers to a field of study that enables computers to learn without being explicitly programmed (van Rijmenam & Logue, 2021;Wang & Siau, 2019). Instead of following determined rules like pre-programmed algorithms, machine learning algorithms start from very little programming and are trained on big and unstructured data sets.…”

Institutional Perspectives on Digital Transformation

“…Typically AI systems have a "master" and differ in their degree of autonomy (Larsen, 2021). To meaningfully inquire whether there can be artificial institutional agents, the broader challenge is how we conceptualize AI itself as it relates to actorhood and agency (Hwang & Colyvas, 2019), and the theoretical challenge of how to conceptualize nonhuman or artificial agency (van Rijmenam & Logue, 2021). This is especially so as AI agency and the rise of the artificially intelligent agent are both fundamentally different and yet are perceived to be increasingly similar to human agency in terms of intentionality and reflexivity.…”