Abstract

Artificial Intelligence-as-a-Service (AIaaS) empowers individuals and organisations to access AI on-demand, in either tailored or ‘off-the-shelf’ forms. However, institutional separation between development, training and deployment can lead to critical opacities, such as obscuring the level of human effort necessary to produce and train AI services. Information about how, where, and for whom AI services have been produced are valuable secrets, which vendors strategically disclose to clients depending on commercial interests. This article provides a critical analysis of how AIaaS vendors manipulate the visibility of human labour in AI production based on whether the vendor relies on paid or unpaid labour to fill interstitial gaps. Where vendors are able to occlude human labour in the organisational ‘backstage,’ such as in data preparation, validation or impersonation, they do so regularly, further contributing to ongoing techno-utopian narratives of AI hype. Yet, when vendors must co-produce the AI service with the client, such as through localised AI training, they must ‘lift the curtain’, resulting in a paradoxical situation of needing to both perpetuate dominant AI hype narratives while emphasising AI’s mundane limitations.

Highlights

  • In the current zeitgeist of research into artificial intelligence (AI), academic interest has largely focused on AI as an abstract sociotechnical phenomenon, or as embedded in major platforms such as Facebook, Google or Twitter

  • Information about how, where, and for whom AI services have been produced are valuable secrets, which vendors strategically disclose to clients depending on commercial interests

  • When AI-as-a-Service offerings (AIaaS) vendors must involve the human labour of clients to co-produce the AI service, the role of human intervention is made hypervisible

Read more

Summary

Introduction

In the current zeitgeist of research into artificial intelligence (AI), academic interest has largely focused on AI as an abstract sociotechnical phenomenon, or as embedded in major platforms such as Facebook, Google or Twitter. While AIaaS adoption in organisations continues apace (Vesa and Tienari, 2020; von Krogh, 2018), a complex AI production ecosystem has emerged which connects vendors, clients, developers and data workers through both informal and formal ties. Drawing on Daniels’ (1987) concept of invisible work as that which ‘disappears from our observations and reckonings’ (403), I offer a critical analysis on the human labour involved in AI production.

Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call