Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Co-Designing Collaborative Generative AI Tools for Freelancers

Kashif Imteyaz, Michael Muller, Claudia Flores-Saviaga, Saiph Savage

TL;DR

The paper addresses how to design collaborative generative AI for freelancers, a context characterized by decentralized, temporary teams and limited institutional support. Through synchronous Future Workshops and a three-month asynchronous Slack phase with 27 freelancers, the authors reveal that current AI tools embody technological rationality, risking context-insensitive outputs and over-reliance. They propose an 'auxiliary AI' model that supports collaboration while preserving human creative agency, complemented by design principles (diverse skill support, AI as background helper, and a dedicated human coordinator) and ethical guidelines for attribution. Grounded in Marcuse and Feenberg, the work offers practical design implications and a methodology (design probes using DALL·E) to reclaim democratic, human-centered technology design in AI-enabled collaboration with freelancers.

Abstract

Most generative AI tools prioritize individual productivity and personalization, with limited support for collaboration. Designed for traditional workplaces, these tools do not fit freelancers' short-term teams or lack of shared institutional support, which can worsen their isolation and overlook freelancing platform dynamics. This mismatch means that, instead of empowering freelancers, current generative AI tools could reinforce existing precarity and make freelancer collaboration harder. To investigate how to design generative AI tools to support freelancer collaboration, we conducted co-design sessions with 27 freelancers. A key concern that emerged was the risk of AI systems compromising their creative agency and work identities when collaborating, especially when AI tools could reproduce content without attribution, threatening the authenticity and distinctiveness of their collaborative work. Freelancers proposed "auxiliary AI" systems, human-guided tools that support their creative agencies and identities, allowing for flexible freelancer-led collaborations that promote "productive friction". Drawing on Marcuse's concept of technological rationality, we argue that freelancers are resisting one-dimensional, efficiency-driven AI, and instead envisioning technologies that preserve their collective creative agencies. We conclude with design recommendations for collaborative generative AI tools for freelancers.

Co-Designing Collaborative Generative AI Tools for Freelancers

TL;DR

The paper addresses how to design collaborative generative AI for freelancers, a context characterized by decentralized, temporary teams and limited institutional support. Through synchronous Future Workshops and a three-month asynchronous Slack phase with 27 freelancers, the authors reveal that current AI tools embody technological rationality, risking context-insensitive outputs and over-reliance. They propose an 'auxiliary AI' model that supports collaboration while preserving human creative agency, complemented by design principles (diverse skill support, AI as background helper, and a dedicated human coordinator) and ethical guidelines for attribution. Grounded in Marcuse and Feenberg, the work offers practical design implications and a methodology (design probes using DALL·E) to reclaim democratic, human-centered technology design in AI-enabled collaboration with freelancers.

Abstract

Most generative AI tools prioritize individual productivity and personalization, with limited support for collaboration. Designed for traditional workplaces, these tools do not fit freelancers' short-term teams or lack of shared institutional support, which can worsen their isolation and overlook freelancing platform dynamics. This mismatch means that, instead of empowering freelancers, current generative AI tools could reinforce existing precarity and make freelancer collaboration harder. To investigate how to design generative AI tools to support freelancer collaboration, we conducted co-design sessions with 27 freelancers. A key concern that emerged was the risk of AI systems compromising their creative agency and work identities when collaborating, especially when AI tools could reproduce content without attribution, threatening the authenticity and distinctiveness of their collaborative work. Freelancers proposed "auxiliary AI" systems, human-guided tools that support their creative agencies and identities, allowing for flexible freelancer-led collaborations that promote "productive friction". Drawing on Marcuse's concept of technological rationality, we argue that freelancers are resisting one-dimensional, efficiency-driven AI, and instead envisioning technologies that preserve their collective creative agencies. We conclude with design recommendations for collaborative generative AI tools for freelancers.
Paper Structure (52 sections, 9 figures, 1 table)

This paper contains 52 sections, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Freelancers and Collaborative Work
  4. Defining the Nature of Collaboration in Freelance Work
  5. Collaborative Generative AI Tools: Existing Approaches and Gaps
  6. Co-Design Approaches
  7. Remote Participatory and Co-Design Methods
  8. Design Probes using DALL-E Images
  9. Critical Theory and Technology Design
  10. Marcuse's Critique of Technological Rationality
  11. Critical Perspectives on AI and Platform Labor
  12. Methods
  13. Procedure for Synchronous Co-Design Sessions
  14. Generative AI Tutorial
  15. Co-Design Phase I: Critiquing the Present Challenges of Generative AI Tools for Collaboration
  16. ...and 37 more sections

Figures (9)

  • Figure 1: Design probe from Phase I showing how generative AI wastes freelancers' time with irrelevant, homogenized outputs.
  • Figure 2: Phase I probe showing AI-induced over-reliance.
  • Figure 3: Phase III design probe showing freelancers with diverse skills and background collaborating.
  • Figure 4: Phase I design probe showing how AI overtakes human oversight when freelancer teams are not diverse and lack technical expertise.
  • Figure 5: Phase II probe showing participants' vision of auxiliary AI supporting collaboration.
  • ...and 4 more figures