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"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Work

Angel Hsing-Chi Hwang, Senya Wong, Baixiao Chen, Jessica He, Hyo Jin Do

TL;DR

Investigating how both workers and clients perceive AI use and disclosure in the freelance economy through a three-stage study reveals a key expectation gap around disclosure and highlights the role of unclear or absent client AI policies.

Abstract

The growing use of AI applications among freelance workers is reshaping trust and relationships with clients. This paper investigates how both workers and clients perceive AI use and disclosure in the freelance economy through a three-stage study: interviews with workers and two survey studies with workers and clients. Findings first reveal a key expectation gap around disclosure: Workers often adopt passive disclosure practices, revealing AI use only when asked, as they assume clients can already detect it. Clients, however, are far less confident in recognizing AI-assisted work and prefer proactive disclosure. A second finding highlights the role of unclear or absent client AI policies, which leave workers consistently misinterpreting clients' expectations for AI use and disclosure. Together, these gaps point to the need for clearer guidelines and practices for AI disclosure. Insights extend beyond freelancing, offering implications for trust, accountability, and policy design in other AI-mediated work domains.

"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Work

TL;DR

Investigating how both workers and clients perceive AI use and disclosure in the freelance economy through a three-stage study reveals a key expectation gap around disclosure and highlights the role of unclear or absent client AI policies.

Abstract

The growing use of AI applications among freelance workers is reshaping trust and relationships with clients. This paper investigates how both workers and clients perceive AI use and disclosure in the freelance economy through a three-stage study: interviews with workers and two survey studies with workers and clients. Findings first reveal a key expectation gap around disclosure: Workers often adopt passive disclosure practices, revealing AI use only when asked, as they assume clients can already detect it. Clients, however, are far less confident in recognizing AI-assisted work and prefer proactive disclosure. A second finding highlights the role of unclear or absent client AI policies, which leave workers consistently misinterpreting clients' expectations for AI use and disclosure. Together, these gaps point to the need for clearer guidelines and practices for AI disclosure. Insights extend beyond freelancing, offering implications for trust, accountability, and policy design in other AI-mediated work domains.
Paper Structure (43 sections, 7 figures, 6 tables)

This paper contains 43 sections, 7 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Background and Related Work
  3. Navigating Freelance Workplace in the Age of Generative AI
  4. Perceptual Harms and Secret Use of AI
  5. Transparency, Attribution, and Disclosure of AI Use
  6. Methods
  7. Findings
  8. AI Use in Freelance Work
  9. Misalignment of Accepted AI Use
  10. Expectation Gaps in AI Disclosure
  11. Workers' Approaches to AI Disclosure
  12. Mismatched Expectations for AI Disclosure and their Potential Consequences
  13. Evaluating the Tradeoff of AI Disclosure
  14. (Mis)Interpretations of AI Policies
  15. Permitted AI use.
  16. ...and 28 more sections

Figures (7)

  • Figure 1: Workers and clients' perceptions of common freelance tasks as major or minor tasks for AI use.
  • Figure 2: Clients and workers also differed in their attitudes toward disclosure. Significantly more workers than clients believed that disclosure of AI use is not required, whereas significantly more clients expected workers to actively disclose when they use AI.
  • Figure 3: Clients' and workers' responses to whether workers are allowed to use AI for their freelance work. The majority of clients and workers both believe AI use is allowed. The portion of clients allowing AI use is slightly larger than workers' expectations.
  • Figure 4: Permitted AI use according to clients' AI policies vs. workers' interpretation of permitted AI use based on each policy.
  • Figure 5: Difference between permitted AI use and workers’ interpretations of AI policies. Positive values indicate that workers believed they were allowed to use AI to a greater extent than the policies actually permitted, while negative values indicate that workers interpreted the policies more restrictively than intended.
  • ...and 2 more figures