Pith. sign in

REVIEW 1 cited by

Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2410.18334 v1 pith:NGCGMJGM submitted 2024-10-24 cs.SE

Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace

classification cs.SE
keywords toolsgenerativedeveloperscodingbeliefsworkcodecontrolled
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Generative AI coding tools are relatively new, and their impact on developers extends beyond traditional coding metrics, influencing beliefs about work and developers' roles in the workplace. This study aims to illuminate developers' preexisting beliefs about generative AI tools, their self perceptions, and how regular use of these tools may alter these beliefs. Using a mixed methods approach, including surveys, a randomized controlled trial, and a three week diary study, we explored the real world application of generative AI tools within a large multinational software company. Our findings reveal that the introduction and sustained use of generative AI coding tools significantly increases developers' perceptions of these tools as both useful and enjoyable. However, developers' views on the trustworthiness of AI generated code remained unchanged. We also discovered unexpected uses of these tools, such as replacing web searches and fostering creative ideation. Additionally, 84 percent of participants reported positive changes in their daily work practices, and 66 percent noted shifts in their feelings about their work, ranging from increased enthusiasm to heightened awareness of the need to stay current with technological advances. This research provides both qualitative and quantitative insights into the evolving role of generative AI in software development and offers practical recommendations for maximizing the benefits of this emerging technology, particularly in balancing the productivity gains from AI-generated code with the need for increased scrutiny and critical evaluation of its outputs.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. "Code Is Cheap. Show Me the Talk.": Lessons from Teaching and Managing AI Coding Tool Usage in a Visualization Course

    cs.HC 2026-07 conditional novelty 6.0

    In a CS visualization course, AI coding labs showed refinement as half of student prompts, explanation nearly absent, optional AI preferred by only 56%, and final projects more polished but visually homogeneous.