Other Scholarly Content

 

How to Debug Inclusivity Bugs? An Empirical Investigation of Finding-to-Fixing with Information Architecture Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/defaults/8049gc556

Descriptions

Attribute NameValues
Creator
Abstract
  • Background: Although some previous research has found ways to find inclusivity bugs (biases in software that introduce inequities among cognitively diverse individuals), little attention has been paid to how to go about fixing such bugs. We hypothesized that Information Architecture (IA)--the way information is organized, structured and labeled--may provide the missing link from finding inclusivity bugs in information-intensive technology to fixing them. Aims: To investigate whether Information Architecture provides an effective way to remove inclusivity bugs from technology, we created Why/Where/Fix, an inclusivity debugging paradigm that adds inclusivity fault localization via IA. Method: We conducted a qualitative empirical investigation in three stages. (Stage 1): An Open Source (OSS) team used the Why (which cognitive styles) and Where (which IA) parts to guide their understanding of inclusivity bugs in their OSS project’s infrastructure. (Stage 2): The OSS team used the outcomes of Stage One to produce IA-based fixes (Fix) to the inclusivity bugs they had found. (Stage 3): We brought OSS newcomers into the lab to see whether and how the IA-based fixes had improved equity and inclusion across cognitively diverse OSS newcomers. Results: Information Architecture was a source of numerous inclusivity bugs. The OSS team's use of IA to fix these bugs reduced the number of inclusivity bugs participants experienced by 90%. Conclusions: These results provide encouraging evidence that using IA through Why/Where/Fix can help technologists to address inclusivity bugs in information-intensive technologies such as OSS project infrastructures.
License
Resource Type
Date Issued
Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language

Relationships

Parents:

This work has no parents.

Items