Talking About the Assumption in the Room

Fuente: arXiv
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Hauptverfasser: Mothilal, Ramaravind Kommiya, Lalani, Faisal M., Ahmed, Syed Ishtiaque, Guha, Shion, Sultana, Sharifa
Format: Preprint
Veröffentlicht: 2025
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author Mothilal, Ramaravind Kommiya
Lalani, Faisal M.
Ahmed, Syed Ishtiaque
Guha, Shion
Sultana, Sharifa
author_facet Mothilal, Ramaravind Kommiya
Lalani, Faisal M.
Ahmed, Syed Ishtiaque
Guha, Shion
Sultana, Sharifa
contents The reference to assumptions in how practitioners use or interact with machine learning (ML) systems is ubiquitous in HCI and responsible ML discourse. However, what remains unclear from prior works is the conceptualization of assumptions and how practitioners identify and handle assumptions throughout their workflows. This leads to confusion about what assumptions are and what needs to be done with them. We use the concept of an argument from Informal Logic, a branch of Philosophy, to offer a new perspective to understand and explicate the confusions surrounding assumptions. Through semi-structured interviews with 22 ML practitioners, we find what contributes most to these confusions is how independently assumptions are constructed, how reactively and reflectively they are handled, and how nebulously they are recorded. Our study brings the peripheral discussion of assumptions in ML to the center and presents recommendations for practitioners to better think about and work with assumptions.
format Preprint
id arxiv_https___arxiv_org_abs_2502_13268
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Talking About the Assumption in the Room
Mothilal, Ramaravind Kommiya
Lalani, Faisal M.
Ahmed, Syed Ishtiaque
Guha, Shion
Sultana, Sharifa
Human-Computer Interaction
Machine Learning
The reference to assumptions in how practitioners use or interact with machine learning (ML) systems is ubiquitous in HCI and responsible ML discourse. However, what remains unclear from prior works is the conceptualization of assumptions and how practitioners identify and handle assumptions throughout their workflows. This leads to confusion about what assumptions are and what needs to be done with them. We use the concept of an argument from Informal Logic, a branch of Philosophy, to offer a new perspective to understand and explicate the confusions surrounding assumptions. Through semi-structured interviews with 22 ML practitioners, we find what contributes most to these confusions is how independently assumptions are constructed, how reactively and reflectively they are handled, and how nebulously they are recorded. Our study brings the peripheral discussion of assumptions in ML to the center and presents recommendations for practitioners to better think about and work with assumptions.
title Talking About the Assumption in the Room
topic Human-Computer Interaction
Machine Learning
url https://arxiv.org/abs/2502.13268