Disengagement through Algorithms: How Traditional Organizations Aim for Experts' Satisfaction

This study examines the use of algorithmic tools in traditional organizational decision-making processes. Through forty semi-structured interviews with managers, engineers, and (expert) users across six European projects, we suggest that initiators deploy algorithms not to automate actions or replace users, but to disengage themselves from prescriptive decision-making. Consequently, the responsibility to choose, select, and decide falls upon the users; they become engaged. Therefore, algorithm evaluation is oriented towards utility, interpretability, and, more broadly, user satisfaction. Further research is encouraged to analyze the advent of a 'satisfaction regime', from platforms to traditional organizations.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2024-10-16
DOI
https://doi.org/10.1609/aies.v7i1.31711
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Disengagement through Algorithms: How Traditional Organizations Aim for Experts' Satisfaction

Jérémie Poiroux
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Big Data and Business Intelligence
article

Disengagement through Algorithms: How Traditional Organizations Aim for Experts' Satisfaction

Jérémie Poiroux
article en

Abstract

This study examines the use of algorithmic tools in traditional organizational decision-making processes. Through forty semi-structured interviews with managers, engineers, and (expert) users across six European projects, we suggest that initiators deploy algorithms not to automate actions or replace users, but to disengage themselves from prescriptive decision-making. Consequently, the responsibility to choose, select, and decide falls upon the users; they become engaged. Therefore, algorithm evaluation is oriented towards utility, interpretability, and, more broadly, user satisfaction. Further research is encouraged to analyze the advent of a 'satisfaction regime', from platforms to traditional organizations.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 7
The University of Tokyo (JP)
Centre National de la Recherche Scientifique, Japan Society for the Promotion of Science
Peace, Justice and strong institutions
Openalex Percentile: Top 68%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.