Friction by Machine
How to Slow Down Reasoning with Computational Methods
Bibliographic Data
| ID | 5948401 |
|---|---|
| Authors | Anders Koed Madsen (0000-0003-2842-4908, Institute of Technology of Cambodia), Anders Kristian Munk (0000-0002-5542-3065, Institute of Technology of Cambodia), Johan Irving Søltoft (0000-0002-3076-0575, Institute of Technology of Cambodia) |
| Year | 2023 |
| Volume | 2023 |
| Issue | 1 |
| Pages | 65-88 |
| Publication date | 2023-11-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ethnographic Praxis in Industry Conference Proceedings (CONFERENCE) |
| Journal identifiers | ISSN: 1559-890X • E-ISSN: 1559-8918 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/epic.12153 |
| OpenAlex | W4406323162 |
| Language | EN |
| Citations received | 10 |
| References cited | 19 |
This paper provides a theoretical alternative to the prevailing perception of machine learning as synonymous with speed and efficiency. Inspired by ethnographic fieldwork and grounded in pragmatist philosophy, we introduce the concept of "data friction" as the situation when encounters between held beliefs and data patterns possess the potential to stimulate innovative thinking. Contrary to the conventional connotations of "speed" and "control," we argue that computational methods can generate a productive dissonance, thereby fostering slower and more reflective practices within organizations. Drawing on a decade of experience in participatory data design and data sprints, we present a typology of data frictions and outline three ways in which algorithmic techniques within data science can be reimagined as "friction machines". We illustrate these theoretical points through a dive into three case studies conducted with applied anthropologist in the movie industry, urban planning, and research
Cognitive science · Computer Science · Modeling, Simulation, and Optimization · Multi-Agent Systems and Negotiation · Psychology · Robot Manipulation and Learning · Artificial Intelligence
Closing the loop
Navigating digital geographies
Can Machines Perform a Qualitative Data Analysis? Reading the Debate With Alan Turing
Interventions and dissonance in industrial research
A novel, human-in-the-loop computational grounded theory framework for big social data
A Call for an AI Anthropology
Multi-Agent Ethnography
Recalcitrant audiencing
Updating 'The Future of Coding
Beyond the GenAI gold rush
The Data Revolution
The Onlife Manifesto
ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software
Digital methods as ‘experimental a priori’ – how to navigate vague empirical situations as an operationalist pragmatist
Diagrammatic reasoning
Ethnography
The real-time city? Big data and smart urbanism
Soft City Sensing
Guessing and Abduction
Part of the action, or ‘going native’? Learning to cope with the ‘politics of integration’
The Thick Machine
A view from data science
Algorithmic failure as a humanities methodology
History and Significance of the Emic/Etic Distinction
From dissonance to resonance
| Unique citing works | 10 |
|---|---|
| Citations per year | 5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 9 |