Investigating ADM in Shared Mobility: A Design Ethnographic Approach

Vaike Fors; Meike  Brodersen; Kaspar Raats; Sarah Pink; Rachel Charlotte Smith

Investigating ADM in Shared Mobility: A Design Ethnographic Approach

Vaike Fors^*, Meike Brodersen, Kaspar Raats, Sarah Pink, Rachel Charlotte Smith

^*Corresponding author for this work

School of Communication and Culture - Department of Digital Design and Information Studies

Research output: Contribution to book/anthology/report/proceeding › Book chapter › Research › peer-review

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Abstract

In this chapter, we demonstrate how a design ethnographic approach to future algorithm-powered mobility solutions opens up possibilities to research social implications of automated decision making (ADM) from a situational perspective, by investigating the context of ADM rather than simply observing the technology itself and how it is used. The context of our discussion is one where the development of autonomous vehicles and artificial intelligence (AI) applications, in the service of transportation, has sparked a renewed research interest into shared mobility systems, and how these can respond to emerging challenges of rising traffic congestion and pollution levels. Our research addresses the gap between algorithm-based approaches to designing for optimizing, streamlining, and efficiency, the questions of how these systems and services are activated in people’s everyday life, and how they interfere with decision-making around traveling and shared mobility. We argue that to understand how these services and technologies will be adopted and implemented in society, research attention must be directed to people in real-life situations where this type of ADM operates.

Original language	English
Title of host publication	Everyday Automation : Experiencing and Anticipating Emerging Technologies
Editors	Sarah Pink, Martin Berg, Deborah Lupton, Minna Ruckenstein
Place of publication	London
Publisher	Routledge
Publication date	Apr 2022
Pages	197-212
Chapter	13
ISBN (Electronic)	9781003170884
Publication status	Published - Apr 2022

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10.4324_9781003170884-17_chapterpdfFinal published version, 989 KBLicence: CC BY-NC-ND

AHA II: Design Ethnographic Living Labs for Future Urban Mobility - A Human Approach
Fors, V. (PI), Smith, R. C. (Collaborator), Pink, S. (Collaborator), Lund, J. (Participant), Raats, K. (Participant), Ebbesson, E. (Participant), Osz, K. (Participant), Brodersen, M. (Participant) & Lutz, P. (Participant)
01/10/2019 → 31/12/2022
Project: Research
Re-humanising Automated Decision-Making
Berg, M. (PI), Svensson, J. (Participant), Lupton, D. (Participant), Fors, V. (Participant), Pink, S. (Participant), Lanzeni, D. (Participant), Raats, K. (Participant), Rolandsson, B. (Participant), Ruckenstein, M. (Participant), Smith, R. C. (Participant) & Velkova, J. (Participant)
14/06/2019 → 31/12/2023
Project: Research

Cite this

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title = "Investigating ADM in Shared Mobility: A Design Ethnographic Approach",

abstract = "In this chapter, we demonstrate how a design ethnographic approach to future algorithm-powered mobility solutions opens up possibilities to research social implications of automated decision making (ADM) from a situational perspective, by investigating the context of ADM rather than simply observing the technology itself and how it is used. The context of our discussion is one where the development of autonomous vehicles and artificial intelligence (AI) applications, in the service of transportation, has sparked a renewed research interest into shared mobility systems, and how these can respond to emerging challenges of rising traffic congestion and pollution levels. Our research addresses the gap between algorithm-based approaches to designing for optimizing, streamlining, and efficiency, the questions of how these systems and services are activated in people{\textquoteright}s everyday life, and how they interfere with decision-making around traveling and shared mobility. We argue that to understand how these services and technologies will be adopted and implemented in society, research attention must be directed to people in real-life situations where this type of ADM operates.",

author = "Vaike Fors and Meike Brodersen and Kaspar Raats and Sarah Pink and Smith, {Rachel Charlotte}",

note = "OA Funder: Malm{\"o} University Data Society ",

year = "2022",

month = apr,

language = "English",

pages = "197--212",

editor = "Pink, {Sarah } and Berg, {Martin } and Deborah Lupton and Minna Ruckenstein",

booktitle = "Everyday Automation",

publisher = "Routledge",

}

Investigating ADM in Shared Mobility: A Design Ethnographic Approach. / Fors, Vaike; Brodersen, Meike ; Raats, Kaspar et al.
Everyday Automation: Experiencing and Anticipating Emerging Technologies. ed. / Sarah Pink; Martin Berg; Deborah Lupton; Minna Ruckenstein. London: Routledge, 2022. p. 197-212.

Research output: Contribution to book/anthology/report/proceeding › Book chapter › Research › peer-review

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T1 - Investigating ADM in Shared Mobility: A Design Ethnographic Approach

AU - Fors, Vaike

AU - Brodersen, Meike

AU - Raats, Kaspar

AU - Pink, Sarah

AU - Smith, Rachel Charlotte

N1 - OA Funder: Malmö University Data Society

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N2 - In this chapter, we demonstrate how a design ethnographic approach to future algorithm-powered mobility solutions opens up possibilities to research social implications of automated decision making (ADM) from a situational perspective, by investigating the context of ADM rather than simply observing the technology itself and how it is used. The context of our discussion is one where the development of autonomous vehicles and artificial intelligence (AI) applications, in the service of transportation, has sparked a renewed research interest into shared mobility systems, and how these can respond to emerging challenges of rising traffic congestion and pollution levels. Our research addresses the gap between algorithm-based approaches to designing for optimizing, streamlining, and efficiency, the questions of how these systems and services are activated in people’s everyday life, and how they interfere with decision-making around traveling and shared mobility. We argue that to understand how these services and technologies will be adopted and implemented in society, research attention must be directed to people in real-life situations where this type of ADM operates.

AB - In this chapter, we demonstrate how a design ethnographic approach to future algorithm-powered mobility solutions opens up possibilities to research social implications of automated decision making (ADM) from a situational perspective, by investigating the context of ADM rather than simply observing the technology itself and how it is used. The context of our discussion is one where the development of autonomous vehicles and artificial intelligence (AI) applications, in the service of transportation, has sparked a renewed research interest into shared mobility systems, and how these can respond to emerging challenges of rising traffic congestion and pollution levels. Our research addresses the gap between algorithm-based approaches to designing for optimizing, streamlining, and efficiency, the questions of how these systems and services are activated in people’s everyday life, and how they interfere with decision-making around traveling and shared mobility. We argue that to understand how these services and technologies will be adopted and implemented in society, research attention must be directed to people in real-life situations where this type of ADM operates.

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Investigating ADM in Shared Mobility: A Design Ethnographic Approach

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Projects

AHA II: Design Ethnographic Living Labs for Future Urban Mobility - A Human Approach

Re-humanising Automated Decision-Making

Cite this