Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context

Auste Simkute; Ewa Luger; Mike Evans; Rhianne Jones

doi:10.1145/3393914.3395862

Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context

Auste Simkute, Ewa Luger, Mike Evans, Rhianne Jones

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Algorithms support decision-making in various contexts, often diminishing human agency in the process. Without meaningful human input, use of predictive systems can result in costly errors, leaving users unable to evaluate accuracy. Intelligibility is one design criterion that may ensure users remain in the decision-making loop. However, guidance is currently diffuse and focused on the lay user, ignoring the role of expertise. We propose a cognitive psychology-based framework that segments decision-making space by users' expertise, risk-environment and motivation. We illustrate this by focusing on expertise, exploring how we might inform usable intelligibility in interface design, enhancing user agency in the decision-making process.

Original language	English
Title of host publication	DIS 2020 Companion
Subtitle of host publication	Companion Publication of the 2020 ACM Designing Interactive Systems Conference
Publisher	Association for Computing Machinery, Inc
Pages	263-268
Number of pages	6
ISBN (Electronic)	9781450379878
DOIs	https://doi.org/10.1145/3393914.3395862
Publication status	Published - 6 Jul 2020
Event	2020 ACM Conference on Designing Interactive Systems, DIS 2020 - Eindhoven, Netherlands Duration: 6 Jul 2020 → 10 Jul 2020

Conference

Conference	2020 ACM Conference on Designing Interactive Systems, DIS 2020
Country/Territory	Netherlands
City	Eindhoven
Period	6/07/20 → 10/07/20

Keywords / Materials (for Non-textual outputs)

algorithm supported decision-making
expertise
explainable ml
human-in-the-loop
intelligibility

Access to Document

10.1145/3393914.3395862

Cite this

@inproceedings{42daf6c206394ceca3681ce5cea4ab28,

title = "Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context",

abstract = "Algorithms support decision-making in various contexts, often diminishing human agency in the process. Without meaningful human input, use of predictive systems can result in costly errors, leaving users unable to evaluate accuracy. Intelligibility is one design criterion that may ensure users remain in the decision-making loop. However, guidance is currently diffuse and focused on the lay user, ignoring the role of expertise. We propose a cognitive psychology-based framework that segments decision-making space by users' expertise, risk-environment and motivation. We illustrate this by focusing on expertise, exploring how we might inform usable intelligibility in interface design, enhancing user agency in the decision-making process.",

keywords = "algorithm supported decision-making, expertise, explainable ml, human-in-the-loop, intelligibility",

author = "Auste Simkute and Ewa Luger and Mike Evans and Rhianne Jones",

note = "Funding Information: The authors gratefully acknowledge support from EPSRC grants EP/T517501/1 and EP/S035362/1. Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 2020 ACM Conference on Designing Interactive Systems, DIS 2020 ; Conference date: 06-07-2020 Through 10-07-2020",

year = "2020",

month = jul,

day = "6",

doi = "10.1145/3393914.3395862",

language = "English",

pages = "263--268",

booktitle = "DIS 2020 Companion",

publisher = "Association for Computing Machinery, Inc",

}

Simkute, A, Luger, E, Evans, M & Jones, R 2020, Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context. in DIS 2020 Companion: Companion Publication of the 2020 ACM Designing Interactive Systems Conference. Association for Computing Machinery, Inc, pp. 263-268, 2020 ACM Conference on Designing Interactive Systems, DIS 2020, Eindhoven, Netherlands, 6/07/20. https://doi.org/10.1145/3393914.3395862

Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context. / Simkute, Auste; Luger, Ewa; Evans, Mike et al.
DIS 2020 Companion: Companion Publication of the 2020 ACM Designing Interactive Systems Conference. Association for Computing Machinery, Inc, 2020. p. 263-268.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Experts in the shadow of algorithmic systems

T2 - 2020 ACM Conference on Designing Interactive Systems, DIS 2020

AU - Simkute, Auste

AU - Luger, Ewa

AU - Evans, Mike

AU - Jones, Rhianne

PY - 2020/7/6

Y1 - 2020/7/6

N2 - Algorithms support decision-making in various contexts, often diminishing human agency in the process. Without meaningful human input, use of predictive systems can result in costly errors, leaving users unable to evaluate accuracy. Intelligibility is one design criterion that may ensure users remain in the decision-making loop. However, guidance is currently diffuse and focused on the lay user, ignoring the role of expertise. We propose a cognitive psychology-based framework that segments decision-making space by users' expertise, risk-environment and motivation. We illustrate this by focusing on expertise, exploring how we might inform usable intelligibility in interface design, enhancing user agency in the decision-making process.

AB - Algorithms support decision-making in various contexts, often diminishing human agency in the process. Without meaningful human input, use of predictive systems can result in costly errors, leaving users unable to evaluate accuracy. Intelligibility is one design criterion that may ensure users remain in the decision-making loop. However, guidance is currently diffuse and focused on the lay user, ignoring the role of expertise. We propose a cognitive psychology-based framework that segments decision-making space by users' expertise, risk-environment and motivation. We illustrate this by focusing on expertise, exploring how we might inform usable intelligibility in interface design, enhancing user agency in the decision-making process.

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KW - expertise

KW - explainable ml

KW - human-in-the-loop

KW - intelligibility

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DO - 10.1145/3393914.3395862

M3 - Conference contribution

AN - SCOPUS:85090111422

SP - 263

EP - 268

BT - DIS 2020 Companion

PB - Association for Computing Machinery, Inc

Y2 - 6 July 2020 through 10 July 2020

ER -

Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context

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Experts in the shadow of algorithmic systems: Exploring intelligibility in a decision-making context

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Conference

Keywords / Materials (for Non-textual outputs)

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Other files and links

Fingerprint

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PETRAS 2

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