Features of Human-Centred Algorithm Design

Marianne Cherrington; David Airehrour; Joan Lu; Qiang Xu; David Cameron-Brown; Ihaka Dunn

doi:10.1109/ITNAC50341.2020.9315169

Features of Human-Centred Algorithm Design

Marianne Cherrington, David Airehrour, Joan Lu, Qiang Xu, David Cameron-Brown, Ihaka Dunn

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

6 Citations (Scopus)

Abstract

Algorithms are pervasive, unseen influencers of decisions. Algorithmic features can fluctuate widely, depending on use, user or criteria applied. This paper considers the nascent field of human-centred algorithm design (HCAD), intersecting human-centred design and algorithmic systems. Human-centred, more-than-metric feature selection approaches, create fairer and deeper meaning. More value is created. The unique impact of this paper is to integrate feature selection within a technology HCAD strategy, for a novel, innovative HCAD approach to machine learning. This flexible and evaluative approach can support data advances with human-social nuance, designed for purpose with knowledge for data-driven decisions. The design of machine learning algorithms to the uses in which they will be employed is user-centric. This is important within environments utilising automated, semi-automated or high-performance analytics.

Original language	English
Title of host publication	2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	9781728188270, 9781728188263
ISBN (Print)	9781728188287
DOIs	https://doi.org/10.1109/ITNAC50341.2020.9315169
Publication status	Published - 25 Nov 2020
Event	30th International Telecommunication Networks and Applications Conference - Held virtually due to COVID19, Melbourne, Australia Duration: 25 Nov 2020 → 27 Nov 2020 Conference number: 30 https://itnac.org.au/2020/25-27-november-2020-melbourne-australia https://www.computer.org/csdl/proceedings/itnac/2020/1qmfDJ9xfUc

Publication series

Name	International Telecommunication Networks and Applications Conference
Publisher	IEEE
ISSN (Print)	2474-1531
ISSN (Electronic)	2474-154X

Conference

Conference	30th International Telecommunication Networks and Applications Conference
Abbreviated title	ITNAC 2020
Country/Territory	Australia
City	Melbourne
Period	25/11/20 → 27/11/20
Internet address	https://itnac.org.au/2020/25-27-november-2020-melbourne-australia https://www.computer.org/csdl/proceedings/itnac/2020/1qmfDJ9xfUc

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Cherrington, M., Airehrour, D., Lu, J., Xu, Q., Cameron-Brown, D., & Dunn, I. (2020). Features of Human-Centred Algorithm Design. In 2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020 [9315169] (International Telecommunication Networks and Applications Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITNAC50341.2020.9315169

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title = "Features of Human-Centred Algorithm Design",

abstract = "Algorithms are pervasive, unseen influencers of decisions. Algorithmic features can fluctuate widely, depending on use, user or criteria applied. This paper considers the nascent field of human-centred algorithm design (HCAD), intersecting human-centred design and algorithmic systems. Human-centred, more-than-metric feature selection approaches, create fairer and deeper meaning. More value is created. The unique impact of this paper is to integrate feature selection within a technology HCAD strategy, for a novel, innovative HCAD approach to machine learning. This flexible and evaluative approach can support data advances with human-social nuance, designed for purpose with knowledge for data-driven decisions. The design of machine learning algorithms to the uses in which they will be employed is user-centric. This is important within environments utilising automated, semi-automated or high-performance analytics.",

keywords = "Algorithmic bias, Big data, Design features, Feature selection, High dimensional data, Human-centred algorithm design",

author = "Marianne Cherrington and David Airehrour and Joan Lu and Qiang Xu and David Cameron-Brown and Ihaka Dunn",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 30th International Telecommunication Networks and Applications Conference, ITNAC 2020 ; Conference date: 25-11-2020 Through 27-11-2020",

year = "2020",

month = nov,

day = "25",

doi = "10.1109/ITNAC50341.2020.9315169",

language = "English",

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series = "International Telecommunication Networks and Applications Conference",

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booktitle = "2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020",

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url = "https://itnac.org.au/2020/25-27-november-2020-melbourne-australia, https://www.computer.org/csdl/proceedings/itnac/2020/1qmfDJ9xfUc",

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Cherrington, M, Airehrour, D, Lu, J, Xu, Q, Cameron-Brown, D & Dunn, I 2020, Features of Human-Centred Algorithm Design. in 2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020., 9315169, International Telecommunication Networks and Applications Conference, Institute of Electrical and Electronics Engineers Inc., 30th International Telecommunication Networks and Applications Conference, Melbourne, Victoria, Australia, 25/11/20. https://doi.org/10.1109/ITNAC50341.2020.9315169

Features of Human-Centred Algorithm Design. / Cherrington, Marianne; Airehrour, David; Lu, Joan et al.

2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9315169 (International Telecommunication Networks and Applications Conference).

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

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T1 - Features of Human-Centred Algorithm Design

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AU - Airehrour, David

AU - Lu, Joan

AU - Xu, Qiang

AU - Cameron-Brown, David

AU - Dunn, Ihaka

N1 - Conference code: 30

PY - 2020/11/25

Y1 - 2020/11/25

N2 - Algorithms are pervasive, unseen influencers of decisions. Algorithmic features can fluctuate widely, depending on use, user or criteria applied. This paper considers the nascent field of human-centred algorithm design (HCAD), intersecting human-centred design and algorithmic systems. Human-centred, more-than-metric feature selection approaches, create fairer and deeper meaning. More value is created. The unique impact of this paper is to integrate feature selection within a technology HCAD strategy, for a novel, innovative HCAD approach to machine learning. This flexible and evaluative approach can support data advances with human-social nuance, designed for purpose with knowledge for data-driven decisions. The design of machine learning algorithms to the uses in which they will be employed is user-centric. This is important within environments utilising automated, semi-automated or high-performance analytics.

AB - Algorithms are pervasive, unseen influencers of decisions. Algorithmic features can fluctuate widely, depending on use, user or criteria applied. This paper considers the nascent field of human-centred algorithm design (HCAD), intersecting human-centred design and algorithmic systems. Human-centred, more-than-metric feature selection approaches, create fairer and deeper meaning. More value is created. The unique impact of this paper is to integrate feature selection within a technology HCAD strategy, for a novel, innovative HCAD approach to machine learning. This flexible and evaluative approach can support data advances with human-social nuance, designed for purpose with knowledge for data-driven decisions. The design of machine learning algorithms to the uses in which they will be employed is user-centric. This is important within environments utilising automated, semi-automated or high-performance analytics.

KW - Algorithmic bias

KW - Big data

KW - Design features

KW - Feature selection

KW - High dimensional data

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T3 - International Telecommunication Networks and Applications Conference

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ER -

Cherrington M, Airehrour D, Lu J, Xu Q, Cameron-Brown D, Dunn I. Features of Human-Centred Algorithm Design. In 2020 30th International Telecommunication Networks and Applications Conference, ITNAC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9315169. (International Telecommunication Networks and Applications Conference). doi: 10.1109/ITNAC50341.2020.9315169

Features of Human-Centred Algorithm Design

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