Personalising explainable recommendations: Literature and conceptualisation

Mohammad Naiseh; Nan Jiang; Jianbing Ma; Raian Ali

doi:10.1007/978-3-030-45691-7_49

Personalising explainable recommendations: Literature and conceptualisation

Mohammad Naiseh^*, Nan Jiang, Jianbing Ma, Raian Ali

^*Corresponding author for this work

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

28 Citations (Scopus)

Abstract

Explanations in intelligent systems aim to enhance a users’ understandability of their reasoning process and the resulted decisions and recommendations. Explanations typically increase trust, user acceptance and retention. The need for explanations is on the rise due to the increasing public concerns about AI and the emergence of new laws, such as the General Data Protection Regulation (GDPR) in Europe. However, users are different in their needs for explanations, and such needs can depend on their dynamic context. Explanations suffer the risk of being seen as information overload, and this makes personalisation more needed. In this paper, we review literature around personalising explanations in intelligent systems. We synthesise a conceptualisation that puts together various aspects being considered important for the personalisation needs and implementation. Moreover, we identify several challenges which would need more research, including the frequency of explanation and their evolution in tandem with the ongoing user experience.

Original language	English
Title of host publication	Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020
Editors	Álvaro Rocha, Hojjat Adeli, Luís Paulo Reis, Sandra Costanzo, Irena Orovic, Fernando Moreira
Publisher	Springer
Pages	518-533
Number of pages	16
ISBN (Print)	9783030456900
DOIs	https://doi.org/10.1007/978-3-030-45691-7_49
Publication status	Published - 2020
Externally published	Yes
Event	8th World Conference on Information Systems and Technologies, WorldCIST 2020 - Budva, Montenegro Duration: 7 Apr 2020 → 10 Apr 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1160 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	8th World Conference on Information Systems and Technologies, WorldCIST 2020
Country/Territory	Montenegro
City	Budva
Period	7/04/20 → 10/04/20

Keywords

Explanations
Human-computer interaction
Intelligent systems
Personalisation

Access to Document

10.1007/978-3-030-45691-7_49

Cite this

Naiseh, M., Jiang, N., Ma, J., & Ali, R. (2020). Personalising explainable recommendations: Literature and conceptualisation. In Á. Rocha, H. Adeli, L. P. Reis, S. Costanzo, I. Orovic, & F. Moreira (Eds.), Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020 (pp. 518-533). (Advances in Intelligent Systems and Computing; Vol. 1160 AISC). Springer. https://doi.org/10.1007/978-3-030-45691-7_49

Naiseh, Mohammad ; Jiang, Nan ; Ma, Jianbing et al. / Personalising explainable recommendations : Literature and conceptualisation. Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020. editor / Álvaro Rocha ; Hojjat Adeli ; Luís Paulo Reis ; Sandra Costanzo ; Irena Orovic ; Fernando Moreira. Springer, 2020. pp. 518-533 (Advances in Intelligent Systems and Computing).

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title = "Personalising explainable recommendations: Literature and conceptualisation",

abstract = "Explanations in intelligent systems aim to enhance a users{\textquoteright} understandability of their reasoning process and the resulted decisions and recommendations. Explanations typically increase trust, user acceptance and retention. The need for explanations is on the rise due to the increasing public concerns about AI and the emergence of new laws, such as the General Data Protection Regulation (GDPR) in Europe. However, users are different in their needs for explanations, and such needs can depend on their dynamic context. Explanations suffer the risk of being seen as information overload, and this makes personalisation more needed. In this paper, we review literature around personalising explanations in intelligent systems. We synthesise a conceptualisation that puts together various aspects being considered important for the personalisation needs and implementation. Moreover, we identify several challenges which would need more research, including the frequency of explanation and their evolution in tandem with the ongoing user experience.",

keywords = "Explanations, Human-computer interaction, Intelligent systems, Personalisation",

author = "Mohammad Naiseh and Nan Jiang and Jianbing Ma and Raian Ali",

note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.; 8th World Conference on Information Systems and Technologies, WorldCIST 2020 ; Conference date: 07-04-2020 Through 10-04-2020",

year = "2020",

doi = "10.1007/978-3-030-45691-7_49",

language = "English",

isbn = "9783030456900",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "518--533",

editor = "{\'A}lvaro Rocha and Hojjat Adeli and Reis, {Lu{\'i}s Paulo} and Sandra Costanzo and Irena Orovic and Fernando Moreira",

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Naiseh, M, Jiang, N, Ma, J & Ali, R 2020, Personalising explainable recommendations: Literature and conceptualisation. in Á Rocha, H Adeli, LP Reis, S Costanzo, I Orovic & F Moreira (eds), Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020. Advances in Intelligent Systems and Computing, vol. 1160 AISC, Springer, pp. 518-533, 8th World Conference on Information Systems and Technologies, WorldCIST 2020, Budva, Montenegro, 7/04/20. https://doi.org/10.1007/978-3-030-45691-7_49

Personalising explainable recommendations: Literature and conceptualisation. / Naiseh, Mohammad; Jiang, Nan; Ma, Jianbing et al.
Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020. ed. / Álvaro Rocha; Hojjat Adeli; Luís Paulo Reis; Sandra Costanzo; Irena Orovic; Fernando Moreira. Springer, 2020. p. 518-533 (Advances in Intelligent Systems and Computing; Vol. 1160 AISC).

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

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T1 - Personalising explainable recommendations

T2 - 8th World Conference on Information Systems and Technologies, WorldCIST 2020

AU - Naiseh, Mohammad

AU - Jiang, Nan

AU - Ma, Jianbing

AU - Ali, Raian

N1 - Publisher Copyright: © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

PY - 2020

Y1 - 2020

N2 - Explanations in intelligent systems aim to enhance a users’ understandability of their reasoning process and the resulted decisions and recommendations. Explanations typically increase trust, user acceptance and retention. The need for explanations is on the rise due to the increasing public concerns about AI and the emergence of new laws, such as the General Data Protection Regulation (GDPR) in Europe. However, users are different in their needs for explanations, and such needs can depend on their dynamic context. Explanations suffer the risk of being seen as information overload, and this makes personalisation more needed. In this paper, we review literature around personalising explanations in intelligent systems. We synthesise a conceptualisation that puts together various aspects being considered important for the personalisation needs and implementation. Moreover, we identify several challenges which would need more research, including the frequency of explanation and their evolution in tandem with the ongoing user experience.

AB - Explanations in intelligent systems aim to enhance a users’ understandability of their reasoning process and the resulted decisions and recommendations. Explanations typically increase trust, user acceptance and retention. The need for explanations is on the rise due to the increasing public concerns about AI and the emergence of new laws, such as the General Data Protection Regulation (GDPR) in Europe. However, users are different in their needs for explanations, and such needs can depend on their dynamic context. Explanations suffer the risk of being seen as information overload, and this makes personalisation more needed. In this paper, we review literature around personalising explanations in intelligent systems. We synthesise a conceptualisation that puts together various aspects being considered important for the personalisation needs and implementation. Moreover, we identify several challenges which would need more research, including the frequency of explanation and their evolution in tandem with the ongoing user experience.

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A2 - Moreira, Fernando

PB - Springer

Y2 - 7 April 2020 through 10 April 2020

ER -

Naiseh M, Jiang N, Ma J, Ali R. Personalising explainable recommendations: Literature and conceptualisation. In Rocha Á, Adeli H, Reis LP, Costanzo S, Orovic I, Moreira F, editors, Trends and Innovations in Information Systems and Technologies - Volume 2, WorldCIST 2020. Springer. 2020. p. 518-533. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-45691-7_49

Personalising explainable recommendations: Literature and conceptualisation

Abstract

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Keywords

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