Modeling needs user modeling

Mustafa Mert Çelikok; Pierre Alexandre Murena; Samuel Kaski

doi:10.3389/frai.2023.1097891

Modeling needs user modeling

Mustafa Mert Çelikok, Pierre Alexandre Murena, Samuel Kaski^*

^*Corresponding author for this work

University of Manchester

Research output: Contribution to journal › Article › Scientific › peer-review

2 Citations (Scopus)

56 Downloads (Pure)

Abstract

Modeling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modeling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modeling a broader set of problems, through iterative modeling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modeling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modeling workflows, and human-centric or human-compatible machine learning pipelines.

Original language	English
Article number	1097891
Pages (from-to)	1-6
Number of pages	6
Journal	Frontiers in Artificial Intelligence
Volume	6
DOIs	https://doi.org/10.3389/frai.2023.1097891
Publication status	Published - 2023
MoE publication type	A1 Journal article-refereed

Funding

This work was supported by the Academy of Finland (Flagship programme: Finnish Center for Artificial Intelligence FCAI and decision 345604) Humane-AI-NET and ELISE Networks of Excellence Centres (EU Horizon: 2020 grant agreements 952026 and 951847), UKRI Turing AI World-Leading Researcher Fellowship (EP/W002973/1), and a KAUTE Foundation personal grant for MÇ.

Keywords

AI assistance
human-centric artificial intelligence
human–AI collaboration
human–AI interaction
machine learning
probabilistic modeling
user modeling

Access to Document

10.3389/frai.2023.1097891Licence: CC BY

Modeling needs user modelingFinal published version, 1 MBLicence: CC BY

Cite this

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title = "Modeling needs user modeling",

abstract = "Modeling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modeling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modeling a broader set of problems, through iterative modeling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modeling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modeling workflows, and human-centric or human-compatible machine learning pipelines.",

keywords = "AI assistance, human-centric artificial intelligence, human–AI collaboration, human–AI interaction, machine learning, probabilistic modeling, user modeling",

author = "{\c C}elikok, \{Mustafa Mert\} and Murena, \{Pierre Alexandre\} and Samuel Kaski",

note = "Funding Information: This work was supported by the Academy of Finland (Flagship programme: Finnish Center for Artificial Intelligence FCAI and decision 345604) Humane-AI-NET and ELISE Networks of Excellence Centres (EU Horizon: 2020 grant agreements 952026 and 951847), UKRI Turing AI World-Leading Researcher Fellowship (EP/W002973/1), and a KAUTE Foundation personal grant for M{\c C}. | openaire: EC/H2020/952026/EU//HumanE-AI-Net | openaire: EC/H2020/951847/EU//ELISE ",

year = "2023",

doi = "10.3389/frai.2023.1097891",

language = "English",

volume = "6",

pages = "1--6",

journal = "Frontiers in Artificial Intelligence",

issn = "2624-8212",

publisher = "Frontiers Media",

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T1 - Modeling needs user modeling

AU - Çelikok, Mustafa Mert

AU - Murena, Pierre Alexandre

AU - Kaski, Samuel

N1 - Funding Information: This work was supported by the Academy of Finland (Flagship programme: Finnish Center for Artificial Intelligence FCAI and decision 345604) Humane-AI-NET and ELISE Networks of Excellence Centres (EU Horizon: 2020 grant agreements 952026 and 951847), UKRI Turing AI World-Leading Researcher Fellowship (EP/W002973/1), and a KAUTE Foundation personal grant for MÇ. | openaire: EC/H2020/952026/EU//HumanE-AI-Net | openaire: EC/H2020/951847/EU//ELISE

PY - 2023

Y1 - 2023

N2 - Modeling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modeling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modeling a broader set of problems, through iterative modeling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modeling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modeling workflows, and human-centric or human-compatible machine learning pipelines.

AB - Modeling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modeling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modeling a broader set of problems, through iterative modeling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modeling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modeling workflows, and human-centric or human-compatible machine learning pipelines.

KW - AI assistance

KW - human-centric artificial intelligence

KW - human–AI collaboration

KW - human–AI interaction

KW - machine learning

KW - probabilistic modeling

KW - user modeling

UR - https://www.scopus.com/pages/publications/85153508715

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SN - 2624-8212

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SP - 1

EP - 6

JO - Frontiers in Artificial Intelligence

JF - Frontiers in Artificial Intelligence

M1 - 1097891

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Modeling needs user modeling

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

MAMAA /Kaski S.: Maximally Autonomous AI Assistant/Kaski S.

HumanE-AI-Net: HumanE AI Network

ELISE: European Learning and Intelligent Systems Excellence

Cite this

Modeling needs user modeling

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Projects

MAMAA /Kaski S.: Maximally Autonomous AI Assistant/Kaski S.

HumanE-AI-Net: HumanE AI Network

ELISE: European Learning and Intelligent Systems Excellence

Cite this