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The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence. / Nechesov, Andrey V.; Vityaev, Evgenii E.; Goncharov, Sergey S. et al.

In: Bulletin of Irkutsk State University, Series Mathematics, Vol. 54, 7, 2025, p. 96-112.

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Nechesov AV, Vityaev EE, Goncharov SS, Sviridenko DI. The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence. Bulletin of Irkutsk State University, Series Mathematics. 2025;54:96-112. 7. doi: 10.26516/1997-7670.2025.54.96

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@article{b4489658a02e4b43bd6bb3c935485b5a,
title = "The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence",
abstract = "While AI systems excel at reasoning within formal frameworks, their tendency to hallucinate remains a critical challenge. This paper proposes a task-basedapproach to enhance reliability. By focusing on the specific task and its resolution criteria, we ensure AI solutions are informed by a deep understanding of the problem{\textquoteright}s inherent limitations, including its defining axioms and theorems. This comprehension of the problem{\textquoteright}s structure and constraints is key to mitigating hallucination and building trustworthy AI.",
keywords = "agent-based approach, artificial intelligence, computability, machine learning, semantic modeling, task approach, artificial intelligence, machine learning, agent-based approach, task approach, computability, semantic modeling",
author = "Nechesov, {Andrey V.} and Vityaev, {Evgenii E.} and Goncharov, {Sergey S.} and Sviridenko, {Dmitry I.}",
note = "Nechesov A. V., Vityaev E. E., Goncharov S. S., Sviridenko D. I. The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence. The Bulletin of Irkutsk State University. Series Mathematics, 2025, vol. 54, pp. 96–112. https://doi.org/10.26516/1997-7670.2025.54.96 This work was supported by a grant for research centers, provided by the Ministry of Economic Development of the Russian Federation in accordance with the subsidy agreement with the Novosibirsk State University dated April 17, 2025 No.139-15-2025-006: IGK 000000C313925P3S0002.",
year = "2025",
doi = "10.26516/1997-7670.2025.54.96",
language = "English",
volume = "54",
pages = "96--112",
journal = "Bulletin of Irkutsk State University, Series Mathematics",
issn = "1997-7670",
publisher = "Иркутский государственный университет",

}

RIS

TY - JOUR

T1 - The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence

AU - Nechesov, Andrey V.

AU - Vityaev, Evgenii E.

AU - Goncharov, Sergey S.

AU - Sviridenko, Dmitry I.

N1 - Nechesov A. V., Vityaev E. E., Goncharov S. S., Sviridenko D. I. The Task-Based Approach: A New Paradigm for Building Trustworthy Artificial Intelligence. The Bulletin of Irkutsk State University. Series Mathematics, 2025, vol. 54, pp. 96–112. https://doi.org/10.26516/1997-7670.2025.54.96 This work was supported by a grant for research centers, provided by the Ministry of Economic Development of the Russian Federation in accordance with the subsidy agreement with the Novosibirsk State University dated April 17, 2025 No.139-15-2025-006: IGK 000000C313925P3S0002.

PY - 2025

Y1 - 2025

N2 - While AI systems excel at reasoning within formal frameworks, their tendency to hallucinate remains a critical challenge. This paper proposes a task-basedapproach to enhance reliability. By focusing on the specific task and its resolution criteria, we ensure AI solutions are informed by a deep understanding of the problem’s inherent limitations, including its defining axioms and theorems. This comprehension of the problem’s structure and constraints is key to mitigating hallucination and building trustworthy AI.

AB - While AI systems excel at reasoning within formal frameworks, their tendency to hallucinate remains a critical challenge. This paper proposes a task-basedapproach to enhance reliability. By focusing on the specific task and its resolution criteria, we ensure AI solutions are informed by a deep understanding of the problem’s inherent limitations, including its defining axioms and theorems. This comprehension of the problem’s structure and constraints is key to mitigating hallucination and building trustworthy AI.

KW - agent-based approach

KW - artificial intelligence

KW - computability

KW - machine learning

KW - semantic modeling

KW - task approach

KW - artificial intelligence

KW - machine learning

KW - agent-based approach

KW - task approach

KW - computability

KW - semantic modeling

UR - https://www.scopus.com/pages/publications/105023650466

UR - https://www.mendeley.com/catalogue/410e80a6-ef65-3ab4-996d-f82ccbf8b1e7/

U2 - 10.26516/1997-7670.2025.54.96

DO - 10.26516/1997-7670.2025.54.96

M3 - Article

VL - 54

SP - 96

EP - 112

JO - Bulletin of Irkutsk State University, Series Mathematics

JF - Bulletin of Irkutsk State University, Series Mathematics

SN - 1997-7670

M1 - 7

ER -

ID: 72664944