Artificial intelligence in maintenance: Synthesis of technical issues.

Purpose of the Article. The purpose of the article is to address the regulatory and technical issues of effective creation, operation and operation of safe, reliable and effective systems based on artificial intelligence. The research method. Opportunities for conceptual and logical modeling of ergasystems and invariant architectures of rational modeling based on the problem-oriented version of the integrated “information-cybernetic-didactic” approach using the information and mathematical structure of the automated optical-electronic system of groundspace monitoring are considered. Results. Presented conceptual and logical model of the system of regulatory and technical regulation of systems based on artificial intelligence technologies, and the invariant architecture of the rational model of the artificial intelligence system, developed a method of solving the problem of the operation of the automated optical-electronic system of ground-space monitoring.

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Risk assessment of sewer condition using artificial intelligence tools: application to the SANEST sewer system

Water Science & Technology ◽

10.2166/wst.2013.758 ◽

2013 ◽

Vol 69 (3) ◽

pp. 622-627 ◽

Cited By ~ 3

Author(s):

V. Sousa ◽

J. P. Matos ◽

N. Almeida ◽

J. Saldanha Matos

Keyword(s):

Artificial Intelligence ◽

Asset Management ◽

Support Vector ◽

Support Tools ◽

Maintenance And Rehabilitation ◽

Vector Machines ◽

Technical Issues ◽

Wastewater Infrastructure ◽

Asset Management System

Operation, maintenance and rehabilitation comprise the main concerns of wastewater infrastructure asset management. Given the nature of the service provided by a wastewater system and the characteristics of the supporting infrastructure, technical issues are relevant to support asset management decisions. In particular, in densely urbanized areas served by large, complex and aging sewer networks, the sustainability of the infrastructures largely depends on the implementation of an efficient asset management system. The efficiency of such a system may be enhanced with technical decision support tools. This paper describes the role of artificial intelligence tools such as artificial neural networks and support vector machines for assisting the planning of operation and maintenance activities of wastewater infrastructures. A case study of the application of this type of tool to the wastewater infrastructures of Sistema de Saneamento da Costa do Estoril is presented.

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The development of artificial intelligence in Brazil: emphasis on the military sphere and the questions of intellectual property

Право и политика ◽

10.7256/2454-0706.2021.10.36096 ◽

2021 ◽

pp. 1-21

Author(s):

Ksenia Michailovna Belikova

Keyword(s):

Artificial Intelligence ◽

Intellectual Property ◽

Computational Models ◽

Legal Regulation ◽

The European Union ◽

Technology Infrastructure ◽

Legal Perspective ◽

Technical Issues ◽

The Subject ◽

The Military

The subject of this research is the development of artificial intelligence in Brazil based on the recently adopted act “National Strategy for the Development of Artificial Intelligence” of April 2021 with an emphasis on the military sphere through the prism of legislative provisions on intellectual property, potential and needs of the country, as well as real joint projects with its foreign partner Israel in the sphere of procurement and engineering of unmanned aerial vehicles (Harpia, Elbit Hermes 900 and 450, IAI Heron). The relevance of this article is substantiated by timely consideration of the legal perspective of the approaches of Brazil towards the implementation of artificial intelligence, as multiple foreign states aim to implement the adopted strategies in this sphere. The scientific novelty consists in the following positions: artificial intelligence can be implemented in production, public safety and public authority, through ensuring the due level of the development of such crucial components as education and human resources, scientific and technology infrastructure, and business foundation, legal regulation and management, as well as taking into account international experience. At the same time, the technologies underlying artificial intelligence and machine learning – computational models, algorithms of classification, clusterization, educational, and others are not subject to patenting in Brazil (same as in the European Union), although are regarded as inventions for solution of technical issues – as the engineering applications of artificial intelligence.

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Coarse ethics: how to ethically assess explainable artificial intelligence

AI and Ethics ◽

10.1007/s43681-021-00091-y ◽

2021 ◽

Author(s):

Takashi Izumo ◽

Yueh-Hsuan Weng

Keyword(s):

Artificial Intelligence ◽

Prediction Accuracy ◽

Autonomous Systems ◽

Decision Making Process ◽

Human Society ◽

High Coverage ◽

Trade Off ◽

Order Preservation ◽

Trade Offs ◽

Technical Issues

AbstractThe integration of artificial intelligence (AI) into human society mandates that their decision-making process is explicable to users, as exemplified in Asimov’s Three Laws of Robotics. Such human interpretability calls for explainable AI (XAI), of which this paper cites various models. However, the transaction between computable accuracy and human interpretability can be a trade-off, requiring answers to questions about the negotiable conditions and the degrees of AI prediction accuracy that may be sacrificed to enable user-interpretability. The extant research has focussed on technical issues, but it is also desirable to apply a branch of ethics to deal with the trade-off problem. This scholarly domain is labelled coarse ethics in this study, which discusses two issues vis-à-vis AI prediction as a type of evaluation. First, which formal conditions would allow trade-offs? The study posits two minimal requisites: adequately high coverage and order-preservation. The second issue concerns conditions that could justify the trade-off between computable accuracy and human interpretability, to which the study suggests two justification methods: impracticability and adjustment of perspective from machine-computable to human-interpretable. This study contributes by connecting ethics to autonomous systems for future regulation by formally assessing the adequacy of AI rationales.

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