Artificial Intelligence—The Driving Force of Industry 4.0

Magd, Hesham; Jonathan, Henry; Khan, Shad Ahmad; Geddawy, Mohamed El

doi:10.1002/9781119905141.ch1

Cited by 6 publications

(2 citation statements)

References 8 publications

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“…The development of information technologies, from systems that only manage project planning and resources, to complex systems that function at the project level, is presented in works [2,3]. These works highlight the main trends in the development of tools.…”

Section: References Analysis and Problem Statementmentioning

confidence: 99%

Development of a multilingual intelligent project planning and monitoring system

Teslia

Yehorchenkova

Yehorchenkov

et al. 2023

EEJET

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The object of research of this work is the processes of project planning and monitoring. The solved problem is the development of a model, method and structures of a multilingual intelligent project planning and monitoring system and its experimental verification of the ability to understand the statements of managers in different languages. The requirements for such a system are formulated. An analysis of the existing theoretical and practical developments in this area was carried out. It was established that there are no developments in the field of project management that can adapt to new natural languages. It was found that the formulated requirements can be satisfied within the framework of the reflexive approach. It is characterized by simplicity, continuity, and insensitivity to errors in natural language statements. To confirm these assumptions, an experimental multilingual project planning and monitoring system and experimental research methodology were developed. The results of the experiments obtained during the use of the created experimental system testify to the correct identification of the content of appeals to the intellectual system in 6 languages with a probability higher than 0.99, and to recognize the structure of statements with a probability higher than 0.98. And the time for configuring the system to work with a new language did not exceed 1 hour. This allows to use it for practical work in distributed management systems for remote interaction of managers and specialists with the system in different languages. The conducted experiments confirmed the assumption about the effectiveness of the reflexive approach for creating project management systems. The developed model, method, structures, and system can be used for different types of projects, such as regional development projects, IT, etc.

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Section: References Analysis and Problem Statementmentioning

confidence: 99%

Development of a multilingual intelligent project planning and monitoring system

Teslia

Yehorchenkova

Yehorchenkov

et al. 2023

EEJET

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“…Artificial intelligence (AI) is the driving force behind industry 4.0 and has profoundly affected manufacturing, business, work, and our daily life ( Magd et al, 2022 ). The invention of generative AI technologies, such as ChatGPT, marks a particularly significant leap in AI’s competence.…”

Section: Introductionmentioning

confidence: 99%

Developing trustworthy artificial intelligence: insights from research on interpersonal, human-automation, and human-AI trust

Li,

Wu,

Huang

et al. 2024

Front. Psychol.

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The rapid advancement of artificial intelligence (AI) has impacted society in many aspects. Alongside this progress, concerns such as privacy violation, discriminatory bias, and safety risks have also surfaced, highlighting the need for the development of ethical, responsible, and socially beneficial AI. In response, the concept of trustworthy AI has gained prominence, and several guidelines for developing trustworthy AI have been proposed. Against this background, we demonstrate the significance of psychological research in identifying factors that contribute to the formation of trust in AI. Specifically, we review research findings on interpersonal, human-automation, and human-AI trust from the perspective of a three-dimension framework (i.e., the trustor, the trustee, and their interactive context). The framework synthesizes common factors related to trust formation and maintenance across different trust types. These factors point out the foundational requirements for building trustworthy AI and provide pivotal guidance for its development that also involves communication, education, and training for users. We conclude by discussing how the insights in trust research can help enhance AI’s trustworthiness and foster its adoption and application.

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