Technology Aspects of Artificial Intelligence: Industry 5.0 for Organization Decision Making

Chandel, Aditi; Sharma, Bhisham

doi:10.1007/978-3-031-13150-9_7

Cited by 3 publications

(3 citation statements)

References 39 publications

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“…Having this differentiation in mind, intelligence augmentation could happen in different modes or by different strategies, as well as mutually, with AI augmenting human or humans augmenting AI (Jain et al, 2021). This led to different roles evolving for humans and robots, although the distinct, active role of AI was underlined as a prerequisite for teaming (Li et al, 2022;Chandel and Sharma, 2023). The authors claimed that research is needed on the different cooperation modes.…”

Section: Understandings Of Human-ai Teamingmentioning

confidence: 99%

“…One interesting idea shown in some of the publications offers a way to unite the different terms used within the field: the concept of existing collaboration modes or different views on human-AI work. Authors such as McNeese et al (2021), Li et al (2022), Chandel and Sharma (2023), and Endsley (2023) address that there might be different ways (or degrees) of AI and humans collaborating: Some aim to support the human, which reflects more of a cooperative perspective with distinct, not necessarily mutually interdependent tasks. Others are conceptualized as human-AI teams from the very beginning, with mutual intelligence augmentation, dynamic adaptation to one another and collaborative task execution.…”

Section: Current Research Streams and Understandingsmentioning

confidence: 99%

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Defining human-AI teaming the human-centered way: a scoping review and network analysis

Berretta,

Tausch,

Ontrup

et al. 2023

Front. Artif. Intell.

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IntroductionWith the advancement of technology and the increasing utilization of AI, the nature of human work is evolving, requiring individuals to collaborate not only with other humans but also with AI technologies to accomplish complex goals. This requires a shift in perspective from technology-driven questions to a human-centered research and design agenda putting people and evolving teams in the center of attention. A socio-technical approach is needed to view AI as more than just a technological tool, but as a team member, leading to the emergence of human-AI teaming (HAIT). In this new form of work, humans and AI synergistically combine their respective capabilities to accomplish shared goals.MethodsThe aim of our work is to uncover current research streams on HAIT and derive a unified understanding of the construct through a bibliometric network analysis, a scoping review and synthetization of a definition from a socio-technical point of view. In addition, antecedents and outcomes examined in the literature are extracted to guide future research in this field.ResultsThrough network analysis, five clusters with different research focuses on HAIT were identified. These clusters revolve around (1) human and (2) task-dependent variables, (3) AI explainability, (4) AI-driven robotic systems, and (5) the effects of AI performance on human perception. Despite these diverse research focuses, the current body of literature is predominantly driven by a technology-centric and engineering perspective, with no consistent definition or terminology of HAIT emerging to date.DiscussionWe propose a unifying definition combining a human-centered and team-oriented perspective as well as summarize what is still needed in future research regarding HAIT. Thus, this work contributes to support the idea of the Frontiers Research Topic of a theoretical and conceptual basis for human work with AI systems.

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Section: Understandings Of Human-ai Teamingmentioning

confidence: 99%

Section: Current Research Streams and Understandingsmentioning

confidence: 99%

Defining human-AI teaming the human-centered way: a scoping review and network analysis

Berretta,

Tausch,

Ontrup

et al. 2023

Front. Artif. Intell.

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“…Whether it is required by external reality of higher education or the logical development of higher education itself, taking reform is an important guarantee for achieving the sustainable development of higher engineering education in the future [1]. Faced with the strong impact of the new round of industrial revolution, artificial intelligence, big data, and the Internet of Things (IoT), governments around the world have launched and deployed a variety of strategies [2][3][4]. Following Germany's "Industry 4.0", the United State's "Industrial Internet Strategy", France's "New Industrial France strategy ", and Japan's "Japan Revitalization Strategy", China's "Made in China 2025" was introduced [5].…”

Section: Introductionmentioning

confidence: 99%

Exploration and Practice of General Problem in Different Curricula of Mechanical Engineering Major under the Background of New Engineering

Li,

Wang

2024

Proceedings of the 3rd International Conference on Internet Technology and Educational Informatization, ITEI 2023, November 24–

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Under the environment of new engineering construction, innovative talents should have excellent comprehensive qualities, a wide range of knowledge, a multidisciplinary knowledge, and the ability to extract, transfer, and deepen the application of the learned knowledge. As for the curricula of Mechanical Engineering Major of Huzhou University, mass-damping-spring (m-c-k) system in "Theoretical Mechanics" curriculum and resistance-inductance-capacitance (R-L-C) system in "Electrical and Electronics" curriculum are scheduled respectively. However, each of the two systems is composed of one energy storage element and two energy dissipation elements similarly. And two systems are characterized by second-order differential equation. Thereby the problems related with the two systems can be classified into one general problem. Based on abovementioned situation, a reform of exploration and practice of general problem in different curricula is proposed. General problems of different curricula are combined into one special lecture for senior undergraduate or graduate students. And the method of finding general problems, teaching means, requirements for the teacher are constructed. Moreover, an experiment for assessing the effective of the reform is designed and carried out. Two groups of students from two parallel classes of Mechanical Engineering major are chosen. One group learn the m-c-k and R-L-C systems intensively while the other group learn them separately at an interval of one month. The group's average scores of learning the two systems intensively are 11.22 points higher than the group's average scores of learning them separately at an interval of one month. Also, the method reported in this paper can be also expanded to other engineering majors.

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Eco-Conscious Consumption

Thomas,

Kayarkatte

2024

Eco-Innovation and Sustainable Development in Industry 5.0

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This chapter explores the pivotal role of sustainable consumption and the heightened consumer awareness of eco-friendly products in Industry 5.0. Analyzing current trends and future projections probes into the evolving landscape of consumer choices, emphasizing the need for eco-innovation to drive sustainable development. The chapter also examines the challenges and opportunities ahead, offering insights for businesses and policymakers to navigate the dynamic intersection of industry, innovation, and environmental consciousness.

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Technology Aspects of Artificial Intelligence: Industry 5.0 for Organization Decision Making

Cited by 3 publications

References 39 publications

Defining human-AI teaming the human-centered way: a scoping review and network analysis

Defining human-AI teaming the human-centered way: a scoping review and network analysis

Exploration and Practice of General Problem in Different Curricula of Mechanical Engineering Major under the Background of New Engineering

Eco-Conscious Consumption

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