Relevant bibliographies by topics / The concept of Artificial Intelligence (AI)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'The concept of Artificial Intelligence (AI)'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "The concept of Artificial Intelligence (AI)"

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Solomonov, E. V. "Concept and Signs of Artificial Intelligence." Herald of Omsk University. Series: Law, no. 4 (2023): 57–65. http://dx.doi.org/10.24147/1990-5173.2023.20(4).57-65.

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Russian and foreign legislation lack a common understanding of both the essence of artificial intelligence and a unified approach to the legal definition of the concept of AI. Purpose. Analyze existing definitions of artificial intelligence, highlight the characteristics of artificial intelligence as a legal category. Formulate a definition. Methodology. The general principles of scientific knowledge (comprehensiveness, systematicity, objectivity), the general philosophical method (dialectical), general scientific methods of knowledge (comparison, ascent from the abstract to the particular), g
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Sideraki, Angeliki, and Athanasios Drigas. "Artificial Intelligence (AI) in Autism." Technium Social Sciences Journal 26 (December 9, 2021): 262–77. http://dx.doi.org/10.47577/tssj.v26i1.5208.

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This paper examines the issue of artificial intelligence and its association with autism. More specifically, at a first level, reference is made to the concept of artificial intelligence, but also to concepts that are directly related and are an extension of it. In addition, the various areas in which the use of artificial intelligence is identified are presented, while the concept of autism and its connection to technology are also analyzed. As research progresses on artificial intelligence and the diagnosis of autism. More specifically, the role of artificial intelligence is now particularly
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Marcos, Alfredo. "Information and artificial intelligence." Análisis Jurídico - Político 2, no. 3 (2020): 21–37. http://dx.doi.org/10.22490/26655489.4103.

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There is a deep discussion about the so-called artificial intelligence (AI) –which is currently fuelled by bigdata- and about its possible effects on human life. I question in this article if we could get some advantage thinking about AI by clarifying the concept of information. I will argue, in effect, that a well-developed concept of information can provide some light on what we call AI. To argue in favour of this thesis, I will first explain my approach to the notion of information. Then, I will raise in brief some deliberations about AI. We can better understand what data is by taking into
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Peter Smith, Peter Smith, and Laura Smith Peter Smith. "Artificial Intelligence (AI) and Ethics." International Journal of Computer Auditing 6, no. 1 (2024): 069–76. https://doi.org/10.53106/256299802024120601006.

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<p>AI is everywhere around us and affecting our lives in many ways, some of which we may not even be aware of. This paper discusses the advantages and disadvantages of AI and its impact upon society. The authors, Peter, and Laura are both disabled which means that, inevitably, they view AI and the ethical issues which it brings, through the lens of disabled people. However, they try as much as they can to discuss the ethical issues around AI in an unbiased manner. This commentary starts by introducing the concept of AI, the authors and their disabilities, the meanings of ethics and goes
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Jarrahi, Mohammad Hossein, Christoph Lutz, and Gemma Newlands. "Artificial intelligence, human intelligence and hybrid intelligence based on mutual augmentation." Big Data & Society 9, no. 2 (2022): 205395172211428. http://dx.doi.org/10.1177/20539517221142824.

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There is little consensus on what artificial intelligence (AI) systems may or may not embrace. Although this may point to multiplicity of interpretations and backgrounds, a lack of conceptual clarity could thwart the development of common ground around the concept among researchers, practitioners and users of AI and pave the way for misinterpretation and abuse of the concept. This article argues that one of the effective ways to delineate the concept of AI is to compare and contrast it with human intelligence. In doing so, the article broaches the unique capabilities of humans and AI in relati
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Günay, Mustafa. "Artificial Intelligence and Originality in Design." ART/icle: Sanat ve Tasarım Dergisi 4, no. 3 (2025): 449–69. https://doi.org/10.56590/stdarticle.1548924.

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The Purpose of the Study: This paper addresses how artificial intelligence (AI) plays a role in the world of design and how it affects the concept of originality. The paper examines the use of AI in areas such as graphic design, logo design, painting, original designs and web design, and discusses the innovations that this technology brings to design processes. The paper also considers the positive and negative effects of AI on designers. Positive effects include the acceleration of design processes and the access to a wider creative spectrum. On the other hand, the impact of AI on originality
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Plotnikov, Sergei A., Mikhail Lipkovich, Danila M. Semenov, and Alexander L. Fradkov. "Artificial intelligence based neurofeedback." Cybernetics and Physics, Volume 8, 2019, Number 4 (December 30, 2019): 287–91. http://dx.doi.org/10.35470/2226-4116-2019-8-4-287-291.

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A new approach to the design of neurofeedback systems based on using Artificial Intelligence (AI) tools is proposed. The concept of control models of biological neural networks, and the set-up including equipment and software tools developed in IPME RAS in order to implement the proposed concept is described. as well as the AI methods and programs proposed for use.
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Germanov, Nikolai S. "The concept of responsible artificial intelligence as the future of artificial intelligence in medicine." Digital Diagnostics 4, no. 1S (2023): 27–29. http://dx.doi.org/10.17816/dd430334.

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Active deployment of artificial intelligence (AI) systems in medicine creates many challenges. Recently, the concept of responsible artificial intelligence (RAI) was widely discussed, which is aimed at solving the inevitable ethical, legal, and social problems. The scientific literature was analyzed and the possibility of applying the RAI concept to overcome the existing AI problems in medicine was considered. Studies of possible AI applications in medicine showed that current algorithms are unable to meet the basic enduring needs of society, particularly, fairness, transparency, and reliabili
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Kim, Sangyeol, and Hyuntai Kim. "Artificial intelligence(AI) Composition Technology Trends & Creation Platform." Korean Society of Culture and Convergence 44, no. 6 (2022): 207–28. http://dx.doi.org/10.33645/cnc.2022.6.44.6.207.

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this study, the technical concept of composition using artificial intelligence, which is attracting attention as a major field of the 4th industrial revolution, and the development and service cases of major platforms are studied. The purpose of this study was to find out the plan and development plan. The concept of artificial intelligence was explained, and the concepts of LSTM and RNN, which are representative data generation models used in artificial intelligence composition, and GAN, which is an adversarial generation model, were studied, and the data generation process and algorithm of a
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Shah, Yamini D., Shailvi M. Soni, and Manish P. Patel. "Artificial intelligence in healthcare." Indian Journal of Pharmacy and Pharmacology 8, no. 2 (2021): 102–15. http://dx.doi.org/10.18231/j.ijpp.2021.018.

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Artificial Intelligence (AI) is described as a field of science and engineering that is concerned with the artificial appreciation of what is generally referred to as prudent behavior and the formation of fascinations that demonstrate such conduct. AI is an expansive concept that encloses a series of advances (a considerable lot of which have been being worked on for quite a few years) that are expected to use human-like insight to handle the problems. Right now in combination with enhanced AI developments like extreme or significantly more engaged, we are experiencing a renewed enthusiasm for
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Dissertations / Theses on the topic "The concept of Artificial Intelligence (AI)"

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Kanumury, Rajesh. "Integrating business and engineering processes in manufacturing environment using AI concepts." Ohio : Ohio University, 1995. http://www.ohiolink.edu/etd/view.cgi?ohiou1179423333.

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Karlsson, Marcus. "Developing services based on Artificial Intelligence." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-73090.

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This thesis explores the development process of services based on artificial intelligence (AI) technology within an industrial setting. There has been a renewed interest in the technology and leading technology companies as well as many start-ups has integrated it into their market offerings. The technology´s general application potential for enhancing products and services along with the task automation possibility for improved operational excellence makes it a valuable asset for companies. However, the implementation rate of AI services is still low for many industrial actors. The research i
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Kim, Jee Won. "How speciesism affects artificial intelligence (AI) adoption intent." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/228673/1/Jee%20Won_Kim_Thesis.pdf.

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As there have been concerns about the excessive advancement of artificial intelligence (AI) surpassing humans, exploring reactions to AI as challenging human superiority is meaningful. By examining how the hierarchical and discriminative views on animals (speciesism) affects the views on non-living AI, this thesis has significant and novel contributions to AI adoption literature and AI product marketing.
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Fatima, Samar. "Mapping artificial intelligence affordances for the public sector." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/235926/1/Samar%2BFatime%2BThesis.pdf.

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This thesis explores the affordances of artificial intelligence (AI) for the public sector. The thesis consists of three studies that answer what, why and how questions of AI affordance actualization in public sector using a combination of primary and secondary data sources. In this thesis, the affordance theory lens is used to explore AI affordance perception and actualization for the public sector through three related studies. The perception of AI affordance is investigated in the first two studies. The third study designed and evaluated artefact for public agencies to actualize AI affordan
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Malmborn, Albin, and Linus Sjöberg. "Implementing Artificial intelligence." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20942.

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Den här uppsatsen har som syfte att undersöka huruvida det är möjligt att ta fram riktlinjer för vad privata verksamheter behöver ta i beaktande inför en planerad implementering av artificiell intelligens. Studien kommer belysa faktorer som hjälper företag att förstå vad som krävs inför en sådan omställning, men även de hinder som måste övervinnas för att lyckas. Studiens datainsamling har genomförts med två metoder, först en litteraturstudie sedan kvalitativa, semistrukturerade forskningsintervjuer. Dessa har sedan analyserats med vars en analysmetod som kompletterar varandra och därefter tol
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Edlund, Mattias. "Artificial Intelligence in Games : Faking Human Behavior." Thesis, Uppsala universitet, Institutionen för speldesign, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-258222.

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This paper examines the possibilities of faking human behavior with artificial intelligence in computer games, by using efficient methods that save valuable development time and also creates a more rich experience for the players of a game. The specific implementation of artificial intelligence created and discussed is a neural network controlling a finite-state machine. The objective was to mimic human behavior rather than simulating true intelligence. A 2D shooter game is developed and used for experiments performed with human and artificial intelligence controlled players. The game sessions
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Khan, Laiq. "Hybrid AI paradigms applied to power system damping controls." Thesis, University of Strathclyde, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273412.

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Svedberg, Peter O. S. "Steps towards an empirically responsible AI : a methodological and theoretical framework." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-246.

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<p>Initially we pursue a minimal model of a cognitive system. This in turn form the basis for the development of amethodological and theoretical framework. Two methodological requirements of the model are that explanation be from the perspective of the phenomena, and that we have structural determination. The minimal model is derived from the explanatory side of a biologically based cognitive science. Fransisco Varela is our principal source for this part. The model defines the relationship between a formally defined autonomous system and an environment, in such a way as to generate the world
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Rafiq, M. Y. "Artificial intelligence techniques for the structural design of buildings." Thesis, University of Strathclyde, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382446.

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Casten, Carlberg Carl Johan, and Elsa Jerhamre. "Artificial Intelligence in Agriculture : Opportunities and Challenges." Thesis, Uppsala universitet, Avdelningen för datorteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443576.

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Artificial Intelligence (AI) is increasingly used in different parts of society for providing decision support in various activities. The agricultural sector is anticipated to benefit from an increased usage of AI and smart devices, a concept called smart farming technologies. Since the agricultural sector faces several simultaneous challenges, such as shrinking marginals, complicated pan-European regulations, and demands to mitigate the environmental footprint, there are great expectations that smart farming will benefit both individual farmers and industry stakeholders. However, most previou
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Books on the topic "The concept of Artificial Intelligence (AI)"

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Grebenyuk, Elena, Darya Danielyan, Sarkis Danielyan, and Sergey Kramarov. Artificial Intelligence in Education: Opportunities, Methods, and Recommendations for Educators. Publishing Center RIOR, 2024. http://dx.doi.org/10.29039/02147-7.

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The training and practical manual covers the main concepts and methods of utilizing artificial intelligence (AI) technologies in educational activities. The primary goal of this work is to provide educators in educational institutions with knowledge about the possibilities of applying AI in teaching, as well as practical recommendations for integrating these technologies into classroom activities. The publication is designed to develop educators' competencies in the field of artificial intelligence to enhance the quality of teaching and student performance. The book describes the use of AI to
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Alareeni, Bahaaeddin A. M., and Islam Elgedawy, eds. Artificial Intelligence (AI) and Finance. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39158-3.

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Winston, Patrick Henry. Artificial intelligence. 3rd ed. Addison-Wesley, 1993.

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Long, Guodong, Xinghuo Yu, and Sen Wang, eds. AI 2021: Advances in Artificial Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97546-3.

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Nicholson, Ann, and Xiaodong Li, eds. AI 2009: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10439-8.

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Peng, Wei, Damminda Alahakoon, and Xiaodong Li, eds. AI 2017: Advances in Artificial Intelligence. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63004-5.

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Orgun, Mehmet A., and John Thornton, eds. AI 2007: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-76928-6.

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Wobcke, Wayne, and Mengjie Zhang, eds. AI 2008: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89378-3.

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Thielscher, Michael, and Dongmo Zhang, eds. AI 2012: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35101-3.

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McKay, Bob, and John Slaney, eds. AI 2002: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36187-1.

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Book chapters on the topic "The concept of Artificial Intelligence (AI)"

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Myklebust, Thor, Tor Stålhane, and Dorthea Mathilde Kristin Vatn. "Artificial Intelligence (AI)." In SpringerBriefs in Computer Science. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-80504-2_6.

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Abstract This chapter first provides a section on artificial intelligence (AI) in high risk systems, giving an overview over the current progress in standards relating to this topic. Next, a section addresses explainable AI (XAI) both as a technical concept and as a concept that has evident human and organizational sides to it. Lastly, a section on the concept of safety of intended functionality (SOTIF) is provided as it addresses safety in AI-driven systems, especially autonomous vehicles. This approach helps mitigate risks from functional insufficiencies in AI algorithms, making it vital for
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Stahl, Bernd Carsten. "Perspectives on Artificial Intelligence." In SpringerBriefs in Research and Innovation Governance. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69978-9_2.

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AbstractA discussion of the ethics of artificial intelligence hinges on the definition of the term. In this chapter I propose three interrelated but distinct concepts of AI, which raise different types of ethical issues. The first concept of AI is that of machine learning, which is often seen as an example of “narrow” AI. The second concept is that of artificial general intelligence standing for the attempt to replicate human capabilities. Finally, I suggest that the term AI is often used to denote converging socio-technical systems. Each of these three concepts of AI has different properties
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Raglin, Adrienne. "Leveraging Generative AI Concepts with Uncertainty of Information Concept." In Artificial Intelligence in HCI. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60611-3_17.

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O’Brien, Bettina, and V. Uma. "Computer Vision Concepts and Applications." In Artificial Intelligence (AI). CRC Press, 2021. http://dx.doi.org/10.1201/9781003005629-6.

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Chala, Sisay Adugna, and Alexander Graß. "Human-AI Interaction for Semantic Knowledge Enrichment of AI Model Output." In Artificial Intelligence in Manufacturing. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46452-2_3.

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AbstractModern manufacturing requires developing a framework of AI solutions that capture and process data from various sources including from human-AI collaboration. This chapter tries to describe the concept of domain knowledge fusion in human-AI collaboration for manufacturing. Human interaction with AI is enabled in such a way that the domain expert not only inspects the output of the AI model but also injects engineered knowledge in order to retrain AI models for iterative improvement. Domain knowledge fusion is a technique that involves combining knowledge from multiple domains or source
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McCarthy, John. "Concepts of Logical AI." In Logic-Based Artificial Intelligence. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-1567-8_2.

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Redozubov, Alexey, and Dmitry Klepikov. "The Meaning of Things as a Concept in a Strong AI Architecture." In Artificial General Intelligence. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52152-3_30.

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Liu, Anjin, Guangquan Zhang, Jie Lu, Ning Lu, and Chin-Teng Lin. "An Online Competence-Based Concept Drift Detection Algorithm." In AI 2016: Advances in Artificial Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50127-7_36.

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Stirling, Moana, Yun Sing Koh, Philippe Fournier-Viger, and Sri Devi Ravana. "Concept Drift Detector Selection for Hoeffding Adaptive Trees." In AI 2018: Advances in Artificial Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03991-2_65.

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Singh, Pramod K. "IC 2: An Interval Based Characteristic Concept Learner." In AI 2005: Advances in Artificial Intelligence. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11589990_118.

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Conference papers on the topic "The concept of Artificial Intelligence (AI)"

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Voronkova, Valentyna, Vitalina Nikitenko, Roman Oleksenko, T�t�ana Khrystova, Vladyslav Pyurko, and Halina Harbar. "USE OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES TO ACHIEVE THE GOALS OF ENVIRONMENTALLY SUSTAINABLE DEVELOPMENT." In SGEM International Multidisciplinary Scientific GeoConference. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024v/6.2/s26.50.

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This article aims to develop a concept for utilizing artificial intelligence (AI) technologies to achieve environmentally sustainable development goals, leveraging a suite of technologies for environmental protection and natural resource management in the digital age. The study employs risk-oriented approaches, system analysis, and modeling to explore the application of AI in attaining environmental sustainability objectives. Research Results: 1.The study presents an analysis of AI technologies applied to achieving environmentally sustainable development goals. 2. It formulates a concept for t
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Summerville, Amy, Louis Martí, Ion Juvina, B. Locke Welborn, Cara Widmer, and Alice Leung. "A Proof-of-Concept Validation of Alignment in Decision-Making Attributes for Trustworthy AI." In 2025 IEEE Conference on Artificial Intelligence (CAI). IEEE, 2025. https://doi.org/10.1109/cai64502.2025.00204.

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Suthaharan, Shan. "Detective AI: distinguishing AI generated and real images by leveraging the concept of cross-correlation of connected image components of bit-planes." In Emerging Topics in Artificial Intelligence (ETAI) 2024, edited by Giovanni Volpe, Joana B. Pereira, Daniel Brunner, and Aydogan Ozcan. SPIE, 2024. http://dx.doi.org/10.1117/12.3027551.

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Corina, Rotar, Raul-Octav Munteanu-Bardan, and Ildiko Tulbure. "ARTIFICIAL INTELLIGENCE USAGE POSSIBILITIES FOR ENVIRONMENTAL MONITORING." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024v/4.2/s07.54.

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Designing the multitude of technological applications in various activity fields of human society has without question had the direct result of increasing humanity�s quality of life. Nevertheless, besides the positive intended impact of technological advance several negative effects have emerged, especially regarding environmental pollution on different levels. In this regard a lot of debates have primarily started on a scientific level with the goal of finding the best strategies for trying to solve complex created situations and to succeed in keeping good environmental quality. After underst
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Abdelsalam, Reem Ramadan, Yomna Refaat Abdelalim, Nayra Ibrahim Elgazzaz, et al. "Generative AI for Healthcare: Concepts and Applications." In 2024 International Conference on Smart-Digital-Green Technologies and Artificial Intelligence Sciences (CSDGAIS). IEEE, 2024. https://doi.org/10.1109/csdgais64098.2024.11064841.

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Schweidtmann, Artur M. "Mining Chemical Process Information from Literature for Generative Process Design: A Perspective." In Foundations of Computer-Aided Process Design. PSE Press, 2024. http://dx.doi.org/10.69997/sct.184704.

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Artificial intelligence (AI) and particularly generative AI led to recent breakthroughs, e.g., in generating text and images. There is also a potential of these technologies in chemical engineering, but the lack of structured big domain-relevant data hinders advancements. I envision an open Chemical Engineering Knowledge Graph (ChemEngKG) that provides big open and linked chemical process information. In this article, I present the concept of �flowsheet mining� as the first step towards the ChemEngKG. Flowsheet mining extracts process information from flowsheets and process descriptions found
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Winecoff, Amy A., and Elizabeth Anne Watkins. "Artificial Concepts of Artificial Intelligence." In AIES '22: AAAI/ACM Conference on AI, Ethics, and Society. ACM, 2022. http://dx.doi.org/10.1145/3514094.3534138.

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Mahiout, Mohamed Said, Faisal Naif Al Enezi, Gagok Imam Santoso, and Mohammed Satti Ali Elhaj. "Artificial-Intelligence-Based Well Placement Look Ahead Concept." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211752-ms.

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Abstract Artificial intelligence (AI) brings many benefits to the oil and gas industry and in particular the automation of the geosteering process with structural prediction ahead of the bit to optimize horizontal well placement and reduce the operational challenges. AI techniques are based on data analysis that learn from data, identify patterns and make predictions without the need of direct human intervention. Recent ultra-deep azimuthal resistivity (UDAR) logging-while-drilling (LWD) tools have reached a significant depth of investigation capabilities to provide real time information that
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KALJUN, Jasmin, Andrej CUPAR, and Klavdija KOPŠE KALJUN. "FROM CONCEPT TO CREATION: LEVERAGING ARTIFICIAL INTELLIGENCE IN MECHANICAL DESIGN AND IDEATION." In 11th International Scientific Conference IRMES 2025 Research and Development of Mechanical Elements and Systems. University of Niš, Faculty of Mechanical Engineering, 2025. https://doi.org/10.46793/irmes25.pla2k.

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This paper explores the integration of artificial intelligence (AI) into mechanical design workflows, with a focus on improving ideation, creativity and iterative development. Traditional design processes, limited by sequential workflows, time-consuming iterations and reliance on intuition, are increasingly unable to cope with the complexity and pace of modern product development. To overcome these limitations, an AI-driven design framework is proposed that consists of four interconnected components: generative design algorithms, surrogate modelling and performance prediction, data-driven deci
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Eddy, Douglas, Sundar Krishnamurty, Ian Grosse, Michael White, and Damon Blanchette. "A Defect Prevention Concept Using Artificial Intelligence." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22112.

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Abstract Defect prevention is particularly critical in operations such as aircraft assembly or service. Failure Modes and Effects Analysis (FMEA) procedures have been deployed manually for many years. However, the manual procedures fail to utilize capability to build intelligence into inspection processes that can facilitate elimination of human error. In this work, we introduce an artificial intelligence (AI)-based concept that can iteratively learn to assure zero defects from a given inspection process. This work introduces a schema that can serve as a knowledge management framework in a rel
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Reports on the topic "The concept of Artificial Intelligence (AI)"

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Blanchard, Alexander, and Laura Bruun. Bias in Military Artificial Intelligence. Stockholm International Peace Research Institute, 2024. https://doi.org/10.55163/cjft9557.

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To support states involved in the policy debate on military artificial intelligence (AI), this background paper provides a deeper examination of the issue of bias in military AI. Three insights arise. First, policymakers could usefully develop an account of bias in military AI that captures shared concern around unfairness. If so, ‘bias in military AI’ might be taken to refer to the systemically skewed performance of a military AI system that leads to unjustifiably different behaviours—which may perpetuate or exacerbate harmful or discriminatory outcomes—depending on such social characteristic
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Moskicheva, Elena. Integration of Artificial Intelligence in Industrial Design: From Generative Models to Intelligent Automation. Intellectual Archive, 2025. https://doi.org/10.32370/iaj.3263.

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This article examines the role of artificial intelligence in transforming industrial design processes. Special attention is given to generative design, the use of AI in CAD environments, and the concept of digital twins. Practical examples of intelligent systems applied in product development are provided, demonstrating increased efficiency, reduced timeframes, and improved quality of design solutions. The paper also discusses future prospects for AI integration and the associated ethical challenges.
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Su, Fei, Vladislav Chernavskikh, and Wilfred Wan. Advancing Governance at the Nexus of Artificial Intelligence and Nuclear Weapons. Stockholm International Peace Research Institute, 2025. https://doi.org/10.55163/onlb7070.

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The rapid advancement of military artificial intelligence (AI), especially its potential integration into nuclear systems, presents significant risks to strategic stability and established deterrence practices. Despite these concerns, no dedicated governance framework currently exists to address the specific challenges of the AI–nuclear nexus. Existing initiatives have primarily focused on ensuring human control over nuclear decision-making. There are a number of state-led initiatives on the governance of military AI more broadly. They can be adapted to address the use of AI in nuclear weapons
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Arnold, Zachary, Rebecca Gelles, and Ilya Rahkovsky. Identifying AI-Related Companies: A Conceptual Outline and Proof of Concept. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200018.

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Artificial intelligence is of increasing interest to the private sector, but what exactly constitutes an “AI company?” This data brief offers a flexible, data-driven framework for identifying the companies most relevant in this field at the moment, providing policymakers and researchers with a tool for mapping technology transfer risks and gauging the overall health of America’s AI sector.
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Bennet, Karen, Gopi Krishnan Rajbahadur, Arthit Suriyawongkul, and Kate Stewart. Implementing AI Bill of Materials (AI BOM) with SPDX 3.0: A Comprehensive Guide to Creating AI and Dataset Bill of Materials. The Linux Foundation, 2024. https://doi.org/10.70828/rned4427.

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A Software Bill of Materials (SBOM) is becoming an increasingly important tool in regulatory and technical spaces to introduce more transparency and security into a project's software supply chain. Artificial intelligence (AI) projects face unique challenges beyond the security of their software, and thus require a more expansive approach to a bill of materials. In this report, we introduce the concept of an AI-BOM, expanding on the SBOM to include the documentation of algorithms, data collection methods, frameworks and libraries, licensing information, and standard compliance.
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Arnold, Zachary, Joanne Boisson, Lorenzo Bongiovanni, Daniel Chou, Carrie Peelman, and Ilya Rahkovsky. Using Machine Learning to Fill Gaps in Chinese AI Market Data. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200064.

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In this proof-of-concept project, CSET and Amplyfi Ltd. used machine learning models and Chinese-language web data to identify Chinese companies active in artificial intelligence. Most of these companies were not labeled or described as AI-related in two high-quality commercial datasets. The authors' findings show that using structured data alone—even from the best providers—will yield an incomplete picture of the Chinese AI landscape.
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Gehlhaus, Diana, and Ilya Rahkovsky. U.S. AI Workforce: Labor Market Dynamics. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200086.

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A lack of good data on the U.S. artificial intelligence workforce limits the potential effectiveness of policies meant to increase and cultivate this cadre of talent. In this issue brief, the authors bridge that information gap with new analysis on the state of the U.S. AI workforce, along with insight into the ongoing concern over AI talent shortages. Their findings suggest some segments of the AI workforce are more likely than others to be experiencing a supply-demand gap.
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Acharya, Ashwin, Max Langenkamp, and James Dunham. Trends in AI Research for the Visual Surveillance of Populations. Center for Security and Emerging Technology, 2022. http://dx.doi.org/10.51593/20200097.

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Progress in artificial intelligence has led to growing concern about the capabilities of AI-powered surveillance systems. This data brief uses bibliometric analysis to chart recent trends in visual surveillance research — what share of overall computer vision research it comprises, which countries are leading the way, and how things have varied over time.
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Doo, Johnny. Beyond Aviation: Embedded Gaming, Artificial Intelligence, Training, and Recruitment for the Advanced Air Mobility Industry. SAE International, 2024. https://doi.org/10.4271/epr2024028.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Recent advancements in electric vertical take-off and landing (eVTOL) aircraft and the broader advanced air mobility (AAM) movement have generated significant interest within and beyond the traditional aviation industry. Many new applications have been identified and are under development, with considerable potential for market growth and exciting potential. However, talent resources are the most critical parameters to make or break the AAM vision, and significantly more talent is needed than the traditional aviation ind
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Stankovic, Mirjana, and Nikola Neftenov. Cross Pollination and Digitalization of Public Sector Data: Opportunities and Challenges. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004355.

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This report aims to aid governments in Latin America and the Caribbean in embracing the opportunities public sector data utilization and artificial intelligence (AI) deployment can provide in achieving a circular economy model and the UNs Sustainable Development Goals (SDGs). For such purpose, the report provides a novel concept of sharing data between key players that we have named data cross-pollination. Drawing on this concept, it considers four SDGs, i.e., energy, sustainable food systems, reducing pollution, and smart cities. Building on case studies and initiatives, the report highlights
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