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Layne, Armand. "Artificial intelligence (ai)." Intelligent Systems in Accounting, Finance and Management 13, no. 3 (July 2005): 179–81. http://dx.doi.org/10.1002/isaf.267.
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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 (December 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 on to discuss the ethical issues which Peter and Laura see in their day-to-day lives. They then drawfromthe literature on AI and ethics to broaden the discussion to take account of current published work by others on the topic. Finally, they return to their own perspectives and conclude that AI offers many advantages to society and our future. However, they also warn of the dangers and ethical challenges which AI raises. It is hoped that this commentary frames a contribution to the field of AI and ethics which readers will find interesting, useful and, perhaps, challenging.</p> <p> </p>
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Kishorekumar, Mr A., Mr E. Ezhilarasan, and Mr R. Parthiban. "Intelligent Drone based Personal Assistant using Artificial Intelligence AI." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 1618–21. http://dx.doi.org/10.31142/ijtsrd11482.
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Huang, Ming-Hui, and Roland T. Rust. "Artificial Intelligence in Service." Journal of Service Research 21, no. 2 (February 5, 2018): 155–72. http://dx.doi.org/10.1177/1094670517752459.
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Artificial intelligence (AI) is increasingly reshaping service by performing various tasks, constituting a major source of innovation, yet threatening human jobs. We develop a theory of AI job replacement to address this double-edged impact. The theory specifies four intelligences required for service tasks—mechanical, analytical, intuitive, and empathetic—and lays out the way firms should decide between humans and machines for accomplishing those tasks. AI is developing in a predictable order, with mechanical mostly preceding analytical, analytical mostly preceding intuitive, and intuitive mostly preceding empathetic intelligence. The theory asserts that AI job replacement occurs fundamentally at the task level, rather than the job level, and for “lower” (easier for AI) intelligence tasks first. AI first replaces some of a service job’s tasks, a transition stage seen as augmentation, and then progresses to replace human labor entirely when it has the ability to take over all of a job’s tasks. The progression of AI task replacement from lower to higher intelligences results in predictable shifts over time in the relative importance of the intelligences for service employees. An important implication from our theory is that analytical skills will become less important, as AI takes over more analytical tasks, giving the “softer” intuitive and empathetic skills even more importance for service employees. Eventually, AI will be capable of performing even the intuitive and empathetic tasks, which enables innovative ways of human–machine integration for providing service but also results in a fundamental threat for human employment.
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Tarekar, Sagar. "Artificial Intelligence." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (March 31, 2024): 2533–35. http://dx.doi.org/10.22214/ijraset.2024.59386.
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Abstract: We have chosen this topic to spotlight on one of the most technological trend these days known as AI(Artificial Intelligent). Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision. AI brings up images of high- functioning, human-like robots taking over the world, AI isn’t intended to replace humans. Therefore we will discuss some of the most important aspects related to AI in which it will help in a better understanding of Artificial Intelligent and both its advantages and disadvantages to be able to protect ourselves from the upcoming technological trend.
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Singhal, Ankur, and Komal Gupta. "Artificial Intelligence: Transforming Ayurveda." Indian Journal of Ancient Medicine and Yoga 15, no. 4 (December 27, 2022): 151–58. http://dx.doi.org/10.21088/ijamy.0974.6986.15422.3.
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As we know technology is at its boom in 21st century and it has touched our every aspect of life including The Ayurveda: ‘The science of life’. So for upgrading this ancient and 5000 yrs old system of medicine there must be full fledged inclusion of technology that allows computers and machines to function in an intelligent manner. This change with the help of technology is called as Artificial intelligence. It is the simulation of human intelligence processes by machines, especially computer systems. By adopting and adapting this digital world in the field of Ayurveda we can create a revolutionary change. The development of artificial intelligence (AI) in the medical field has been growing rapidly. The majority of the studies utilized AI models to predict certain patterns and find reliable computerized models to assist physicians. The objective of this article is to categorize and seek the current and further usage of AI in Ayurveda. A systematic scoping review has been conducted. The entire database, articles, and news have been used to find studies regarding AI and Ayurveda. A broad-range search strategy was applied to locate all relevant studies. Although the results from this review have shown the potential use of AI models in Ayurveda, future research ought to focus on verifying and validating the models by performing a large-scale clinical trial to better promote AI in Ayurveda in the era of digital health.
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Daisy, Anjali. "Artificial Intelligence." International Journal of Social Ecology and Sustainable Development 13, no. 1 (January 2022): 1–9. http://dx.doi.org/10.4018/ijsesd.292075.
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Artificial Intelligence (AI) is gradually changing the practice of surgery with the advanced technological development of imaging, navigation, and robotic intervention. In this article, the recent successful and influential applications of AI in surgery are reviewed from pre-operative planning and intra-operative guidance to the integration of surgical robots. It ends with summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery. Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures. The technology is also known as computer-aided surgery and robot-assisted surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments in the field of Neuro Surgery.
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Bagnato, Vincenzo Paolo. "Artificial Intelligence for Design The Artificial Intelligence of Objects." Venturing into the Age of AI: Insights and Perspectives, no. 27 (October 1, 2023): 30–35. http://dx.doi.org/10.37199/f40002705.
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Artificial Intelligence (AI) is increasingly permeating various domains, revolutionizing traditional processes and opening new avenues for innovation. In the realm of design, AI holds immense promise, offering capabilities to augment human creativity, streamline workflows, and deliver personalized user experiences. This paper explores the intersection of AI and design, highlighting its transformative potential and key implications. Firstly, for instance, AI-powered design tools automate repetitive tasks, freeing up designers' time for more creative endeavors, while generative design algorithms can generate myriad design options based on specified constraints, enabling designers to explore more efficiently brand-new solutions. Additionally, AI-driven predictive analytics provide insights into user preferences and market trends, facilitating informed design decisions and enhancing product relevance; moreover, AI enables the creation of personalized user experiences by analyzing vast datasets to understand individual preferences and behaviors: this personalization extends across various design domains, from user interfaces and digital products to physical spaces and services. Ethical considerations are paramount in the integration of AI into design processes: designers must address issues of transparency, fairness, and bias to ensure that AI-driven solutions uphold ethical standards and respect user privacy; furthermore, human-AI collaboration emerges as a fundamental paradigm, where AI augments human creativity and decision-making rather than replacing it entirely. Challenges such as technical complexity, data privacy concerns, and the need for upskilling within the design workforce accompany the integration of AI in design; thus, addressing these challenges requires interdisciplinary collaboration and a holistic approach encompassing technological, ethical, and socio-economic dimensions. In this framework, this paper sets the stage for further exploration of AI's transformative impact on design and the ethical considerations guiding its integration into practice.
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Kaur, Ms Parminder. "Artificial Intelligence." International Journal for Research in Applied Science and Engineering Technology 11, no. 10 (October 31, 2023): 597–99. http://dx.doi.org/10.22214/ijraset.2023.56025.
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Abstract: A multidisciplinary discipline called artificial intelligence (A.I.) aims to automate jobs that currently need human intelligence. Artificial intelligence (AI), while not being well known, is a technology that is revolutionising all facets of existence. In order to rethink how we mix data, analyse it, and make decisions, this article attempts to inform laypeople about AI and urge them to use it as a tool in various fields. In this post, we briefly discussed artificial intelligence (AI), its principles, and potential applications.
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Al Dajeh, Bakhit Moh’d. "Artificial Intelligence Governance." Journal of Ecohumanism 3, no. 4 (July 18, 2024): 300–313. http://dx.doi.org/10.62754/joe.v3i4.3515.
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Research on AI governance is important towards potentially useful and constraining affordable misuse, reduce new risks and economic trends that threaten to disrupt public political and economic trends, and drive off target as interest in advanced AI systems and the norms, focal points, and use of new AI research are potentially transformative and governance institutions aim to prevent. Potential public benefits from policy community re-using AI research are enormous, including reduced economic instability. A fundamental challenge in AI governance is a cognitive framing challenge: governing AI research requires understanding new kinds of safety risks, performance goals, and intended applications that advanced AI systems will make possible. Specifically, the letter focuses on how AI research could mitigate issues such as the possibility of AI capabilities getting concentrated within a small and hard-to-regulate group of actors, and ultimately recommends the prioritization of open research and collaboration, with concern for long-term social and economic looming to the forefront of coalitions if AI becomes an increasingly important aspect of the future economy and society.
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Kumar, Sarvesh, Upasana Gupta, Arvind Kumar Singh, and Avadh Kishore Singh. "Artificial Intelligence." Journal of Computers, Mechanical and Management 2, no. 3 (August 31, 2023): 31–42. http://dx.doi.org/10.57159/gadl.jcmm.2.3.23064.
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As we navigate the digital era of the 21st century, cyber security has grown into a pressing societal issue that requires innovative, cutting-edge solutions. In response to this pressing need, Artificial Intelligence (AI) has emerged as a revolutionary instrument, causing a paradigm shift in cyber security. AI's prowess resides in its capacity to process and analyze immense quantities of heterogeneous cyber security data, thereby facilitating the efficient completion of crucial tasks. These duties, which include threat detection, asset prioritization, and vulnerability management, are performed with a level of speed and accuracy that far exceeds human capabilities, thereby transforming our approach to cyber security. This document provides a comprehensive dissection of AI's profound impact on cyber security, as well as an in-depth analysis of how AI tools not only augment, but in many cases transcend human-mediated processes. By delving into the complexities of AI implementation within the realm of cyber security, we demonstrate the potential for AI to effectively anticipate, identify, and preempt cyber threats, empowering organizations to take a proactive stance towards digital safety. Despite these advancements, it is essential to consider the inherent limitations of AI. We emphasize the need for sustained human oversight and intervention to ensure that cyber security measures are proportionate and effective. Importantly, we address potential ethical concerns and emphasize the significance of robust governance structures for the responsible and transparent use of artificial intelligence in cyber security. This paper clarifies the transformative role of AI in reshaping cyber security strategies, thereby contributing to a safer, more secure digital future. In doing so, it sets the groundwork for further exploration and discussion on the use of AI in cyber security, a discussion that is becoming increasingly important as we continue to move deeper into the digital age.
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A, Zapata Flórez. "Cognitive Priority over Ethical Priority in Artificial Intelligence: The Primordial Philosophical Analysis in Artificial Intelligence." Philosophy International Journal 5, no. 4 (October 10, 2022): 1–10. http://dx.doi.org/10.23880/phij-16000269.
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The general idea that we have of artificial intelligence (AI) consists of the belief that machines will be able to develop conscious thoughts such as those possessed by human beings, and, as computing advances, such thinking will also advance until intelligence to surpass the human being, with which the advancement of AI represents ethical risks in the future. In reality, such a belief hides a cognitive assumption, which assumes that computational engineering explains human intelligence through the mind-computer metaphor. According to this assumption, technology explains cognition, and philosophy, through ethics, reflects on the impact of said technology. However, in this article, I contradict such an assumption and defend that the philosophy in AI is not reduced to the ethics that is present after the use and impact of AI in the world. I intend to expose that a good ethics of AI is the one that reflects on the appropriate risks facing AI, and for this, philosophy, beforehand, must make a cognitive analysis about the possibilities that computing has to create intelligent machines, namely, whether or not the mindcomputer metaphor makes sense. My thesis consists in defending that the philosophical analysis about AI must be carried out both on a cognitive level and on an ethical level, but that the philosophical priority in the cognitive analysis over the ethical priority, since the ethical risks of AI depend of the possibilities of technology, and only the cognitive approach can account for this.
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Siau, Keng, and Weiyu Wang. "Artificial Intelligence (AI) Ethics." Journal of Database Management 31, no. 2 (April 2020): 74–87. http://dx.doi.org/10.4018/jdm.2020040105.
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Artificial intelligence (AI)-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data biases, data security, data privacy, and ethical problems of AI-based technology pose significant risks for users, developers, humanity, and societies. As AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. Even though the concept of “machine ethics” was proposed around 2006, AI ethics is still in the infancy stage. AI ethics is the field related to the study of ethical issues in AI. To address AI ethics, one needs to consider the ethics of AI and how to build ethical AI. Ethics of AI studies the ethical principles, rules, guidelines, policies, and regulations that are related to AI. Ethical AI is an AI that performs and behaves ethically. One must recognize and understand the potential ethical and moral issues that may be caused by AI to formulate the necessary ethical principles, rules, guidelines, policies, and regulations for AI (i.e., Ethics of AI). With the appropriate ethics of AI, one can then build AI that exhibits ethical behavior (i.e., Ethical AI). This paper will discuss AI ethics by looking at the ethics of AI and ethical AI. What are the perceived ethical and moral issues with AI? What are the general and common ethical principles, rules, guidelines, policies, and regulations that can resolve or at least attenuate these ethical and moral issues with AI? What are some of the necessary features and characteristics of an ethical AI? How to adhere to the ethics of AI to build ethical AI?
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Muhammad Chairil Imran, Nurul Amaliah, Rampeng, Nur Ina Syam, Fahmi Room, and Muhammad Sofyan Djafar Sage. "The Feasibility of Artificial Intelligences (AI) In Speaking Skill: Lecturers’ Perceptions." IJOLEH : International Journal of Education and Humanities 2, no. 2 (November 8, 2023): 135–44. http://dx.doi.org/10.56314/ijoleh.v2i2.172.
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The benefits of Artificial intelligence (AI) for education can be understood as a long-term investment, which helps lecturers, students and education system continue to improve the quality of education. The development of artificial intelligence (AI) today is increasingly rapid and increasingly integrated with social life in society. Artificial intelligence (AI) continues to be developed to support science and technology, including in education. These tools can help lecturers to improve their teaching practices. The aim of the present study is to Lecturers perceptions on use of Artificial Intelligence (AI) technology in learning Speaking. This study applied qualitative research. The results of the study found that Artificial Intelligences (AI) technology has opened the door to more adaptive and personalized education. The use of AI technology has brought a transformation in learning methods. Artificial Intelligences (AI) also enables adaptive learning in speaking class. It can be concluded that the use of Artificial Intelligences (AI) in language learning has opened up various new opportunities in increasing the effectiveness and efficiency of language learning, especially in speaking class.
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Takama, Yasufumi. "Web Intelligence and Artificial Intelligence." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 1 (January 20, 2017): 25–30. http://dx.doi.org/10.20965/jaciii.2017.p0025.
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This paper briefly summarizes the progress of artificial intelligence (AI) and web intelligence (WI) in the last two decades. The reason why we mention AI and WI together is because those have strong relationship with each other. This paper first summarizes the history of AI, and then gives brief description of supervised learning, which I think has played a major role in AI in the last two decades. As most history of WI is in the target decades, this paper first briefly describes major WI topics, and then gives more detailed description about information recommendation, which I think one of more successful and necessary technologies in practical use.
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Avetisyana, A. I. "Trusted artificial intelligence." Вестник Российской академии наук 94, no. 3 (August 15, 2024): 200–209. http://dx.doi.org/10.31857/s0869587324030039.
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In this paper we discuss the problem of creating trusted artificial intelligence (AI) technologies. Modern AI is based on machine learning and neural networks and is vulnerable to biases and errors. Efforts are made to establish standards for the development of trusted AI technologies, but they have not yet succeeded. AI technologies trust can only be achieved with the appropriate scientific and technological base and corresponding tools and techniques for countering attacks. We present the ISP RAS Trusted AI Research Center results and propose a work model that can ensure technological independence and long-term sustainable development in this area.
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Norvig, Peter. "Artificial intelligence: Everyday AI." New Scientist 216, no. 2889 (November 2012): iv—v. http://dx.doi.org/10.1016/s0262-4079(12)62784-5.
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Balas, Hashim, and Reem Shatnawi. "Legal framework for AI applications." F1000Research 13 (April 29, 2024): 418. http://dx.doi.org/10.12688/f1000research.147019.1.
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Artificial intelligence (AI), the most widespread technological term, has become an integral part of human daily life. People are becoming increasingly dependent on AI-powered devices; thus, it is now essential to have a legal framework to oversee artificial intelligence's various uses and legal peculiarities. As artificial intelligence has entered all areas of life and into various sectors, which requires examining in detail the legal nature of artificial intelligence, determining the laws that must be applied to it, and identifying the people or entities responsible for it to determine the scope of their responsibilities for the resulting damages that may be caused to others as a result of the use of intelligence. Artificial, this research aimed to examine the adequacy of the legal rules in Jordanian legislation regulating the provisions of artificial intelligence in light of the diversity of its applications and its different legal nature. The research is divided into two chapters. The first chapter presents the concept of artificial intelligence, and the second chapter discusses the legal liability of artificial intelligence. The results of the research revealed that the Jordanian legislator did not specify the legal nature of the artificial intelligence and contented himself with stipulating it in separate texts, Legal liability resulting from utilizing artificial intelligence systems can be challenged under regulations of the defect in manufacturing, responsibility for guarding things, and the distinction between responsibilities due to the degree of independence and intelligence of artificial intelligence, In determining the liability of artificial intelligence, the legislator should consider the types of artificial intelligence systems, their different capabilities, and their independence from humans, The process of enacting special laws regulating all aspects of artificial intelligence must be expedited. This law should be characterized by flexibility that enables it to keep pace with and rapid development witnessed in this field.
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Femi, Femi, and Didi Supriadi. "Implementation of Artificial Intelligence Technology-Based Learning Media at SD Negeri Kotagede 1 Yogyakarta." International Journal of Engineering, Science and Information Technology 5, no. 1 (November 8, 2024): 51–56. http://dx.doi.org/10.52088/ijesty.v5i1.628.
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In the digital era, the field of education is witnessing the transformation that occurs through the integration of artificial intelligence (AI). With artificial intelligence's (AI) potential to revolutionize various sectors, it presents itself as a material or tool that can enhance the teaching and learning experience. Its features align with our thinking, enabling us to progress according to our desired content. Artificial intelligence (AI) is today's most important tool in education. Artificial intelligence (AI) plays a crucial role in enabling the use of AI-based learning media, thereby facilitating the learning process in education. Artificial intelligence (AI)--based learning media in education will aid teachers and students in learning. This study aims to provide insight to all of us regarding the implementation of learning media based on artificial intelligence (AI) technology at SD Negeri Kotagede 1 Yogyakarta. This study employs a descriptive-qualitative approach. In the current educational landscape, particularly at SD Negeri Kotagede 1 Yogyakarta, artificial intelligence (AI) plays a crucial role. Artificial intelligence (AI) can facilitate the learning process flow by using learning media based on artificial intelligence technology. Teachers can utilize artificial intelligence to design programs and learning processes, while students can enhance their comprehension of the material and cultivate their critical thinking skills. Implementing learning media based on artificial intelligence (AI) technology can benefit educational institutions in a more interesting, innovative, effective, and creative learning process.
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Darwish, Ashraf. "Explainable Artificial Intelligence: A New Era of Artificial Intelligence." Digital Technologies Research and Applications 1, no. 1 (January 26, 2022): 1. http://dx.doi.org/10.54963/dtra.v1i1.29.
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Recently, Artificial Intelligence (AI) has emerged as an emerging with advanced methodologies and innovative applications. With the rapid advancement of AI concepts and technologies, there has been a recent trend to add interpretability and explainability to the paradigm. With the increasing complexity of AI applications, their a relationship with data analytics, and the ubiquity of demanding applications in a variety of critical applications such as medicine, defense, justice and autonomous vehicles , there is an increasing need to associate the results with sound explanations to domain experts. All of these elements have contributed to Explainable Artificial Intelligence (XAI).
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Lee, Jin Choon. "Application of Artificial Intelligence (AI) in Laryngeal Cancer." Journal of Clinical Otolaryngology Head and Neck Surgery 34, no. 2 (June 2023): 27–35. http://dx.doi.org/10.35420/jcohns.2023.34.2.27.
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Devedzic, Vladan. "Is this artificial intelligence?" Facta universitatis - series: Electronics and Energetics 33, no. 4 (2020): 499–529. http://dx.doi.org/10.2298/fuee2004499d.
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Artificial Intelligence (AI) has become one of the most frequently used terms in the technical jargon (and often in not-so-technical jargon). Recent advancements in the field of AI have certainly contributed to the AI hype, and so have numerous applications and results of using AI technology in practice. Still, just like with any other hype, the AI hype has its controversies. This paper critically examines developments in the field of AI from multiple perspectives - research, technological, social and pragmatic. Part of the controversies of the AI hype stem from the fact that people use the term AI differently, often without a deep understanding of the wider context in which AI as a field has been developing since its inception in Mid 1950s.
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Karki, Dipendra, Nirupan Karki, Rewan Kumar Dahal, and Ganesh Bhattarai. "Future of Education in the Era of Artificial Intelligence." Journal of Interdisciplinary Studies 12, no. 1 (December 31, 2023): 54–63. http://dx.doi.org/10.3126/jis.v12i1.65448.
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The increasing use of Artificial Intelligence (AI) in the field of education has raised significant concerns regarding the potential displacement of educators by AI systems. The present study explores the diverse domain of artificiala intelligence’s influence on academia, examining its capacity to transform conventional educational frameworks. By conducting a methodical investigation using scholarly resources including IEEE Xplore, ACM Digital Library, ERIC, and Google Scholar, this study develops an extensive compilation of 135 publications that were published between January 2017 and June 2023. The results of the study demonstrate a dynamic environment in which artificial intelligence serves as both a stimulant and a challenge. The present analysis emphasizes the complex relationship between artificial intelligence (AI) and education, as evidenced by the theoretical underpinnings emphasized by Panaou et al. (2012), as well as the promise of AI advocated by Luckin et al. (2016). The research highlights the significance of adopting a well-rounded strategy, wherein artificial intelligence serves to enhance the responsibilities of educators rather than replace them.
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Smith, Adam Leon. "Artificial Intelligence." ITNOW 64, no. 3 (August 19, 2022): 47. http://dx.doi.org/10.1093/combul/bwac093.
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Warankar, Mayuri. "Generative Artificial Intelligence." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 20, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem31146.
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Generative AI is a cool tech that helps machines create new stuff that looks a lot like what humans make. Think of it like a computer artist who can paint pictures, write stories, compose music, and even make videos. This paper is all about explaining generative AI: where it came from, what it's doing now, and how it's used. It works by using fancy computer programs and smart algorithms to understand patterns in data and then make new things that fit those patterns. It's super important because it's changing how we do things in fields like healthcare, entertainment, and education. But, it's not all fun and games. Generative AI also brings up some serious questions about privacy, fairness, and making sure we use it in good ways. This paper dives into all that, showing the good and the tricky parts of generative AI and how it's shaping our world. Key Words: Generative AI, technology, machine creativity, data patterns, applications, healthcare, entertainment, education, privacy, fairness, ethical use, societal impact.
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MR, Anoop. "ARTIFICIAL INTELLIGENCE AND MARKETING." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 4 (April 11, 2021): 1247–56. http://dx.doi.org/10.17762/turcomat.v12i4.1184.
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Artificial intelligence (AI) has grown in recent years in many fields: research, industry, pharmaceuticals, automobile and education. In marketing, AI has also been effective. The aim of this article is to explore the usage and effect of AI in marketing. The authors posed two study concerns - which fields are applied to AI marketing and how AI impacts marketers. The authors carried out secondary data investigations with samples of AI used for marketing purposes in order to address these queries. The review of the illustration given demonstrates, while the implementations are manual, that AI is broadly integrated in marketing. This may be a result of the latest technologies being implemented cautiously and experimentally. Uncertainty about the AI implementation outcomes can influence the caution when applying these developments. In the position of marketing managers, the emerging AI assistants often participate as the results of the survey reveal that they are becoming an increasingly valuable delivery platform such that products are increasingly important. The findings of this analysis show that improving the AI assistants would also be important. The benefit of competition is therefore reduced to a hygiene consideration inasmuch as the search engine optimization is optimised and saturated for each operator. Brand design would once again become an essential criterion for customer decision-making. Moreover, because consumer data collection is an essential component in the usage of AI technology in marketing, the results demonstrate that marketing managers strive more and more to enforce consistent customer policy. Furthermore, the growing usage of AI technology often requires sufficient technical expertise from marketing managers. For example, in both facets of the marketing mix, AI influences both the distribution of customer value and the marketing and management. In specific proposals for marketing AI deployment, innovation design and perspectives into how new capabilities may be incorporated into the new technology marketing team have consequences for the business.
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Smith, Adam Leon. "Artificial Intelligence." ITNOW 64, no. 2 (May 12, 2022): 65. http://dx.doi.org/10.1093/itnow/bwac065.
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Rodrigues, Rowena, Anais Resseguier, and Nicole Santiago. "When Artificial Intelligence Fails." Public Governance, Administration and Finances Law Review 8, no. 2 (December 14, 2023): 17–28. http://dx.doi.org/10.53116/pgaflr.7030.
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Diverse initiatives promote the responsible development, deployment and use of Artificial Intelligence (AI). AI incident databases have emerged as a valuable and timely learning resource and tool in AI governance. This article assesses the value of such databases and outlines how this value can be enhanced. It reviews four databases: the AI Incident Database, the AI, Algorithmic, and Automation Incidents and Controversies Repository, the AI Incident Tracker and Where in the World Is AI. The article provides a descriptive analysis of these databases, examines their objectives, and locates them within the landscape of initiatives that advance responsible AI. It reflects on their primary objective, i.e. learning from mistakes to avoid them in the future, and explores how they might benefit diverse stakeholders. The article supports the broader uptake of these databases and recommends four key actions to enhance their value.
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Yadav, Narendra, Latika Sharma, and Urmila Dhake. "Artificial Intelligence: The Future." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (December 30, 2023): 1–10. http://dx.doi.org/10.55041/ijsrem27796.
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Artificial intelligence is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the field of study in computer science that develops and studies intelligent machines. "AI" may also refer to the machines themselves. AI is not a new for the scientist, it was introduce in 1943 with artificial neurons model and get popular in 1950 due to “Turting test” the test was done to get answer that machine can think?, purposed by Alan Turing. Basically AI is categorized into three types, Artificial Narrow Intelligence, Artificial General Intelligence and Artificial Super Intelligence. Deep learning and machine learning is major subfield of Artificial intelligence. DL as a subset of ML, which is also another subset of AI. Therefore, AI is the all-encompassing concept that initially erupted. Application of AI fields are Healthcare, Business, Education, Agriculture, Finance, Law, Entertainment and media, Software coding and IT processes, Security, Manufacturing, Banking and Transportation. In reference to Job creation or distraction, Artificial Intelligence is not job killer but a job category killer”. In the latest report (May 2023) on The Future of Jobs, the World Economic Forum (WEF) predicts the creation of 69 million jobs by 2027 thanks to AI, but also the destruction of 89 million jobs. In context to intelligence level, Jan. 2022, Age of IQ level of AI was as 7 year Children and in Dec. 2022, Age of IQ level of AI was as 9 year Children. India is emerging market in global and it has around 12 % of work could be automated by AI. In India more than 2000 startup are related to AI and 90000 plus AI Professional work in India.The economic impact of AI, for select G20 countries and estimates AI to boost India’s annual growth rate by 1.3 percentage points by 2035. AI has potential to add 1 trillion to India’s economy in 2035. We are going to enter into new technological world, it’s may be our fortune or misfortune. Key Words: - Artificial Intelligence, Machine learning, Job, India
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Kambarbekov, G. М., and A. Ye Baimaganbetov. "USING ARTIFICIAL INTELLIGENCE FOR HYDROLOGICAL MODELLING." Geography and water resources, no. 1 (March 28, 2024): 58–62. http://dx.doi.org/10.55764/2957-9856/2024-1-58-62.8.
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Hydrological modelling plays a critical role in managing water resources, especially in arid and semi-arid regions where water scarcity is a major challenge. With the emergence of artificial intelligence (AI), hydrological modelling has experienced a significant transformation in recent years. This paper reviews the recent advances in AI-based hydrological modelling and examines its potential applications in water resource management. The study highlights the role of AI in enhancing the accuracy of hydrological models and facilitating more efficient and sustainable water management practices. The results suggest that AI-based hydrological models have the potential to revolutionize the way water resources are managed, and that future research in this area is warranted.
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Schuurman, Derek C. "Virtue and Artificial Intelligence." Perspectives on Science and Christian Faith 75, no. 3 (December 2023): 155–61. http://dx.doi.org/10.56315/pscf12-23schuurman.
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Two questions concerning artificial intelligence (AI) and virtue are explored. The first question is whether AI is capable of virtue, and the second question explores if AI can assist humans in the acquisition of virtue. It is argued that AI cannot be a moral agent and therefore cannot genuinely be virtuous. However, AI can perform behaviors that are in accordance with virtuous behavior. The notion of "virtue-by-proxy" is introduced in which virtuous programmers can strive to design AI programs that are trained to mimic certain virtues or behave in accordance with virtue. Next, it is argued that since AI systems can nudge humans toward repeated practices and habits, they will inevitably shape and form users. Thus, AI systems might be designed to assist humans with virtue formation; likewise, they could be misdirected to encourage certain vices. Finally, the concept of virtue in the Christian tradition is contrasted with secular notions of virtue and is used to inform limits on the role of AI in virtue formation.
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Sharma, Anupam, and Jasleen Kaur. "Artificial Intelligence Based System." Information Resources Management Journal 34, no. 2 (April 2021): 80–90. http://dx.doi.org/10.4018/irmj.2021040105.
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The field of artificial intelligence (AI) has evolved considerably in the last 60 years. While there are now many AI applications that have been deployed in high-income country contexts, use of AI in resource-poor settings remains relatively nascent. With a few notable exceptions, there are limited examples of AI being used in such settings. However, there are signs that this is changing. Several high-profile meetings have been convened in recent years to discuss the development and deployment of AI applications to reduce poverty and deliver a broad range of critical public services. The authors provide a general overview of AI and how it can be used to improve global health outcomes in resource-poor settings. They also describe some of the current ethical debates around patient safety and privacy. The research paper specifically highlights the challenges related to women menstrual hygiene and suggests AI technology for improving the menstrual hygiene and healthcare services in resource-poor settings for women. Many health system hurdles in such settings could be overcome with the use of AI and other complementary emerging technologies. Further research and investments in the development of AI tools tailored to resource-poor settings will accelerate the realization of the full potential of AI for improving global health in resource-poor contexts.
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Zurnali, Cut, and Wahjono Wahjono. "ARTIFICIAL INTELLIGENCE DALAM REKRUTMEN." Jurnal Ilmiah Infokam 18, no. 2 (December 14, 2022): 119–24. http://dx.doi.org/10.53845/infokam.v18i2.327.
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Teknologi AI telah mencapai fase pengembangan berkecepatan tinggi. AI memungkinkan perusahaan untuk menghapus tugas yang berulang, membosankan, dan rentan terhadap kesalahan karena ambiguitas. AI membantu departemen SDM dengan mengotomatiskan dan menyelesaikan sebagian besar tugas SDM bernilai rendah ke lingkup pekerjaan yang lebih strategis. AI memiliki potensi untuk merevolusi pengalaman karyawan dalam berbagai cara, mulai dari perekrutan hingga manajemen bakat, dengan memproses sejumlah besar data secara cepat dan akurat. Banyak organisasi sudah mengintegrasikan teknologi AI dalam proses rekrutmen karyawan baru. Secara empiris dan konseptual, dampak AI terhadap proses rekrutmen dapat ditemukan dalam banyak penelitian dan kajian literatur.
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Singh, Anant Manish, and Wasif Bilal Haju. "Artificial IntelligenceArtificial Intelligence." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 1210–20. http://dx.doi.org/10.22214/ijraset.2022.44306.
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Abstract: Artificial intelligence (A.I.) is a multidisciplinary field aimed at automating tasks that currently need human intelligence. Despite its lack of general familiarity, artificial intelligence (AI) is a technology that is revolutionizing every aspect of life. This article aims to educate laypeople about AI and encourage them to utilize it as a tool in many disciplines to rethink how we combine data, analyze it, and make choices. We quickly covered what artificial intelligence (AI) is, how it works, and how it may be applied in our daily lives in this article.
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Marinchak, Christina McDowell, Edward Forrest, and Bogdan Hoanca. "Artificial Intelligence." International Journal of E-Entrepreneurship and Innovation 8, no. 2 (July 2018): 14–24. http://dx.doi.org/10.4018/ijeei.2018070102.
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As marketers and consumers simultaneously adopt artificial intelligence (AI) services and applications, the dynamic of the process of exchange between the buyer and seller in the marketplace is being fundamentally altered. This article reviews the emerging patterns of adoption and rates of diffusion of AI applications by both marketers and consumers. On the marketers' side the authors will address the single most defining phenomenon that is affecting the marketer's role and function in the marketing process: the exponential increase in the number, variety and capability of marketing applications, platforms and services that perform, control, influence and/or integrate virtually every marketing task and decision.
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Rezaev, Andrey V., and Natalia D. Tregubova. "Artificial Intelligence and Artificial Sociality." Epistemology & Philosophy of Science 56, no. 4 (2019): 183–99. http://dx.doi.org/10.5840/eps201956475.
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The paper aims to formulate theoretical and methodological foundations as well as basic research questions for studying intervention of artificial intelligence in everyday life of medical and life sciences in the 21 century. It is an invitation for professional philosophical, theoretical and methodological discussion about the necessity and reality of artificial intelligence in contemporary medical/life sciences and medicine. The authors commence with a proposition of their definitions of ‘artificial intelligence’ (AI) and ‘artificial sociality’ (AS). The next section of the paper deals with a review of basic trends in medical/life sciences and medicine. In what follows the authors debate two problems related to incorporation of AI in reality of current medicine. The first is the potential revision of the principles developed in western medicine; the second is the alteration of the contents and forms of medical education. The authors theorize the dynamic interplay between structural expansion and cultural contraction of medicine and life sciences in current practices of higher education and explore how this introduces an essential tension between the necessity and reality for medical professionals to work with AI. The paper shows that attending to institutional dynamics serves as a critical and timely extension of disciplinary/cross/anti-disciplinary critiques of science and medicine, not only since the current inclusion agenda of the AI in medicine may do little to address the real concerns of a medical profession in the XXI century but also because it may inadvertently undermine the institutional recognition and epistemic acceptance of new anti-disciplinary vista for studying AI per se. In conclusion the authors underline basic outcomes of the discussion and propose further routes for inquiry and research.
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Reggia, James A., Garrett E. Katz, and Gregory P. Davis. "Artificial Conscious Intelligence." Journal of Artificial Intelligence and Consciousness 07, no. 01 (March 2020): 95–107. http://dx.doi.org/10.1142/s270507852050006x.
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The field of artificial consciousness (AC) has largely developed outside of mainstream artificial intelligence (AI), with separate goals and criteria for success and with only a minimal exchange of ideas. This is unfortunate as the two fields appear to be synergistic. For example, here we consider the question of how concepts developed in AC research might contribute to more effective future AI systems. We first briefly discuss several past hypotheses about the function(s) of human consciousness, and present our own hypothesis that short-term working memory and very rapid learning should be a central concern in such matters. In this context, we then present ideas about how integrating concepts from AC into AI systems to develop an artificial conscious intelligence (ACI) could both produce more effective AI technology and contribute to a deeper scientific understanding of the fundamental nature of consciousness and intelligence.
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Fan, Yifei, and Frank Desvignes. "Artificial intelligence in China." Annales des Mines - Enjeux numériques N° 1, no. 1 (January 24, 2018): 72–77. http://dx.doi.org/10.3917/ennu.001.0072.
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China has emerged as a major competitor of the United States in the field of artificial intelligence (AI), even though the total funding in AI startups in China is still lagging behind the US. The application of AI in China is already massive (especially in Fintechs) and has perhaps surpassed every other country in the world. The initiatives of the Chinese tech giants (Baidu, Alibaba and Tecent) are described along with government plans. Attention is drawn to China’s competitive advantages in AI and to use cases in insurance. Instead of just being innovative imitators, Chinese players have become leaders in developing and applying AI. In the future, China might show the world how to do AI…
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Dayal, Aryeshwar. "Artificial Intelligence and Artificial Stupidity: The Inseparables." International Journal of Computer Science and Mobile Computing 13, no. 10 (October 30, 2024): 54–57. http://dx.doi.org/10.47760/ijcsmc.2024.v13i10.006.
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Artificial intelligence (AI) has long been heralded for its ability to simulate human intelligence, enabling machines to perform complex tasks such as decision-making, problem-solving, and data analysis. However, alongside the advancements in AI, the concept of artificial stupidity (AS) has gained attention. AS refers to the limitations and errors made by AI systems, often resulting from incomplete data, biased algorithms, or the inherent restrictions placed on AI to simulate more human-like decision-making. These instances of "stupidity" can lead to nonsensical or harmful outcomes, especially when AI is applied to critical areas such as healthcare, autonomous systems, and legal decision-making. This narrative review explores the duality between AI's potential and its flaws, emphasizing the importance of understanding both AI and AS in developing robust, safe, and ethical AI applications. By addressing the causes of artificial stupidity, such as algorithmic limitations and poor data quality, researchers and developers can improve the reliability and decision-making capabilities of AI systems. There is also the need for human oversight and ethical considerations to mitigate the negative impacts of artificial stupidity, especially in high-stakes environments.
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Swain, Santosh Kumar. "Artificial Intelligence in Otorhinolaryngology." Annals of Indian Academy of Otorhinolaryngology Head and Neck Surgery 7, no. 2 (2023): 19–24. http://dx.doi.org/10.4103/aiao.aiao_9_23.
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Abstract Artificial intelligence (AI) is most likely to have a significant influence on medical research and clinical practice in the near future. Common uses of AI in health care include diagnosis of disease, complete drug research, and development, improved clinician–patient communication, transcription of medical records like prescriptions, and remote patient treatment. The search strategy was made with keywords of AI and otorhinolaryngology on Medline, Scopus, PubMed, and Google Scholar databases, and full-text articles available were reviewed. This review article is focused on the use of AI in otorhinolaryngology. Innovative new health-care solutions in the area of otorhinolaryngology are being driven by recent breakthroughs in AI. Otorhinolaryngologists are key stakeholders of AI technologies that will enhance patient care. For improving AI technologies, high-standard data collecting is necessary, and otorhinolaryngologists should work with data scientists to direct them toward the most significant medical research. This review article emphasizes the crucial value of ethical, unbiased artificially intelligent systems for patient management in otorhinolaryngology.
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Silbert, Tony, and Bill Matuszak. "Artificial Intelligence (AI) Meets Appreciative Inquiry (ai)." AI Practitioner 26, no. 3 (September 1, 2024): 14–20. http://dx.doi.org/10.12781/978-1-907549-60-1-3.
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Tony Silbert and Bill Matuszak’s collaborative dialogue explores the potential fusion of AI and ai. Their conversation underscores the significance of proactively mitigating biases in Artificial Intelligence through Appreciative Inquiry’s generative-focused approach. It highlights the need for collaboration between AI experts and ai practitioners to foster ethical AI development practices that prioritize transparency, fairness, and accountability.
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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 (June 15, 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 AI, energized by a tremendous increase in computing capacity and a significantly greater increase in knowledge. AI, along with machine learning, can be used in computer vision. More advantages in the field of engineering as well as in medicine can be accomplished based on these future scenarios worldwide. Healthcare is seen as the next domain that is said to be altered by the use of the concept of artificial intelligence. The AI process is used for critical diseases such as cancer, neurology, cardiology and diabetes. The review includes the ongoing flow status of medical services for AI applications. A few progressive explorations of AI applications in medicinal services that provide a perspective on future where human interactions are gradually brought together by social insurance conveyance. Likewise, this review will discuss how AI and machine learning can save the life of someone. It is also a guide for healthcare professionals to see how, when, and where AI can be more efficient and have the desired outcomes.
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Gheysen, F., and S. Rex. "Artificial intelligence in anesthesiology." Acta Anaesthesiologica Belgica 74, no. 3 (September 2023): 185–94. http://dx.doi.org/10.56126/75.3.21.
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Artificial intelligence (AI) is rapidly evolving and gaining attention in the medical world. Our aim is to provide readers with insights into this quickly changing medical landscape and the role of clinicians in the middle of this popular technology. In this review, our aim is to explain some of the increasingly frequently used AI terminology explicitly for physicians. Next, we give a summation, an overview of currently existing applications, future possibilities for AI in the medical field of anesthesiology and thoroughly highlight possible problems that could arise from implementing this technology in daily practice. Therefore, we conducted a literature search, including all types of articles published between the first of January 2010 and the 1st of May 2023, written in English, and having a free full text available. We searched Pubmed, Medline, and Embase using “artificial intelligence”, “machine learning”, “deep learning”, “neural networks” and “anesthesiology” as MESH terms. To structure these findings, we divided the results into five categories: preoperatively, perioperatively, postoperatively, AI in the intensive care unit and finally, AI used for teaching purposes. In the first category, we found AI applications for airway assessment, risk prediction, and logistic support. Secondly, we made a summation of AI applications used during the operation. AI can predict hypotensive events, delivering automated anesthesia, reducing false alarms, and aiding in the analysis of ultrasound anatomy in locoregional anesthesia and echocardiography. Thirdly, namely postoperatively, AI can be applied in predicting acute kidney injury, pulmonary complications, postoperative cognitive dysfunction and can help to diagnose postoperative pain in children. At the intensive care unit, AI tools discriminate acute respiratory distress syndrome (ARDS) from pulmonary oedema in pleural ultrasound, predict mortality and sepsis more accurately, and predict survival rates in severe Coronavirus-19 (COVID-19). Finally, AI has been described in training residents in spinal ultrasound, simulation, and plexus block anatomy. Several concerns must be addressed regarding the use of AI. Firstly, this software does not explain its decision process (i.e., the ‘black box problem’). Secondly, to develop AI models and decision support systems, we need big and accurate datasets, unfortunately with potential unknown bias. Thirdly, we need an ethical and legal framework before implementing this technology. At the end of this paper, we discuss whether this technology will be able to replace the clinician one day. This paper adds value to already existing literature because it not only offers a summation of existing literature on AI applications in anesthesiology but also gives clear definitions of AI itself and critically assesses implementation of this technology.
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Shinde, Sachin, Yojana Patil, Amol Jamkhande, Yashodharaa Shah, Neelam Kakde, Pramod Waghmare, Rachna Sonone, Snehal Pote, and Isha Vaidya. "Artificial Intelligence in Dentistry." Journal of Indian Association of Public Health Dentistry 22, no. 1 (2024): 6–10. http://dx.doi.org/10.4103/jiaphd.jiaphd_272_22.
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Artificial intelligence (AI) is a technological breakthrough that is rapidly progressing all over the world. AI has a variety of uses in medicine and dentistry, ranging from data analysis to using neural networks for diagnosis. AI has received enormous attention and has gone through a transition stage from being a pure statistical tool to being one of the main drivers of modern medicine. We are at the dawn of a new era, and AI is undoubtedly the future of dental practice management. This aim article is to review the various applications of AI in all the specialties of dentistry.
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Al Hendi, Khalid Dhafer, Mohammad Hamad Alyami, Mashary Alkahtany, Alok Dwivedi, and Hussain Ghanem Alsaqour. "Artificial intelligence in prosthodontics." Bioinformation 20, no. 3 (March 31, 2024): 238–42. http://dx.doi.org/10.6026/973206300200238.
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Artificial Intelligence (AI) is gaining popularity worldwide owing to its significant impact in science and innovation. The role of AI in prosthodontics has increased significantly in recent years. AI is used for diagnosis, decision-making, prognosis, treatment planning and prediction of outcomes. Integration of AI into prosthodontics can enhance the accuracy and precision of dental practice. However, limited datasets are a major constraint in its practical applications.
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Rios-Campos, Carlos, Sandra Marcela Zapata Vega, Mariuxi Ileana Tejada-Castro, Erick Orlando Guerrero Zambrano, Dany Jamnier German Barreto Perez, Edilbrando Vega Calderón, Luz Magaly Fernandez Rojas, and Irene Marely Ballena Alcantara. "Artificial Intelligence and Business." South Florida Journal of Development 4, no. 9 (November 29, 2023): 3547–64. http://dx.doi.org/10.46932/sfjdv4n9-015.
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The general objective of the research was to determine the advances related to the artificial intelligence and business. The specific objectives of the research are to identify the software of AI used in business and the countries that invest more in AI. Methodology, in this research, 62 documents have been selected, carried out in the period 2018 - 2023; including: scientific articles, review articles and information from websites of recognized organizations. Results, every day new AI tools appear that support activities in today's businesses. Conclusions, about the general objective of the research, the importance of AI in business is beginning to be understood. Therefore, it is adopted in various organizational processes worldwide. AI is impacting various human activities, so it is necessary to keep an eye on its evolution. During the pandemic, businesses worldwide had to intensively use information and communication technologies in order to reach their customers. Subsequently, AI is presented as a tool that can radically change business. About the specific objectives of the research, the software of AI used in business are: Salesforce, HubSpot, IBM Watson, ChatGPT, Alteryx Analytics Automation Platform, Amazon SageMaker, GPT-3 model, Adobe Sensei, Marketo, Supply-chain management solutions based on artificial intelligence (AI), Kasisto, Workday, HireVue, Tableau, Power BI, Dynamic Yield, Darktrace, Copy.ai, UiPath, Automation Anywhere, Merative, Google Health, Google Translate. The countries that invest the most in AI are the United States, China and the European Union.
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Mofatteh, Mohammad. "Neurosurgery and artificial intelligence." AIMS Neuroscience 8, no. 4 (2021): 477–95. http://dx.doi.org/10.3934/neuroscience.2021025.
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<abstract> <p>Neurosurgeons receive extensive and lengthy training to equip themselves with various technical skills, and neurosurgery require a great deal of pre-, intra- and postoperative clinical data collection, decision making, care and recovery. The last decade has seen a significant increase in the importance of artificial intelligence (AI) in neurosurgery. AI can provide a great promise in neurosurgery by complementing neurosurgeons' skills to provide the best possible interventional and noninterventional care for patients by enhancing diagnostic and prognostic outcomes in clinical treatment and help neurosurgeons with decision making during surgical interventions to improve patient outcomes. Furthermore, AI is playing a pivotal role in the production, processing and storage of clinical and experimental data. AI usage in neurosurgery can also reduce the costs associated with surgical care and provide high-quality healthcare to a broader population. Additionally, AI and neurosurgery can build a symbiotic relationship where AI helps to push the boundaries of neurosurgery, and neurosurgery can help AI to develop better and more robust algorithms. This review explores the role of AI in interventional and noninterventional aspects of neurosurgery during pre-, intra- and postoperative care, such as diagnosis, clinical decision making, surgical operation, prognosis, data acquisition, and research within the neurosurgical arena.</p> </abstract>
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Olojede, Helen Titilola, and Ayo Fadahunsi. "On Decolonising Artificial Intelligence." Àgídìgbo: ABUAD Journal of the Humanities 12, no. 1 (September 12, 2024): 269–82. http://dx.doi.org/10.53982/agidigbo.2024.1201.20-j.
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Logic and probability as branches of Mathematics and aspects of Philosophy, underlie and play significant roles in the development of Artificial Intelligence (AI). In its simplest form, logic concerns right reasoning (especially one devoid of fallacies), patent truth and inferences. Probability has to do with uncertainties, that is, the likelihood of an event happening. The divide between traditional AI and modern AI regarding what roles logic and probability play in the development of AI has been mitigated with the notion that both are complementary without displacing the other. While the birth of AI as a field is usually linked to the 1956 conference with figures involving Marvin Minsky and John McCarthy, there are traces of what we refer to as robots, automatons and computations which form the foundation of AI in some non-Western philosophies. To this end, this paper chronicles the emergence of AI in non-Western philosophies, especially in African philosophy and then uses the Yoruba's 'ifá' to exemplify the idea of decolonising Al, not forgetting that the basis of ifá itself is logic and, sometimes, probability.
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Znamenska, Maria. "CPD: Artificial intelligence 4." Optician 269, no. 6950 (April 26, 2024): 22–25. http://dx.doi.org/10.12968/opti.2024.269.6950.22.
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In a continuation of our AI series, OCT expert Maria Znamenska, an associate professor of ophthalmology and chief medical officer for AI Altris, describes the potential applications of AI technology to OCT scanning in optometric practice
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Kertysova, Katarina. "Artificial Intelligence and Disinformation." Security and Human Rights 29, no. 1-4 (December 12, 2018): 55–81. http://dx.doi.org/10.1163/18750230-02901005.
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This article explores the challenges and opportunities presented by advances in artificial intelligence (AI) in the context of information operations. The article first examines the ways in which AI can be used to counter disinformation online. It then dives into some of the limitations of AI solutions and threats associated with AI techniques, namely user profiling, micro-targeting, and deep fakes. Finally, the paper reviews a number of solutions that could help address the spread of AI-powered disinformation and improve the online environment. The article recognises that in the fight against disinformation, there is no single fix. The next wave of disinformation calls first and foremost for societal resilience.