Search results for: legal artificial intelligence

Authors: Ukpaka Paschal

Abstract:

Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.

Keywords: artificial intelligence, creativity, GANs, first-person experience

Procedia PDF Downloads 138

Authors: Belkacem Laimouche

Abstract:

With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

Procedia PDF Downloads 105

Authors: Seyed Sobhan Alvani, Mohammad Gohari

Abstract:

By developing cities and increasing the population, traffic congestion has become a vital problem. Due to this crisis, urban designers try to present solutions to decrease this difficulty. On the other hand, predicting the model with perfect accuracy is essential for solution-providing. The current study presents a model based on artificial intelligence which can predict traffic index based on city population, growth rate, and area. The accuracy of the model was evaluated, which is acceptable and it is around 90%. Thus, urban designers and planners can employ it for predicting traffic index in the future to provide strategies.

Keywords: traffic index, population growth rate, cities wideness, artificial neural network

Procedia PDF Downloads 44

Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

Abstract:

Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

Procedia PDF Downloads 79

Authors: Sanele E. Nene L., Lia M. Hewitt

Abstract:

Background: Artificial intelligence (AI) has a high value in healthcare, various applications have been developed for the efficiency of clinical operations, such as appointment/surgery scheduling, diagnostic image analysis, prognosis, prediction and management of specific ailments. Purpose: The purpose of this study was to explore, describe, contrast, evaluate, and develop the various leadership strategies as a conceptual framework, applied by public health Operational Managers (OMs) to embrace AI benefits, with the aim to improve the healthcare system in a public hospital. Design and Method: A qualitative, exploratory, descriptive and contextual research design was followed and a descriptive phenomenological approach. Five phases were followed to conduct this study. Phenomenological individual interviews and focus groups were used to collect data and a phenomenological thematic data analysis method was used. Findings and conclusion: Three themes surfaced as the experiences of AI by the OMs; Positive experiences related to AI, Management and leadership processes in AI facilitation, and Challenges related to AI.

Keywords: ambivalence, embracing, Artificial intelligence, public hospital

Procedia PDF Downloads 80

Authors: Duong Van Thanh

Abstract:

Artificial Intelligence (AI) has been recently a new trend in Higher Education systems globally as well as in the Vietnamese Higher Education. This study explores the benefits and challenges in applications of AI in 02 selected universities, ie. Vietnam National Universities in Hanoi Capital and the University of Economics in Ho Chi Minh City. Particularly, this paper focuses on how the ethics of Artificial Intelligence have been addressed among faculty members at these two universities. The AI ethical issues include the access and inclusion, privacy and security, transparency and accountability. AI-powered educational technology has the potential to improve access and inclusion for students with disabilities or other learning needs. However, there is a risk that AI-based systems may not be accessible to all students and may even exacerbate existing inequalities. AI applications can be opaque and difficult to understand, making it challenging to hold them accountable for their decisions and actions. It is important to consider the benefits that adopting AI-systems bring to the institutions, teaching, and learning. And it is equally important to recognize the drawbacks of using AI in education and to take the necessary steps to mitigate any negative impact. The results of this study present a critical concern in higher education in Vietnam, where AI systems may be used to make important decisions about students’ learning and academic progress. The authors of this study attempt to make some recommendation that the AI-system in higher education system is frequently checked by a human in charge to verify that everything is working as it should or if the system needs some retraining or adjustments.

Keywords: artificial intelligence, ethics, challenges, vietnam

Procedia PDF Downloads 130

Authors: Xiaochen Mu

Abstract:

Due to the diversity of stakeholders and the ambiguity of ownership boundaries, the current protection models for Artificial Intelligence Generated Content (AIGC) have many disadvantages. In response to this situation, there are three different protection models worldwide. The United States Copyright Office stipulates that works autonomously generated by artificial intelligence ‘lack’ the element of human creation, and non-human AI cannot create works. To protect and promote investment in the field of artificial intelligence, UK legislation, through Section 9(3) of the CDPA, designates the author of AI-generated works as ‘the person by whom the arrangements necessary for the creation of the work are undertaken.’ China neither simply excludes the work attributes of AI-generated content based on the lack of a natural person subject as the sole reason, nor does it generalize that AIGC should or should not be protected. Instead, it combines specific case circumstances and comprehensively evaluates the degree of originality of AIGC and the contributions of natural persons to AIGC. In China's first AI drawing case, the court determined that the image in question was the result of the plaintiff's design and selection through inputting prompt words and setting parameters, reflecting the plaintiff's intellectual investment and personalized expression, and should be recognized as a work in the sense of copyright law. Despite opposition, the ruling also established the feasibility of the AIGC copyright protection path. The recognition of the work attributes of AIGC will not lead to overprotection that hinders the overall development of the AI industry. Just as with the legislation and regulation of AI by various countries, there is a need for a balance between protection and development. For example, the provisional agreement reached on the EU AI Act, based on a risk classification approach, seeks a dynamic balance between copyright protection and the development of the AI industry.

Keywords: generative artificial intelligence, originality, works, copyright

Procedia PDF Downloads 46

Authors: Rimma Dzhusupova, Jan Bosch, Helena Holmström Olsson

Abstract:

Artificial Intelligence (AI) in the Engineering, Procurement, and Construction (EPC) industry has not yet a proven track record in large-scale projects. Since AI solutions for industrial applications became available only recently, deployment experience and lessons learned are still to be built up. Nevertheless, AI has become an attractive technology for organizations looking to automate repetitive tasks to reduce manual work. Meanwhile, the current AI market has started offering various solutions and services. The contribution of this research is that we explore in detail the challenges and obstacles faced in developing and deploying AI in a large-scale project in the EPC industry based on real-life use cases performed in an EPC company. Those identified challenges are not linked to a specific technology or a company's know-how and, therefore, are universal. The findings in this paper aim to provide feedback to academia to reduce the gap between research and practice experience. They also help reveal the hidden stones when implementing AI solutions in the industry.

Keywords: artificial intelligence, machine learning, deep learning, innovation, engineering, procurement and construction industry, AI in the EPC industry

Procedia PDF Downloads 119

Authors: Mohamad Mahdi Namdari

Abstract:

In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

Procedia PDF Downloads 45

Authors: Shaima Almalhan, Lubna Shukri, Miriam Talal, Safaa Teskieh

Abstract:

Since artificial intelligence is a rapidly evolving topic that has had a significant impact on technical growth and innovation, this paper examines people's awareness, use, and engagement with the Google Translate application. To see how familiar aware users are with the app and its features, quantitative and qualitative research was conducted. The findings revealed that consumers have a high level of confidence in the application and how far people they benefit from this sort of innovation and how convenient it makes communication.

Keywords: artificial intelligence, google translate, speech recognition, language translation, camera translation, speech to text, text to speech

Procedia PDF Downloads 155

Authors: Harsh Sadawarti, Kamal Malik

Abstract:

Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

Procedia PDF Downloads 112

Authors: Gianni Jacucci

Abstract:

Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial intelligence methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while straight AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability

Procedia PDF Downloads 42

Authors: Rafat Alwazna

Abstract:

Technical lexicon is witnessing a large upsurge in the use of new terminologies whose emergence is an inevitable result of the spread of high-quality technology, the existence of scientific paradigms and the fast growth of research in different disciplines. One important subfield of terminology is legal terminology, which forms a crucial part of legal studies, and whose translation from one legal system into another is deemed a formidable and arduous task that needs to be properly performed by legal translators. Indeed, the issue of untranslatability of legal terms, particularly between originally unrelated languages, like legal Arabic and legal English, has long been a real challenge in legal translation. It stems from the conceptual incongruency between legal terms of different legal languages, which are derived from different legal cultures and legal systems. Such conceptual asymmetry is owing to the fact that law has no universal reference and that legal language is what determines the degree of difference in conceptual correspondence. The present paper argues that although conceptual asymmetry, which is the main reason for the issue of untranslatability of legal terms, cannot be denied in legal translation, there exist certain translation techniques which, if properly adopted, would resolve the issue of untranslatability of legal terms and therefore achieve acceptable legal translation. Hence, the question of untranslatability of legal terms should no longer exist within the context of legal translation.

Keywords: conceptual incongruency, Legal terms, translation techniques, untranslatability

Procedia PDF Downloads 200

Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira

Abstract:

This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.

Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision

Procedia PDF Downloads 157

Authors: Rafaella Nogaroli

Abstract:

It is presented hypothetical cases in the context of AI algorithms to support clinical decisions, in order to discuss the importance of doctors to respect AI ethical principles. Regarding the principle of transparency and explanation, there is an impact on the new model of patient consent and on the understanding of qualified information. Besides, the human control of technology (AI as a tool) should guide the physician's activity; otherwise, he breaks the patient's legitimate expectation in a specific result, with the consequent transformation of the medical obligation nature.

Keywords: medical law, artificial intelligence, ethical principles, patient´s informed consent, medical obligations

Procedia PDF Downloads 102

Authors: Sandesh Achar

Abstract:

Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

Procedia PDF Downloads 110

Authors: Xiaoyu Sun

Abstract:

In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

Procedia PDF Downloads 168

Authors: Ebere Ellison Obisike, Justina N. Adalikwu-Obisike

Abstract:

Artificial intelligence (AI) is progressively transforming health and social care. With the rapid invention of various electronic devices, machine learning, and computing systems, the use of AI istraversing many health and social care practices. In this systematic review of journal and grey literature, this study explores how the applications of AI might promote the prevention of micro and macrovascular complications in type 1 diabetic patients. This review focuses on the use of a digitized blood glucose meter and the application of insulin pumps for the effective management of type 1 diabetes in low and middle-income countries. It is projected that the applications of AI may assist individuals with type 1 diabetes to monitor and control their blood glucose level and prevent the early onset of micro and macrovascular complications.

Keywords: artificial intelligence, blood glucose meter, insulin pump, low and middle-income countries, micro and macrovascular complications, type 1 diabetes

Procedia PDF Downloads 199

Authors: Gertrude I. Hewapathirana, Loi A. Nguyen, Mohammed M. Mostafa

Abstract:

Artificial intelligence (AI) technologies and tools are swiftly integrating into many functions of all organizations as a competitive drive to enhance innovations, productivity, efficiency, faster and precise decision making to keep up with rapid changes in the global business arena. Despite increasing research on AI technologies in production, manufacturing, and information management, AI in human resource disciplines is still lagging. Though a few research studies on HR informatics, recruitment, and HRM in general, how to integrate AI in other HR functional disciplines (e.g., compensation, training, mentoring and coaching, employee motivation) is rarely researched. Many inconsistencies of research hinder developing up-to-date knowledge on AI in HR disciplines. Therefore, exploring eight research questions, using bibliometric network analysis combined with a meta-analysis of published research literature. The authors attempt to generate knowledge on the role of AI in improving the efficiency of HR functional disciplines. To advance the knowledge for the benefit of researchers, academics, policymakers, and practitioners, the study highlights the types of AI innovations and outcomes, trends, gaps, themes and topics, fast-moving disciplines, key players, and future directions.AI in HR informatics in high tech firms is the dominant theme in many research publications. While there is increasing attention from researchers and practitioners, there are many gaps between the promise, potential, and real AI applications in HR disciplines. A higher knowledge gap raised many unanswered questions regarding legal, ethical, and morale aspects of AI in HR disciplines as well as the potential contributions of AI in HR disciplines that may guide future research directions. Though the study provides the most current knowledge, it is limited to peer-reviewed empirical, theoretical, and conceptual research publications stored in the WoS database. The implications for theory, practice, and future research are discussed.

Keywords: artificial intelligence, human resources, bibliometric analysis, research directions

Procedia PDF Downloads 98

Authors: Wendy de Gomez

Abstract:

Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

Procedia PDF Downloads 89

Authors: Zahra Hamedani

Abstract:

Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

Procedia PDF Downloads 411

Authors: Najah Kalifah Almazmomi

Abstract:

In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

Procedia PDF Downloads 39

Authors: Mohammed Nasser Al-Suqri

Abstract:

Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

Procedia PDF Downloads 116

Authors: Camila Penido Gomes

Abstract:

Over the past decade, an emerging body of research has been pointing to artificial intelligence´s great potential to improve the use of open data, increase transparency and curb corruption in the public sector. Nonetheless, studies on this subject are scant and usually lack evidence to validate AI-based technologies´ effectiveness in addressing corruption, especially in developing countries. Aiming to fill this void in the literature, this paper sets out to examine how AI has been deployed by civil society to improve the use of open data and prevent congresspeople from misusing public resources in Brazil. Building on the current debates and carrying out a systematic literature review and extensive document analyses, this research reveals that AI should not be deployed as one silver bullet to fight corruption. Instead, this technology is more powerful when adopted by a multidisciplinary team as a civic tool in conjunction with other strategies. This study makes considerable contributions, bringing to the forefront discussion a more accurate understanding of the factors that play a decisive role in the successful implementation of AI-based technologies in anti-corruption efforts.

Keywords: artificial intelligence, civil society organization, corruption, open data, transparency

Procedia PDF Downloads 206

Authors: Mitat Uysal, Aynur Uysal

Abstract:

Artificial Intelligence (AI) is fundamentally driven by mathematics, with many of its core algorithms rooted in mathematical principles such as linear algebra, probability theory, calculus, and optimization techniques. This paper explores the deep connection between AI and mathematics, highlighting the role of mathematical concepts in key AI techniques like machine learning, neural networks, and optimization. To demonstrate this connection, a case study involving the implementation of a neural network using Python is presented. This practical example illustrates the essential role that mathematics plays in training a model and solving real-world problems.

Keywords: AI, mathematics, machine learning, optimization techniques, image processing

Procedia PDF Downloads 18

Authors: Jui-Chen Huang

Abstract:

This research used artificial intelligence method to explore elderly’s opinions on the reuse of telecare, its effect on their service quality, satisfaction and the relationship between customer perceived value and intention to reuse. This study conducted a questionnaire survey on the elderly. A total of 124 valid copies of a questionnaire were obtained. It adopted Backpropagation Network (BPN) to propose an effective and feasible analysis method, which is different from the traditional method. Two third of the total samples (82 samples) were taken as the training data, and the one third of the samples (42 samples) were taken as the testing data. The training and testing data RMSE (root mean square error) are 0.022 and 0.009 in the BPN, respectively. As shown, the errors are acceptable. On the other hand, the training and testing data RMSE are 0.100 and 0.099 in the regression model, respectively. In addition, the results showed the service quality has the greatest effects on the intention to reuse, followed by the satisfaction, and perceived value. This result of the Backpropagation Network method is better than the regression analysis. This result can be used as a reference for future research.

Keywords: artificial intelligence, backpropagation network (BPN), elderly, reuse, telecare

Procedia PDF Downloads 213

Authors: Sandip Suman

Abstract:

Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 99

Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

Abstract:

The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

Procedia PDF Downloads 77

Authors: Abdulaziz Fageeh

Abstract:

This study investigates the integration of artificial intelligence (AI) within the landscape of language learning and teaching, exploring its potential benefits and challenges. Employing a mixed-methods approach, the research draws upon a comprehensive literature review, case studies, user reviews, and in-depth interviews with educators and students. Findings demonstrate that AI tools, including language learning apps and writing assistants, can enhance personalization, improve writing skills, and increase accessibility to language learning resources. However, the study also highlights concerns regarding over-reliance on AI, potential accuracy and reliability issues, and ethical implications such as data privacy and potential bias. User and educator perspectives emphasize the importance of balancing AI with traditional teaching methods, fostering critical thinking skills, and addressing potential misuse. The study concludes by underscoring the need for ongoing research and development to ensure responsible AI integration in language learning, focusing on pedagogical strategies, ethical frameworks, and the long-term impact of AI on learning outcomes.

Keywords: artificial intelligence, language learning, education, technology, ethical considerations, user perceptions

Procedia PDF Downloads 18

Authors: Mohammad Talebi

Abstract:

Supply chain administration could be a concern for all the countries within the world, whereas there's no special approach towards supportability. Generally, for one decade, manufactured insights applications in keen supply chains have found a key part. In this paper, applications of artificial intelligence in supply chain management have been clarified, and towards Canadian plans for smart supply chain management (SCM), a few notes have been suggested. A hierarchical framework for smart SCM might provide a great roadmap for decision-makers to find the most appropriate approach toward smart SCM. Within the system of decision-making, all the levels included in the accomplishment of smart SCM are included. In any case, more considerations are got to be paid to available and needed infrastructures.

Keywords: smart SCM, AI, SSCM, procurement

Procedia PDF Downloads 89