Knowledge Diversity at Universities?

Artificial Intelligence (AI) is an area of ​​research driven by innovation and development that culminates in computers, machines with human-like intelligence characterized by cognitive ability, learnability, adaptability and decision-making ability. The study found that AI is widely adopted and used in education, especially by educational institutions, in various forms. This article reviewed articles by various scientists from different countries. The paper discusses the prospects for the application of artificial intelligence and machine learning technologies in education and in everyday life. The history of the development of artificial intelligence is described, technologies of machine learning and neural networks are analyzed. An overview of already implemented projects for the use of artificial intelligence is given, a forecast of the most promising, according to the authors, directions for the development of artificial intelligence technologies for the next period is given. This article provides an analysis of how educational research is being transformed into an experimental science. AI is combined with the study of science into new ‘digital laboratories’, in which ownership of data, as well as power and authority in the production of educational knowledge, are redistributed between research complexes of computers and scientific knowledge.

Objective: The purpose of this paper is to conduct a thorough review and investigation on the function and importance of AI in education. The development of technology in the sector, and the emergence of raising interest to apply this AI technologies with a view to enable disruptive efficiencies across all aspects of education. Methodology: The study uses a systematic review of literature for exploring the existing literatures and research findings about AI implementation in Education. For learning it tells you good & bad about AI of bunchy resources, And changes because of the whether educational practices. Results: The results suggest that AI can greatly improve the personalization of learning, being able to provide tailored activities beyond traditional strategies. But the review also highlights worries over inequalities that may arise if only a specialist few can call upon top-notch AI tools possibly deepening of the achievement gap. Furthermore, a sanguine reliance on automated solutions could compromise the core human element in education and stymie social-emotional development for our students. Originality/value: Given the tendency for increased transparency, accountability and potential bias of AI systems in this critical domain leading to possible discrimination practices (e.g. admissions, grading etc) it is felt that the paper has great value contribution. There needs to be a spirit among policymakers, educators and developers working together to ensure that AI in education is implemented following certain principles.

The prowess of neurosurgeons emerges from decades of holistic training centered on technical skills, phasic clinical data collection, decision making, care and recovery. Modern research has opened a discussion regarding a remarkable surge in the importance of artificial intelligence (AI) in neurosurgery and its foundational procedures. AI has proven itself to be an invaluable asset in neurosurgery by complementing the aforementioned expertise of neurosurgeons to provide exceptional patient care throughout the pre-operative, intra-operative and post-operative stages of neurosurgery by enhancing diagnostic and prognostic outcomes in clinical treatment and mitigating the pressures associated with manual decision making taken on by neurosurgeons to improve patient outcomes. AI also contributes to the production, processing and storage of clinical and experimental data and has been observed to decrease risks associated with neuroanaesthesiology. The implementation of AI in neurosurgery can globalize high-quality healthcare with central focus on developing nations and thereby reduce the costs associated with surgical procedures. Additionally, mutualism between AI and neurosurgery can be facilitated, where both fields lead neurosurgeons and AI engineers into further exploration and more complex procedures to possibly re-define traditional methods in AI and neurosurgery and ultimately solve healthcare-related global issues. The aim of this review is to explore the capacity of AI in aspects of neurosurgery and investigate the significance of its contributions with regards to the capabilities of human workers

Implementing a reform in medical education requires students’ awareness regarding the importance of artificial intelligence (AI) in modern medical practice. The objective of this study was to investigate students’ perceptions of AI in medical education. A cross-sectional survey was conducted from June 2021 to November 2021 using an online questionnaire to collect data from medical students in the Faculty of Medicine at Kuwait University, Kuwait. The response rate for the survey was 51%, with a sample size of 352. Most students (349 (99.1%)) agreed that AI would play an important role in healthcare. More than half of the students (213 (60.5%)) understood the basic principles of AI, and (329 (93.4%)) students showed comfort with AI terminology. Many students (329 (83.5%)) believed that learning about AI would benefit their careers, and (289 (82.1%)) believed that medical students should receive AI teaching or training. The study revealed that most students had positive perceptions of AI. Undoubtedly, the role of AI in the future of medicine will be significant, and AI-based medical practice is required. There was a strong consensus that AI will not replace doctors but will drastically transform healthcare practices.

<p>The incorporation of Artificial intelligence into software development is moving rapidly with predictive analytics playing a crucial role in better decision making, maximising resources, and increasing product quality. The use of AI powered predictive analytics, and several phases of the software development life cycle has gained considerable traction. However, there is still a lack of exploration in implementing a comprehensive strategy to its application. This paper provides a thorough investigation of the incorporation of Artificial intelligence (AI) across the whole software development process, including requirement analysis, design, coding, testing and maintenance. Using predictive models, artificial intelligence allows for the anticipation of the changes in requirements, discovery of design fault, detection of code defects, optimization of test coverage, prediction of maintenance needs. This paper discusses the comprehensive integration of AI across the whole project lifetime, leading to improved results by enhancing individual stages and creating synergetic benefits. The proposed solution aims to tackle key challenges such as data quality, model interpretability, and tool integration. These solutions include implementation of explainable AI approaches, adoption and strong governance practices. Concrete examples from real world scenarios showcase the practical advantages of using AI driven predictive analytics. These examples highlight the ability to reduce project timelines, enhance code quality, and raise fault detection rates. The importance of AI in software development is anticipated to increase as it continues to improve, presenting enhanced prospects for innovation and efficiency. This paper offers a roadmap for enterprises aiming to use AI to revolutionise the software development processes and achieve exceptional results.</p>

Importance of AI and DL: The integration of Artificial Intelligence (AI) and Deep Learning (DL) into food safety and freshness monitoring is revolutionizing the food industry by enabling real-time, data-driven quality control. This paper explores key AI applications—including electronic nose systems for meat freshness evaluation, computer vision for defect detection, intelligent packaging with smart sensors, and blockchain, enabled traceability, that enhance food safety while reducing waste. AI-based Solutions and Challenges: AI-driven solutions such as predictive analytics for dynamic shelf-life estimation, hyperspectral imaging for contamination detection, and automated sorting systems demonstrate superior accuracy over traditional methods. However, challenges like sensor reliability, data variability, high implementation costs, and regulatory compliance remain barriers to widespread adoption. Future Trends in Terms of Sustainability: Emerging trends highlight the potential of edge AI, federated learning, and explainable AI (XAI) to improve scalability and consumer trust. The future of food safety lies in smart, interconnected systems that ensure transparency, efficiency, and sustainability across the supply chain. By addressing current limitations, AI and DL can transform food quality management, delivering safer, fresher, and more sustainable food products to global markets. Keywords: Food Safety and Freshness, Artificial Intelligence, Deep Learning, Electronic Nose, Smart Packaging, Predictive Analytics, Intelligent Traceability, Real-Time Monitoring.

Artificial intelligence (AI) in health-care is an emerging trend identified as a collection of technologies, programmed to sense, comprehend, act, and learn. Its performance is appreciated for the administrative and clinical healthcare functions and also for research and training purposes. AI includes natural brainpower, instrument learning, deep learning, neural networks, robotics, multiagent organisms, modernization in healthcare, and indistinct reasoning. Health includes healthcare, diagnostics, sanatoriums, and telemedicine, medications, therapeutic utensils and supplies, health assurance, and medical data. Healthcare curriculums are restricted by the unavailability of clinicians and inadequate dimensions, and AI amends these insufficiencies. The importance of AI in India has become a key technology for improving the effectiveness, value, cost, and reach of healthcare. The ethical issues for applying AI in healthcare must be analyzed and standardized. The encounters to the use of AI in health-care were recognized primarily through an analysis of literature, interviews, and roundtable inputs.

In most recent time, the global landscape of supply chain management has experienced unprecedented challenges during the COVID-19 pandemic, which has significantly impacted the routine and smooth operations of different firms in the United States. This paper explains about the importance of artificial intelligence (AI) and machine learning (ML) in the mitigation of these disruptions and possible ways of improving supply chain security and its efficiency. This research adopted a questionnaire survey involving 281 managers, with the aim to comprehensively examine the current state of AI integration across the U.S. supply chain sector, with focus on some key components like real-time tracking, cost optimization, and risk management. A mixed method approach was adopted for this research, utilizing both inferential and descriptive analyses to unravel insights and trends into the role of AI in enhancing supply chain security. The results indicate that integrating AI, most especially through cost optimization, real-time tracking, and risk management components, emerges as a significant determinant of supply chain security in the United States. Real-time tracking technologies are identified as crucial for monitoring shipments and assets, enabling quick responses to security incidents, and ensuring end-to-end visibility throughout the supply chain. Despite the potential benefits, the study highlights challenges that hinder the widespread integration of AI technologies in the U.S. supply chain. The high cost of AI adoption and the limited availability of skilled personnel are major obstacles. To address these challenges, the paper proposes practical recommendations. Firstly, real-time tracking technologies are recommended to monitor shipments and assets, facilitating rapid responses to security incidents, and ensuring visibility across the entire supply chain. Furthermore, the paper suggests optimizing costs by investing in cost-effective security solutions. This includes leveraging AI for automated monitoring systems and adopting secure packaging measures. These strategies aim to minimize vulnerabilities without compromising security standards, offering a balanced approach to enhancing supply chain security while mitigating the financial implications associated with AI adoption.

PurposeIn India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI’s influence on supply chain risk mitigation (SCRM).Design/methodology/approachThis study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses.FindingsThis study’s findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence.Originality/valueThis study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

PurposeThe purpose of this paper is to provide evidence on the relationship between artificial intelligence (AI) and financial inclusion to achieve sustainable development goals (SDGs), an agenda set by United Nations for 2030. Financial inclusion is an enabler of 8 of the 17 SDGs. This paper emphasizes the introduction of AI in the financial sector, which is indispensable for achieving financial inclusion and plays a crucial role in the achievement of SDGs.Design/methodology/approachThis study adopts qualitative research methodology to highlight the significance of AI in achieving high levels of financial inclusion in an economy. Both narrative and comparative approaches are used to provide empirical evidence for reaching the UN SDGs target through AI-assisted financial inclusion.FindingsAI implementation in finance enables people to take part in the formal financial sector and thus, enhances economic growth and reduces poverty.Research limitations/implicationsThis research is limited in its data. Only five top AI applications are chosen and comparison is made between two countries only. Future research should consider it as an established concept and include more data to strengthen the evidence.Practical implicationsThe results of this paper will help policymakers convince governments and institutions to put their efforts toward AI implementation in financial infrastructure of countries.Originality/valueThis research is unique in providing real-life examples and cases demonstrating the significance of AI implementation in the financial sector. Recent literature lacks evidence on the relationship of AI, financial inclusion and SDGs. This study adds to the existing literature by compiling data on top AI applications and comparing the performance of countries in achieving financial inclusion with the help of AI.

As environmental issues increasingly affect global economies, sustainable entrepreneurship, especially within the green startup context, has gained respect as an essential component of modern business. The importance of artificial intelligence (AI) in developing these businesses cannot be ignored. Artificial intelligence is a powerful game-changer in improving operational efficiency, reducing carbon footprints, optimizing resource utilization, and creating innovative green business ideas. This chapter delves into sustainable entrepreneurship and AI, investigating how artificial intelligence (AI) technologies empower green startups to succeed within a competitive, environmentally-minded market landscape. The insights provided in this chapter and the analysis and scope of what AI can do provide some foundational understanding of how green startups can take advantage of AI to promote sustainability and growth in profitability.

AI presents numerous opportunities for teaching and learning because it has the potential to impart knowledge, stimulate cognition, and support learning. This is profitable for those students who may struggle with social interactions in real life. This chapter carefully analyzed some of the merits and demerits of incorporating artificial intelligence (AI) in teaching and learning and highlighted its significance in inclusive education. Based on the literature some of the benefits of AI are improved performance of abilities, social motivation, and encouragement of students. This chapter also identified some difficulties associated with incorporating AI into inclusive education. They are technological difficulties, poor connectivity, challenges with pedagogical issues, and limitations of databases. The objectives of this chapter are to: provide a clearer and better understanding of artificial intelligence and offer detailed information on the importance of AI and inclusion.

With the growth of cyber threats and security threats in the digital environment, the importance of artificial intelligence in cybersecurity is becoming increasingly apparent. Effective use of machine learning algorithms, automated detection and response to cyberattacks, and addressing ethical issues associated with the use of artificial intelligence in this area are key aspects of modern cybersecurity. This article examines the role and impact of artificial intelligence on cybersecurity, identifies its benefits and challenges, and discusses the ethical aspects of this issue. The implementation of artificial intelligence (AI) systems in medicine is one of the most important modern trends in global healthcare. AI technologies are fundamentally changing the global healthcare system, enabling a radical redesign of medical diagnostics, the development of new drugs, and overall improvement in the quality of healthcare services while reducing costs for medical clinics. Artificial intelligence is a technology aimed at creating machines capable of imitating human intelligence. At the core of AI are neural networks, which model the functioning of the human brain. These networks consist of interconnected nodes (called "neurons") that can learn from large amounts of data, analyze information, and make decisions. This modeling allows AI to perform complex tasks, including image recognition, natural language processing, and many other applications, which are applied in various areas of life, including medicine. Artificial intelligence (AI) is having a significant impact on medicine, improving the work of doctors and the efficiency of clinics. Neural networks are currently actively used to process medical images and assist doctors in making diagnoses and choosing treatment strategies. And the opportunities they offer are extremely promising. Keywords: Information Security; Cyber Threats; Information Security; Data Protection.

As the Industry 4.0 paradigm accelerates, the importance of artificial intelligence (AI) in manufacturing industry is increasing. Manufacturing AI requires balanced capabilities between industry-specific domain knowledge and AI capability. Nevertheless, many manufacturing AI startups are mainly focusing on human capital based on AI or data science capability. This article focused on the importance of human capital based on domain knowledge for the success of manufacturing AI. In this article, the relationship between domain knowledge and corporate performance was analyzed for 127 global manufacturing AI startups. Furthermore, the moderating effects of educational level and cofounder size for domain knowledge were analyzed. In addition, an expanded analysis was conducted on effect between domain knowledge, educational level, cofounder size, and corporate performance by business model. This article has new implications for and provides practical contributions to the human capital strategy for manufacturing AI corporates.

State institutions that provide public services needed by citizens are called 'public administration'. The understanding of public administration has changed over time. This process of change consists of the 'classical public administration approach', the essence of which is centralized bureaucracy, and the 'new public administration approach', the essence of which is that the management approach applied in the private sector can also be applied in public administration. Recently, new management approaches in public administration in developed countries have also attracted attention. The digital age approach is seen as a prominent approach in this sense. It is a known fact that public services provided to citizens are significantly affected by the digital age approach. In this sense, the use of artificial intelligence in terms of increasing quality, effectiveness and productivity while providing public services to citizens comes to the forefront. The focus of the study is to conduct a analysis of the effects of artificial intelligence on public administration. First of all, an extensive literature review was conducted based on books, research theses, articles and expert opinions in the relevant discipline. In this context, the importance of artificial intelligence, which is an important phenomenon of the digital age, in terms of today's public administration understanding, in which areas of public administration it can be effective, the results it will have in public services and examples of artificial intelligence applications in public administration are discussed. As a result of the study, although it is thought that artificial intelligence may create problems in terms of security in the long term, it is also seen that it can provide advantages especially in terms of service quality, productivity and effectiveness increase due to the continuous change in technology in the world. In addition, considering that the developments in the field of artificial intelligence continue rapidly, the necessity of utilizing artificial intelligence in public administrations of all countries following the technology is also seen as a result of the study. The study is expected to contribute to the effective implementation of artificial intelligence applications in the field of public administration by increasing the level of knowledge of the relevant segment