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Approach to global regulations around AI
Get PDFRegulation of artificial intelligence (AI) varies significantly globally, reflecting different approaches and priorities. These trends underscore the need to balance technological innovation with rights protection and security. The purpose of this article is to examine the main trends and challenges in the regulation of AI, with a comprehensive view of how the governments of the European Union, China and the United States address this complex and crucial issue due to their involvement as great government powers. . at the economic and social pyolytic level. The study was based on a bibliographic review whose search was intentional towards publications from journals indexed in electronic databases such as Scopus, Web of Science and Google Scholar. The findings demonstrate that the European Union has established a comprehensive framework with the AI Law, imposing specific restrictions and requiring transparency to establish a global standard similar to the GDPR. China, for its part, is transitioning from a fragmented approach to more unified regulation. The introduction of a holistic AI law and the creation of a national AI office indicate an effort to consolidate its regulatory framework, improving consistency and efficiency in risk management. In the United States, regulation remains gradual and decentralized, with initiatives at both the federal and state levels. Although efforts like the AI Bill of Rights are significant, the lack of a unified framework poses coherence and applicability challenges
IA´ Tools for the development of investigative skills
Get PDFThis article explores how the artificial intelligence (IA) it is transforming the education in natural sciences by means of strategies pedagogic innovators. The IA allows the learning personalization, adjusting the content and the rhythm to the individual necessities of the students, what improves the understanding and retention of complex concepts significantly. Also, the use of simulations and virtual models believe interactive and visual learning environments, enriching the educational experience. These tools also foment the development of critical and creative skills, promoting a more active and collaborative approach in the resolution of scientific problems. On the whole, these strategies not only improve the effectiveness of learning, but rather they also prepare the students to face the challenges of the XXI century with a solid base in science and technology
Artificial Intelligence applied to teaching and learning processes
Get PDFArtificial Intelligence (AI) transforms teaching and learning processes by personalizing educational content according to individual students\u27 needs, thus enhancing their performance and motivation. Tools like SlidesAI and Tome facilitate the creation of efficient educational resources, although the quality and privacy of generated data need to be addressed. AI also enables interactive and immersive learning environments, such as simulations and educational games, that adapt in real-time to students\u27 actions. These environments provide richer and more practical experiences. Additionally, the creation of multilingual videos with avatars enhances accessibility and customization of learning. However, ensuring equitable access to these technologies is crucial to avoid educational inequalities. As demonstrated, AI offers multiple benefits for education but requires careful implementation to maximize its advantages and mitigate potential risks
Hospital processes optimization based on artificial intelligence
Get PDFArtificial intelligence is revolutionizing hospital management by optimizing critical processes to improve operational efficiency. The automation of administrative tasks allows reducing errors and streamlining the flow of patients and work, which translates into lower costs and better use of hospital resources. The objective is to analyze research related to the optimization of hospital processes based on artificial intelligence. The research paradigm was qualitative-quantitative, the focus of this research was based on a bibliometric analysis, which was complemented with a documentary review in databases of high international and Latin American impact in the period from 2010 to 2024. The trend of the research was towards an increase, where research in the area of medicine and computer sciences predominated. A keyword co-occurrence and citation analysis were carried out to identify possible lines of research. It was identified that monitoring and predictive analytics technologies based on artificial intelligence enable proactive management of patients\u27 health, preventing complications and optimizing resource allocation. These tools also facilitate the personalization of care, adjusting treatments according to the specific needs of each patient. The implementation of artificial intelligence in hospital processes is a crucial tool for improving operational efficiency and reducing costs through the automation of administrative tasks, resulting in a smoother and more effective operatio
Trends in research on the implementation of artificial intelligence in supply chain management
Get PDFSupply chains play a critical role in the functioning of the global economy. The integration of information systems and emerging technologies, such as artificial intelligence and the Internet of Things, improves visibility, decision making and responsiveness throughout the supply chain. The objective of the research is to analyze research trends on the implementation of artificial intelligence to supply chain management. The research paradigm was quantitative, based on a descriptive, retrospective and bibliometric study, in the SCOPUS database, during the period from 2019 to 2024, without language restriction. The trend of research was positive and towards increase with a maximum peak in the year 2023 of 214 researches, research articles in the area of computer science predominated. The top producing country was the United Kingdom with 127 research papers and four lines of scientific research were identified around the implementation of artificial intelligence in supply chain management. In the business environment, the ability of supply chains to adapt to change is crucial; their management includes planning and coordination, logistics process management and customer relationship management. The integration of information systems and emerging technologies, such as artificial intelligence, has had a great impact on the improvement of all the processes involved in management
The Role of Mulching in Reducing Greenhouse Gas Emissions and Enhancing Soil Health Among Smallholder Farmers in Zambia, Malawi, Kenya, and Tanzania: An AI-Driven Approach
Get PDFMulching is a widely recognized conservation practice that improves soil moisture retention, enhances fertility, and reduces greenhouse gas (GHG) emissions. This study explores the effectiveness of mulching among smallholder farmers in Zambia, Malawi, Kenya, and Tanzania, focusing on its role in mitigating climate change and improving soil health. Additionally, we integrate artificial intelligence (AI) to optimize mulching practices through predictive analytics and real-time monitoring. AI-powered models, utilizing remote sensing data and machine learning algorithms, assess soil conditions, moisture levels, and carbon sequestration potential. These insights enable precision agriculture techniques, helping farmers make data-driven decisions that maximize mulching benefits while minimizing environmental impact. The study also evaluates AI-driven mobile applications and advisory systems that provide tailored recommendations based on localized climate and soil data. By leveraging AI technology, this research aims to enhance the sustainability of mulching practices, improve productivity, and contribute to climate resilience in smallholder farming systems
Role of Artificial Intelligence in Disseminating Climate Information Services in Africa
Get PDFClimate Information Services (CIS) are critical for enabling communities in Africa to make informed decisions in the face of climate variability and change. However, the dissemination of CIS in Africa faces significant challenges, including limited access to data, inadequate infrastructure, and language and cultural barriers. This paper explores the role of Artificial Intelligence (AI) in enhancing the dissemination of CIS across the continent. AI technologies, including machine learning, natural language processing (NLP), and big data analytics, offer promising solutions to these challenges by improving data collection, processing, and communication. Machine learning algorithms can enhance the accuracy of climate forecasts and provide tailored advisories for agriculture and disaster risk reduction. NLP can bridge the communication gap by translating complex climate data into local languages, making it accessible to rural communities. Big data analytics enables the integration of diverse datasets to generate comprehensive climate models and risk assessments. The paper also presents case studies from sub-Saharan Africa, demonstrating the practical implementation of AI in CIS, such as drought prediction, early warning systems, and agricultural advisories. These case studies highlight the potential of AI to improve the accuracy, timeliness, and relevance of climate information, particularly for vulnerable rural populations. The paper concludes with future directions, emphasizing the need for investment in infrastructure, capacity building, and policy frameworks to support the sustainable integration of AI in CIS. By leveraging AI, Africa can enhance its resilience to climate change and improve the livelihoods of its communities
Analysis of the scientific production on the implementation of artificial intelligence in precision agriculture
Get PDFoai:latia.ageditor.uy:article/1The implementation of artificial intelligence is having a transformative impact on precision agriculture by optimizing agricultural resources and minimizing environmental impact, with a focus on sustainable development. The objective of the research is to analyze the scientific production on the implementation of artificial intelligence in precision agriculture. The research was conducted under the quantitative paradigm, using a descriptive and retrospective approach, and its implementation was carried out through a bibliometric study. It was conducted in SCOPUS database in the period 2014 - 2024 without language restriction. The behavior of the research was positive with a maximum peak of 112 researches where research articles in the area of computer science predominated. The most productive country was India with 79 research papers, while the most productive affiliation with 18 research papers was the University of Florida in the United States. Four lines of research and the periods with the highest number of citations in the subject were identified, where it was evidenced that the greatest boom was from 2019. Precision agriculture is an agricultural management tool that integrates a group of advanced technologies such as global positioning systems, geographic information systems, remote sensors, drones, internet of things and artificial intelligence, with an impact on optimizing agricultural resources and minimizing environmental impact in terms of territorial development and the fulfillment of sustainable development objectives
Artificial Intelligence for the development of qualitative studies
Get PDFThe integration of Artificial Intelligence (AI) is revolutionizing qualitative research by optimizing data collection and analysis. Tools such as machine learning and natural language processing enable the analysis of large volumes of information with precision and speed, facilitating the identification of patterns and trends. The adoption of virtual research methods, such as online focus groups and video interviews, has overcome geographical barriers, enabling the participation of diverse and representative samples, in addition to being more cost-effective and allowing real-time data acquisition. The incorporation of advanced biometric techniques, such as eye tracking, facial expression analysis, and neuroimaging, provides a more holistic and accurate understanding of consumers\u27 emotional and subconscious responses. These innovations allow companies to adapt their marketing strategies and product designs more effectively, enhancing personalization and emotional resonance of the experiences offered. 
Tools for AI-driven Development of Research Competencies
Get PDFArtificial intelligence (AI) tools are transforming scientific research by enabling the analysis of large volumes of data and the generation of new hypotheses and theoretical models. In 2024, there is an expected proliferation of smaller and more efficient AI models that can run on accessible hardware, facilitating the democratization of access to this technology. This will allow academic institutions and small businesses to implement and optimize AI models without the need for expensive infrastructures. The ability of AI to handle and analyze large datasets has been particularly useful in fields such as biomedicine, where it has accelerated the discovery of new treatments and therapies. Furthermore, the integration of AI models into local devices addresses critical concerns regarding data privacy and security, enabling the secure processing of sensitive information. These tools not only enhance the efficiency and accuracy of research but also foster innovation by expanding the frontiers of knowledge in diverse disciplines