Artificial Intelligence

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https://africarxiv.ubuntunet.net/handle/1/1624
When studying Artificial Intelligence (AI), the subject can be divided into several key categories, each addressing different aspects of the field. These categories provide a comprehensive framework for studying AI, allowing researchers, practitioners, and students to explore the field from multiple perspectives, considering both the technical aspects and the broader societal impacts. Here's an overview:

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Browsing Artificial Intelligence by Subject "Artificial Intelligence"

Now showing 1 - 3 of 3
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    Artificial Intelligence: The Game Changer in Scientific Research
    (2024-08-08) Ilegbusi, Paul
    Artificial Intelligence (AI) has revolutionised scientific research by enhancing data analysis, accelerating research processes, and improving accuracy. AI's applications span various fields, including biomedicine, environmental science, physics, and materials science. This paper explores AI's transformative impact on scientific research, highlighting its role, applications, challenges, and future prospects. AI tools, such as Explain Paper, Paper Digest, and Chatdoc, facilitate research by summarizing papers, explaining complex concepts, and assisting with literature reviews. Despite AI's benefits, challenges persist, including data privacy and security concerns, bias, and transparency issues. To address these challenges, the paper emphasizes the need for ethical guidelines, robust security measures, and interpretable AI models. The future of AI in scientific research holds promise, with emerging trends and technologies, interdisciplinary innovations, and collaborative platforms driving progress. The paper concludes by highlighting the importance of addressing AI's challenges to ensure its beneficial impact on science and society.
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    Exploring the Potential of Artificial Intelligence for Supporting Indigenous Language Journalism Pedagogy in Nigeria
    (2023-06-14) Iyinolakan, Olayinka
    The African continent has more than 2100 indigenous languages, but many of them are not well- represented in the media. Artificial intelligence (AI) technology offers an opportunity to digitally incorporate these languages into news media and enable journalism pedagogy that emphasizes their use. However, there is limited research on how to integrate AI into journalism training in Africa, especially for indigenous languages. This study evaluates the benefits and challenges of integrating AI tools into journalism training in Nigeria to promote productivity and inclusion of indigenous communities in media content. Mixed research design via in-depth interviews was used to collect data from journalism schools in Nigeria, semi-structured survey with current journalist and secondary data available via AI tools. The findings suggest that using AI tools in journalism education can improve the quality of journalism and equip journalists with skills needed to succeed in the digital age. However, there is no immediate urgency to integrate native language journalism beyond entry level. A bureaucracy-free dynamic curriculum is needed to train budding journalists and retrain veteran practitioners, with funding for recent tools. Future research should broaden the scope and sample size to produce comprehensive and generalizable results for other AI contexts within and beyond Nigeria.
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    On the Preservation of Africa's Cultural Heritage in the Age of Artificial Intelligence
    (2024-03-08) Mohamed Louadi
    In this paper we delve into the historical evolution of data as a fundamental element in communication and knowledge transmission. The paper traces the stages of knowledge dissemination from oral traditions to the digital era, highlighting the significance of languages and cultural diversity in this progression. It also explores the impact of digital technologies on memory, communication, and cultural preservation, emphasizing the need for promoting a culture of the digital (rather than a digital culture) in Africa and beyond. Additionally, it discusses the challenges and opportunities presented by data biases in AI development, underscoring the importance of creating diverse datasets for equitable representation. We advocate for investing in data as a crucial raw material for fostering digital literacy, economic development, and, above all, cultural preservation in the digital age.