Ezinwa, Chidiebere Anthony and Agbo, Benedict Obiora and Ozojukwu, Chinenye Goodness (2024) Analysis of Knowledge and Use of Artificial Intelligence Among Bloggers in Enugu State. International Journal of Non-Governmental Organizations (NGOs) and Essays, 8 (1). pp. 1-26. ISSN 2514-9237 (Print), 2514-9245 (online)
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Abstract
This study explored and analyses the knowledge and use of AI among bloggers in Enugu State. One of the major aims of this study is to identify the benefits and limitations of AI for Enugu bloggers. Among the research question is ‘What are the ethical implications of AI for Enugu bloggers? Uses and Gratifications Theory and the Gatekeeping Theory, served as the theoretical framework for this study. This study adopted survey method which gives room for questionnaire & Interview, also simple random sampling technique which allows all members of the population to have equal chance of being included in the study was used. The population of the study is 500 bloggers in Enugu. The sample size was determined using Taro Yamani formula, meanwhile and 222 copies of questionnaire were distributed. This study analysed the response of 200 respondents. A significant majority (92.5%) of respondents believe that AI poses ethical concerns in the field of blogging. The researchers concluded based on the findings that training on AI ethics is crucial to ensure bloggers are well-informed about the ethical implications of AI technology. Thus, it recommended that bloggers should actively seek opportunities to enhance their understanding of AI. This can be achieved through online courses, workshops, and seminars focused on AI and its applications in the field of blogging. Blogging platforms and AI tool providers should explore options to make AI tools more accessible and affordable to bloggers, especially those with limited budgets. They should be mindful of content that may perpetuate biases or stereotypes.
| Item Type: | Article |
|---|---|
| Subjects: | H Social Sciences > H Social Sciences (General) |
| Depositing User: | Professor Mark T. Owen |
| Date Deposited: | 01 May 2024 12:54 |
| Last Modified: | 01 May 2024 12:54 |
| URI: | https://tudr.org/id/eprint/2945 |
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