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E-Government in Nigeria : Can Generative AI Serve as a Tool for Civic Engagement?

Abdulkareem, Abdulrazaq Kayode (2024) E-Government in Nigeria : Can Generative AI Serve as a Tool for Civic Engagement? PUBLIC GOVERNANCE ADMINISTRATION AND FINANCES LAW REVIEW, 9 (1). ISSN 2498-6275 (nyomtatott); 2786-0736 (online)

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Abstract

This paper examines the potential for using generative artificial intelligence (AI) to boost civic participation in Nigeria’s developing e-government ecosystem. Emerging generative technologies like ChatGPT demonstrate intriguing capabilities to make governance more interactive and engaging through conversational interfaces. Thoughtfully implemented AI tools could increase access and understanding of e-government, particularly for underserved groups. However, risks around bias, privacy, security and capability limitations pose challenges for public sector applications. Additionally, Nigeria’s substantial digital divides and defective trust in government institutions hamper e-government participation currently. This paper analyses opportunities and limitations for applying generative AI to advance civic engagement given Nigeria’s unique socio-cultural context. Findings suggest that while AI holds promise, targeted strategies focused on inclusion, accessibility, education and institutional legitimacy building are critical to realise benefits. Cautious optimism, human-centric design and responsible governance frameworks are needed to employ generative systems successfully. If challenges are addressed, AI could open innovative possibilities for energising civic participation. But further research and controlled pilot applications are required to determine optimal implementation.

Item Type: Article
Uncontrolled Keywords: generative AI, ChatGPT, civil participation, digital literacy, e-government
Subjects: J Political Science / politológia > JS Local government Municipal government / helyi, települési önkormányzat
Depositing User: Andrea Tankó
Date Deposited: 29 Jul 2024 11:13
Last Modified: 29 Jul 2024 11:13
URI: https://real.mtak.hu/id/eprint/201109

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