回顾人工智能在主要领域的挑战和可解释人工智能的未来前景:以尼日利亚为例

K. Mohammed, A. Shehu
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引用次数: 0

摘要

人工智能(AI)已广泛应用于能源、卫生、农业、金融等重要领域。然而,人工智能仍然面临着社会、伦理、法律和技术方面的挑战。重要的是要了解这些系统如何做出决策,同时仍然实现和实施人工智能的好处。可解释AI (XAI)是一种用于解释机器如何做出决策的技术。在这篇综述中,我们讨论了人工智能的挑战,并推荐XAI作为解决人工智能局限性的工具,并提出了一种基于人和条件的方法来应对尼日利亚技术面临的挑战。本文采用叙述性回顾的方法,突出了限制尼日利亚在卫生、能源、农业和金融这四个重要部门使用人工智能的问题,并提出了解决人工智能挑战的建议。综述数据来自期刊和研究人员。我们讨论了可解释的人工智能(XAI)作为一种技术,用于解决在主要领域使用人工智能的可信度、偏见、缺乏数据、专业知识和信心等挑战。本文着重于用户、条件和挑战,并建议在构建XAI系统时考虑人和条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A REVIEW OF ARTIFICIAL INTELLIGENCE (AI) CHALLENGES AND FUTURE PROSPECTS OF EXPLAINABLE AI IN MAJOR FIELDS: A CASE STUDY OF NIGERIA
Artificial intelligence (AI) has been used widely in essential fields such as energy, health, agriculture, finance etc. However, Artificial intelligence is still faced with social, ethical, legal, and technological challenges. It is important to know how these systems make their decisions while still achieving and implementing the benefits of AI. Explainable AI (XAI) is a technique that is used to explain how a machine made a decision. In this review, we discuss the challenges of AI and recommend XAI as a tool to solve the limitations of AI and suggest a human and conditions-based approach to challenges faced in the technology in Nigeria. This paper employs a narrative review to highlight problems that are limiting the use of AI in four important sectors of Nigeria: Health, Energy, Agriculture, and Finance, and suggest recommendations to solve the AI challenges. The review data was obtained from journals and researchers.  We discuss Explainable AI (XAI) as a technique for solving challenges like trustworthiness, bias, lack of data, expertise, and confidence in using AI in major sectors. The paper focuses on the users, conditions, and challenges and recommends that humans and conditions be taken into consideration when building XAI systems.
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