Artificial Intelligence, Big Data, and Cloud Infrastructures: Policy Recommendations for Enhancing Women's Participation in the Tech-Driven Economy

Favour Amarachi Ezeugwa, O. O. Olaniyi, Jennifer Chinelo Ugonnia, Abayomi Shamsudeen Arigbabu, Princess Chimmy Joeaneke
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Abstract

This study investigates the underrepresentation of women in Artificial Intelligence (AI), Big Data, and Cloud Infrastructures, exploring the barriers and challenges they face and assessing the effectiveness of current policies and initiatives to promote gender diversity within the tech industry. Employing quantitative research methods, the study used a survey distributed to 572 female professionals in tech-related roles across various industries, achieving a 67.9% response rate. Multiple regression analysis was utilized to test four main hypotheses concerning barriers to entry and advancement, the inclusivity of educational programs, the impact of diverse teams on innovation and performance, and the effectiveness of gender-inclusive policies. Key findings indicate that the type of organization and specific tech sectors significantly influence the barriers experienced by women. Notably, gender diversity within teams correlates strongly with improved innovation and performance. However, educational and training programs often fail to be sufficiently inclusive, underscoring the need for programs better tailored to women's needs in tech fields. Moreover, the study confirms that implementing gender-inclusive policies substantially increases women's participation in tech roles, especially when these policies are applied long-term. Based on the findings, recommendations are made for adopting comprehensive, inclusive practices at organizational and educational levels, promoting diversity in team composition and leadership, committing long-term to effective policy implementation, and developing supportive networks through mentorship and sponsorship programs. These measures are aimed at reducing gender disparities and enhancing the integration of women into the high-tech economy. The study underscores the critical role that strategic policy-making and organizational change play in fostering an inclusive tech environment that not only addresses gender disparities but also enhances overall industry innovation and performance.
人工智能、大数据和云基础设施:促进妇女参与技术驱动型经济的政策建议
本研究调查了女性在人工智能(AI)、大数据和云计算基础设施领域代表性不足的问题,探讨了她们面临的障碍和挑战,并评估了当前促进科技行业性别多元化的政策和举措的有效性。本研究采用定量研究方法,向 572 名各行业技术相关岗位的女性专业人士发放了调查问卷,回复率达到 67.9%。研究利用多元回归分析法检验了四个主要假设,分别涉及进入和晋升障碍、教育项目的包容性、多元化团队对创新和绩效的影响以及性别包容政策的有效性。主要研究结果表明,组织类型和特定的技术领域对女性遇到的障碍有很大影响。值得注意的是,团队中的性别多元化与创新和绩效的提高密切相关。然而,教育和培训计划往往缺乏足够的包容性,这凸显了科技领域需要更适合女性需求的计划。此外,研究还证实,实施性别包容性政策可以大幅提高女性在科技领域的参与度,尤其是在这些政策长期实施的情况下。根据研究结果,我们提出了以下建议:在组织和教育层面采取全面、包容的做法,促进团队组成和领导层的多元化,长期致力于政策的有效实施,以及通过导师和赞助计划发展支持性网络。这些措施旨在减少性别差异,促进妇女融入高科技经济。这项研究强调了战略性政策制定和组织变革在营造包容性科技环境中的关键作用,这种环境不仅能解决性别差异问题,还能提高整个行业的创新能力和绩效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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