The Future of Artificial Intelligence: Advancing Diversity and Equity in Society
Keywords:
Artificial Intelligence, Diversity, Equity, Algorithmic Bias, Organizational Leadership, Cultural Heritage Preservation, Language Revitalization, Inclusive Technology, Digital Ethics, Technological Innovation, Social ImpactAbstract
Artificial Intelligence (AI) has emerged as a transformative technology with significant potential to benefit society across various sectors. However, to fully realize this potential, AI systems must reflect the diversity of the populations they serve. This research paper explores the critical intersection of AI and diversity, equity, and inclusion (DEI), arguing that a proactive and inclusive approach is essential for harnessing AI's benefits while mitigating inherent risks. The study emphasizes that neglecting diversity in AI design can perpetuate existing inequalities through biased algorithms and discriminatory outcomes. Through a systematic literature review of 117 articles from the Scopus database, this research identifies key themes related to AI's impact on DEI within organizational culture. The findings demonstrate that AI can serve as a powerful tool for advancing DEI initiatives by identifying and addressing algorithmic biases, promoting inclusive decision-making processes, and providing personalized opportunities for marginalized groups. Notably, Ermolova et al. (2024) highlight AI's role in preserving linguistic diversity, particularly for endangered languages, where AI-powered tools enable community-driven language revitalization and cultural heritage preservation. The research reveals that diverse leadership teams foster innovation and enhanced decision-making (Eroğlu & Kaya, 2022; Lu et al., 2015), while effective leadership remains crucial for successful AI integration (Fosch-Villaronga et al., 2022). The paper concludes that while AI holds significant promise for advancing DEI goals, careful development and implementation are essential to ensure equitable outcomes and prevent the reinforcement of existing biases.
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