Generative AI (Gen AI) will mark a paradigm shift from static, one-directional governance to a dynamic, interactive and inclusive model. This transformation, while monumental, doesn’t come without its set of challenges, requiring holistic strategies, robust infrastructural support and a commitment to ethical considerations.
This report explores the transformative potential of Gen AI as a force multiplier for digital governance, making governments more accessible, transparent and efficient. It features insightful interviews with Naim Yazbeck, General Manager at Microsoft, and H.E. Matar Al Hemeiri, Chief Executive at Digital Dubai, around Gen AI’s journey in the UAE and the region.
Highlights
Generative adversarial networks (GANs)
GANs involve a novel approach where two neural networks—the generator and the discriminator—work in tandem.
Variational autoencoders (VAEs)
VAEs take a more statistical approach to generate new data, particularly useful in healthcare for predictive modeling or designing new materials.
Creating rich, detailed, data-informed scenarios, offering the ability to simulate policy outcomes, urban development plans, economic forecasts, or even potential security threats before actual implementation.
Crafting customized content that resonates with diverse citizen groups, ranging from public health advisories during crises, to educational content, to tax-related communications.
Generating synthetic data that augments existing datasets, enabling more robust analytics and insight.
Automating complex decision-making processes by predicting outcomes based on vast datasets.
Ethical and legal challenges include data privacy, ethical considerations and the need for regulatory agility.
Technological challenges encompass resource allocation, skill gaps and the black box nature of AI systems.
Socioeconomic challenges involve building public trust in AI, addressing global disparities in AI adoption and ensuring economic resilience through AI.
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