Desafíos actuales de la Inteligencia Artificial

206 Desafíos actuales de la Inteligencia Artificial Structural effects of AI encompass long-term shifts in job markets due to automation, chang- es in societal norms and behaviors influenced by AI-driven personalization, and significant environmental impacts from sustained computational demands. By integrating these sustainability dimensions and temporal levels of impact, the SusAD provides a comprehensive framework for assessing and visualizing the sustainability impacts of AI technologies. This holistic approach ensures that stakeholders can anticipate and man- age the diverse and evolving effects of AI in a balanced and informed manner. 3.2.Example of SusAD Application To demonstrate the practical use of the SusAD, we present a case study on the imple- mentation of an AI-driven urban traffic management system. This example shows how the SusAD can visualize and manage the sustainability impacts of AI technologies throughout their lifecycle. Urban traffic congestion is a major issue in many cities, causing longer travel times, high- er fuel consumption, and increased greenhouse gas emissions. To address these problems, city planners propose an AI-driven traffic management system aimed at optimizing traffic flow, reducing congestion, and minimizing environmental impact. SusAD is employed to evaluate the necessity and suitability of the AI system for urban traffic management. This initial phase involves workshops with a diverse group of stakehold- ers, including city planners, environmental scientists, local business owners, and residents. The SusAD framework facilitates a thorough exploration of the AI system’s potential impacts across five sustainability dimensions.