The urban landscape is undergoing a transformative shift due to the advent of emerging technologies such as artificial intelligence (AI), ubiquitous computing, and augmented reality. This thesis delves into the ramifications of these technologies on the dynamics and structure of public spaces. Central to this investigation is the introduction of a novel conceptual model, termed the “Smart Bubble,” which serves as a scaffold for examining the interplay between these digital innovations and urban environments. Rather than offering an exhaustive solution, this framework seeks to provide a methodology for analysing the potential of these technologies to cultivate environments that are more adaptable and tailored to individual needs. In an effort to demystify the interactions between users and public spaces, this research employs a combination of visual tools and explainable AI mechanisms, including Bayesian networks and reinforcement learning. The goal is to unearth patterns in space usage, enable semantic clustering of users and spaces, and facilitate the dynamic adjustment of spatial features. This emphasis on visual approaches not only aims to enhance the representation and analysis of public spaces but also aspires to foster environments that are inclusive, efficient, and grounded in principles of transparency, accountability, and democratic oversight. A critical examination of the role of AI-powered visual tools in shaping urban policy forms a cornerstone of this thesis. It advocates for a strategic, outcome-focused methodology that prioritises overarching goals over granular regulatory measures. Furthermore, the thesis champions the adoption of open-source and no-code platforms to democratise access to technology and mitigate the risks associated with the technocratic sway of proprietary systems. Nonetheless, it underlines the importance of a nuanced, context-aware approach to the deployment of these technologies, highlighting the ethical considerations that must guide their integration into the fabric of urban life. In summary, this dissertation probes the capacity of cutting-edge technologies to refine the way public spaces are represented, analysed, and experienced. It contends that the integration of such technologies should be judicious, informed by an in-depth assessment of the social, cultural, and political landscape, and eschews the notion of universal solutions. By situating the deployment of digital tools within a broader urban context, the research proposes a balanced and forward-looking perspective on the convergence of technology and urban space, underpinned by the innovative “Smart Bubble” framework.
Il panorama urbano sta subendo un cambiamento a causa dell’avvento di tecnologie emergenti come l’intelligenza artificiale (AI), l’informatica ubiquitaria e la realtà aumentata. Questa tesi approfondisce le ramificazioni di queste tecnologie sulla dinamica e la struttura degli spazi pubblici. Al centro di questa indagine c’è l’introduzione di un nuovo modello concettuale, chiamato “Smart Bubble”, che funge da impalcatura per esaminare l’interazione tra queste innovazioni digitali e gli ambienti urbani. Piuttosto che offrire una soluzione esaustiva, questo modello cerca di fornire una metodologia per analizzare il potenziale di queste tecnologie per coltivare ambienti più adattabili alle esigenze individuali. Nel tentativo di demistificare le interazioni tra utenti e spazi pubblici, questa ricerca utilizza una combinazione di strumenti visivi e meccanismi di intelligenza artificiale spiegabili, comprese le reti Bayesiane e l’apprendimento per rinforzo. L’obiettivo è portare alla luce modelli nell’utilizzo dello spazio, consentire il raggruppamento su base semantica di utenti e spazi e facilitare l’adattamento dinamico delle caratteristiche spaziali. Questa enfasi sugli approcci visivi non mira solo a migliorare la rappresentazione e l’analisi degli spazi pubblici, ma aspira anche a promuovere ambienti inclusivi, efficienti e basati su principi di trasparenza, responsabilità e controllo democratico. Un esame critico del ruolo degli strumenti visivi basati sull’intelligenza artificiale nel modellare la politica urbana costituisce una pietra angolare di questa tesi, che sostiene una metodologia strategica e focalizzata sui risultati che dia priorità agli obiettivi generali rispetto alle misure normative granulari. Inoltre, la tesi sostiene l’adozione di piattaforme open source e senza codice per democratizzare l’accesso alla tecnologia e mitigare i rischi associati all’influenza tecnocratica dei sistemi proprietari. Ciononostante, il lavoro sottolinea l’importanza di un approccio sfumato e consapevole del contesto per l’implementazione di queste tecnologie, evidenziando le considerazioni etiche che devono guidare la loro integrazione nel tessuto della vita urbana. In sintesi, questa tesi indaga la capacità delle tecnologie all’avanguardia di affinare il modo in cui gli spazi pubblici vengono rappresentati, analizzati e vissuti. Sostiene che l’integrazione di tali tecnologie dovrebbe essere attenta, informata da una valutazione approfondita del panorama sociale, culturale e politico, evitando soluzioni universali. Situando l’impiego degli strumenti digitali all’interno di un contesto urbano più ampio, la ricerca propone una prospettiva equilibrata e a lungo termine sulla convergenza tra tecnologia e spazio urbano, sostenuta dall’approccio “Smart Bubble”.
Ubiquitous Artificial Intelligence and the urban public space
Ceccon, Lorenzo
2023/2024
Abstract
The urban landscape is undergoing a transformative shift due to the advent of emerging technologies such as artificial intelligence (AI), ubiquitous computing, and augmented reality. This thesis delves into the ramifications of these technologies on the dynamics and structure of public spaces. Central to this investigation is the introduction of a novel conceptual model, termed the “Smart Bubble,” which serves as a scaffold for examining the interplay between these digital innovations and urban environments. Rather than offering an exhaustive solution, this framework seeks to provide a methodology for analysing the potential of these technologies to cultivate environments that are more adaptable and tailored to individual needs. In an effort to demystify the interactions between users and public spaces, this research employs a combination of visual tools and explainable AI mechanisms, including Bayesian networks and reinforcement learning. The goal is to unearth patterns in space usage, enable semantic clustering of users and spaces, and facilitate the dynamic adjustment of spatial features. This emphasis on visual approaches not only aims to enhance the representation and analysis of public spaces but also aspires to foster environments that are inclusive, efficient, and grounded in principles of transparency, accountability, and democratic oversight. A critical examination of the role of AI-powered visual tools in shaping urban policy forms a cornerstone of this thesis. It advocates for a strategic, outcome-focused methodology that prioritises overarching goals over granular regulatory measures. Furthermore, the thesis champions the adoption of open-source and no-code platforms to democratise access to technology and mitigate the risks associated with the technocratic sway of proprietary systems. Nonetheless, it underlines the importance of a nuanced, context-aware approach to the deployment of these technologies, highlighting the ethical considerations that must guide their integration into the fabric of urban life. In summary, this dissertation probes the capacity of cutting-edge technologies to refine the way public spaces are represented, analysed, and experienced. It contends that the integration of such technologies should be judicious, informed by an in-depth assessment of the social, cultural, and political landscape, and eschews the notion of universal solutions. By situating the deployment of digital tools within a broader urban context, the research proposes a balanced and forward-looking perspective on the convergence of technology and urban space, underpinned by the innovative “Smart Bubble” framework.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/222015