Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

Abstract

Digitalization is globally transforming the world with profound implications. It has enormous potential to foster progress toward sustainability. However, in its current form, digitalization also continues to enable and encourage practices with numerous unsustainable impacts affecting our environment, ingraining inequality, and degrading quality of life. There is an urgent need to identify such multifaceted impacts holistically. Impact assessment of digital interventions (DIs) leading to digitalization is important specifically for Sustainable Development Goals(SDGs). Action is required to understand the pursuit of short-term gains toward achieving long-term value-driven sustainable development. We need to understand the impact of DIs on various actors and in diverse contexts. A holistic understanding of the impact it creates will help us align it with visions of sustainable development and identify potential measures to mitigate negative short and long-term impacts. The recently developed Digitainability Assessment Framework (DAF) unveils the impact of DIs with an in-depth context-aware assessment and offers an evidence-based impact profile of SDGs at the indicator level. We performed the impact assessment of diverse technologies using DAF. This paper summarizes the insights from the Digitainable Spring School 2022 on "Sustainability with Digitalization and Artificial Intelligence," one of whose goals was to operationalize the DAF as a tool in the action learning process with diverse professionals in the field of digitalization and sustainability. The DAF guides a holistic context-aware process formulation for a given DI. An evidence-based evaluation within the DAF protocol benchmarks a specific DI’s impact against the SDG indicators framework. The operationalization of the DAF was carried out by looking at four different DIs: smart home technologies (SHT) for energy efficiency, blockchain for food security, artificial intelligence for land use cover and changes (LUCC), and big data for international law. Each of the four studies addresses different DIs for digitainability assessment using different techniques for a diverse group of indicators, demonstrating the potential of the DAF but also outlining the existing data gaps that limit a comprehensive analysis.

The Impact of AI in Sdg Implementation: A Delphi Study

“…Goal 11, anchored in the vision of creating inclusive, safe, resilient, and sustainable cities, showcases a strong consensus on AIʹs monumental role in urban development. Target 11.1 (T1) demonstrates AIʹs potential in urban planning, optimizing spaces for equitable housing solutions [69]. Target 11.2 (T2), on the other hand, highlights AIʹs prowess in traffic management, ensuring fluid traffic flows and reduced emissions.…”

“…Target 11.2 (T2), on the other hand, highlights AIʹs prowess in traffic management, ensuring fluid traffic flows and reduced emissions. Additionally, Target 11.3 (T3) accentuates AIʹs transformative role in disaster management, allowing city planners to institute preemptive measures [69]. Goal 12 champions sustainable consumption and production patterns.…”

“…The consensus among the experts, especially with scores reflecting a strong affirmation of AIʹs transformative essence across several SDGs, underscores its cardinal role in forging a sustainable trajectory. Notably, AIʹs adeptness in areas such as urban design, traffic optimization, and disaster response garnered significant median scores, resonating with scholarly contributions that emphasize technologyʹs pivotal role in sustainable urban progression [69]. Through the Delphi method, more insight has been gained into the complex interplay between AI and the SDGs.…”

Harnessing Artificial Intelligence for Advancing Sustainable Development Goals in South Africa's Higher Education System: A Qualitative Study

“…AI systems are designed to process large amounts of data, recognise patterns, and make decisions based on their analysis. In the education framework, AI technologies aim to augment and personalise learning experiences, streamline administrative tasks, and provide valuable insights to educators and students (Gupta et al, 2023). AI has gained prominence worldwide in education, offering various applications and benefits.…”

“…AI-driven early warning systems can identify students at risk of falling behind or dropping out, enabling timely interventions to support vulnerable populations and reduce educational inequalities (Makala et al, 2021). AI can assist educational institutions in optimising resource allocation, ensuring that funding and support reach underserved schools and communities, thereby decreasing resource-related inequalities (Gupta et al, 2023). By adopting AI technologies while keeping inclusivity as a core principle, South Africa can leverage AI to bridge educational disparities, ensuring every student has an equitable opportunity to access quality education and reducing inequalities as outlined in SDG 10.…”