Deploying digitalisation and artificial intelligence in sustainable development research

Abstract

Many industrialised countries have benefited from the advent of twenty-first century technologies, especially automation, that have fundamentally changed manufacturing and industrial production processes. The next step in the evolution of automation is the development of artificial intelligence (AI), i.e. intelligence which is demonstrated by machines and systems, which cannot only perform tasks but also work synergistically with humans and nature. Intelligent systems that can see, analyse situations and respond sensitively to real-time cues, from human gestures and facial expressions to pedestrians crossing a busy street, will reshape transportation, precision agriculture, biodiversity conservation, environmental modelling, public health, construction and manufacturing, as well as initiatives designed to promote prosperity on Earth. This paper explores the connections between AI systems and sustainable development (SD) research. By means of a literature review, world survey, and case studies, ways in which AI can support research on SD and, inter alia, contribute to a more sustainable and equitable world, are identified.

Towards symbiotic approaches between universities, sustainable development, and cities

“…The authors, part of the IUSDRP, regularly publish papers using a similar approach [such as Refs. 17 , 31 , 32 ] and the respective journals accept the procedures used. The questionnaire was validated by a group of sustainability experts in the field.…”

“…At the present, the relationship between universities and cities is beyond a knowledge-based economy to face the interdependence with the dimensions of sustainable development, namely social, economic and environmental. Because a distinctive feature of universities is that they foster creativity, innovation, social and intellectual development, and collaboration 17 , 18 , they are able to transfer this more intensively to the environment than to the universities themselves. Thus, the opportunity to develop large-scale solutions transferable to society will result in the dissemination of innovation at a global level, with huge gains to the surrounding communities.…”

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

“…Firstly, ML and DL could help assess the availability of renewable energy resources (e.g., wind and solar irradiation) [167][168][169][170] as well as supporting enhanced planning and monitoring of energy facilities [153,160]. Secondly, it is widely recognized that AI drives resource efficiency gains and enables the flexible matching of supply and demand in real-time through smart grids and microgrids [14,153,163,[171][172][173]. Nevertheless, smart grids can suffer cyber-attacks and are prone to blackouts in the least developed contexts [61].…”

“…However, it needs to be clarified how and to what extent these DIs provide opportunities and where they could lead to challenges limiting the progress of SDGs. This calls for the impact assessment for meeting the SDGs [6], given that AI promises significant opportunities for sustainable development and contributes to all the SDGs within the 2030 Agenda [9][10][11][12][13][14]. This potential gave birth to various initiatives such as the "AI for social good" paradigm [15,16].…”

Living labs in the context of the UN sustainable development goals: state of the art

“…Also, living labs are grounded in sustainability, crossing diverse fields of knowledge and interests. These span innovation, applicable to smart urban environments, through the promotion of intelligent network technologies (Bakıci et al 2013;Leal Filho et al 2022a); explorations of real-time local settings, that nurture best practices in sustainable development (Nevens et al 2013); and assessments of their role in transformative change on how they can optimize socio-material conditions while ensuring agency and allocating resources (Bulkeley et al 2016).…”