The Digitalization Sustainability Matrix: A Participatory Research Tool for Investigating Digitainability
| Autor: | Mahsa Motlagh, Shivam Gupta, Jakob Rhyner |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Process management
digitainability Computer science lcsh:TJ807-830 Geography Planning and Development lcsh:Renewable energy sources Participatory action research 010501 environmental sciences Management Monitoring Policy and Law participatory tools digitalization 01 natural sciences Matrix (mathematics) 0502 economics and business SDG indicators lcsh:Environmental sciences SDGs SDG 4 0105 earth and related environmental sciences lcsh:GE1-350 Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants 05 social sciences artificial intelligence SDG 13 lcsh:TD194-195 Sustainability 050203 business & management |
| Zdroj: | Sustainability Volume 12 Issue 21 Sustainability, Vol 12, Iss 9283, p 9283 (2020) |
| ISSN: | 2071-1050 |
| Popis: | Rapidly increasing applications of Digitalization and Artificial Intelligence (D& AI) are already impacting our day-to-day life substantially, along with social and economic prospects worldwide. The accelerating utilization of D& AI has stirred the discussion concerning the responsible application of technologies for assisting the implementation of the Sustainable Development Goals (SDGs). D& AI can raise productivity, lower costs, reduce resource intensity, and enable efficient public services. However, there are also risks and downsides that we all must identify and tackle to address any potential short-/long-term undesired impact. Notably, there exists a gap in knowledge about the mutual relationships between D& AI and the 17 SDGs. To address this gap and gather broader perspectives of experts on the potential uses and pitfalls of D& AI for SDGs and their respective indicators, we propose a participatory research approach: the Digitalization&ndash Sustainability Matrix (DSM). The DSM serves as a means for collaborative methods, such as participatory action research (PAR), for the knowledge production process. We exercised the DSM in the Digitainable Thinkathon event, a gathering of experts from diverse sectors and backgrounds for capturing the action-oriented dialogues concerning the use of D& AI technologies for the indicators of SDGs 4 (Education) and 13 (Climate Action). As a tool, the DSM aided in the discussion by systematically capturing transdisciplinary knowledge generated on several aspects, such as: (1) the need for research&ndash practice nexus action (2) data-capturing efforts and social considerations (3) collaborative planning for utilizing the power of D& AI (4) lessons from the diverse community to encourage the purposeful use of technologies. Overall, the proposed approach effectively triggered a discussion on the crucial aspects that need to be considered for D& AI&rsquo s practices, a step towards deep-rooting the transdisciplinary perspectives for meaningful use of D& AI for SDGs. |
| Databáze: | OpenAIRE |
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