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Using information and communication technology advances to leverage the search of the World new balance with less resources -Part 4-

Victor Greu

Romanian Distribution Committee Magazine, 2023, vol. 14, issue 4, 14-26

Abstract: The paper analyses the context of the sustainable development of information and communication technology (ICT), for supporting the Information Society (IS) on the way towards the Knowledge Based Society (KBS) and facing the unprecedented World challenges (like climate changes, Earth resources fading, geopolitical crises, social unbalances and so on). At Earth scale, ICT power of connecting people must have a huge role for leveraging and harmonizing the humankind efforts, in order to refine knowledge all over the World with proper content and speed, versus the above context challenges. Analyzing some relevant examples of ICT trends/results led to concrete elements and even complementary issues for the above context premises. Recalling that semiconductors industry is one of the highest energy consumers on Earth, because of the involved long thermal processes and also of their products global proliferation, in the general context of ICT carbon footprint which exceeds all planes flights, referring to 2016 Paris Agreement on global warming [19], the issue must be updated with new requirements, according to the newest standards and international targets (International Energy Agency’s Net-Zero Emissions by 2050 Scenario) as by [1]. Another analysis (a deeper approach) pointed the recent advances in the new field named carbon-aware computing (CAC) by [2] and led to the necessity of “frameworking†the complex associated activities/processes of CAC, a difficult way of research, including new approaches/models/algorithms or even change paradigms. All these could mean that the role of ICT in IS/KBS remains prominent, but the World sustainable progress requires refining knowledge at Earth ecosystem scale, with harmonized and continuous updated efforts. We further approached some concrete ways to analyze the contextual mechanisms where relevant information could be generated and then transformed in updated useful knowledge and eventually leading to the expected actions and results. The critical issues for refining knowledge could be generated by using the proper data and the associated processes as inputs for the ICT mentioned advances, as the analysis of the relevant field of organizations productivity from [4] proved, but requiring a comprehensive approach, including some actual data needs, where the management ones are paramount and must reflect data-as-a-product, which needs a much wider base for optimization factors, including humans (data consumers) at the end of the line. We concluded that, now, any improvement/solution should include a more comprehensive/holistic approach, which inherently will consider in model/equation more complicate and changing “actors†/factors, but unfortunately more of them contain more uncertainty – a crucial feature of actuality and future. Analysing and eventually mitigating (part of) uncertainty, including ICT advances help, where AI has an increasing role, it is also approached in [5], where the known problems of uncertainty are transferred at the level of AI/ML, but, for facing ML concrete limitations, a principle solution for the AI/ML model confidence improvement is to add reference data in order to calibrate the uncertainty, as, in a deeper domain/approach (a deeper learning), we have to choose/identify those added reference data, among the alternate or closed probabilities of events (contingencies). Finally, finding the most probable scenarios/events, in every ICT/AI/ML application case or system, is not only a complex problem of modelling, but, since the human nature and human decisions are largely implied, we consider that harmonizing and synchronizing all relevant data/actions is paramount for the best results at Earth scale and we have to notice the importance of every little step on such long and winding road, which could be reached by timely analyses and combining ICT/AI with human intelligence/values.

Keywords: net-zero carbon emissions; carbon-aware computing; data-as-a-product; data transformation; calibrated uncertainty; artificial intelligence; machine learning; refining knowledge (search for similar items in EconPapers)
JEL-codes: L63 L86 M15 O31 O33 (search for similar items in EconPapers)
Date: 2023
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