Information and Communications Technology is Merging Data Science and Advanced Artificial Intelligence Towards the Core of Knowledge Based Society, Part 1
Victor Greu
Romanian Distribution Committee Magazine, 2021, vol. 12, issue 1, 15-26
Abstract:
The paper analyses the context of evolution of the Data Science (DS) concept, considering the importance of the mutual relations between the evolution of the technology/economy and generally of the society and the ways this is reflected in the people s minds, as knowledge, which is crucial as information and communication technology (ICT) became the main driving factor of the human society by the complex consequences of ICT services, products and applications when supporting the Information Society (IS) on the way towards the Knowledge Based Society (KBS). In fact, just the actual phase of the mutual relations between the evolution of the society and the knowledge across the individuals became such complex and potentially productive, so we consider it a strategic area for a timely evaluation and optimization, firstly for the obvious reason that the mechanisms behind these relations are building the foundation of the KBS. Although this phase is part of a process with a dynamic evolution in the last decades, the combination of the huge volume of data that are more and more generated on Earth (known as Data Deluge, Big Data etc.), with the naturally higher objectives of KBS, makes knowledge generation and its optimal use a real challenge for ICT specialists (and others too), which led to the DS concept and applications. The analysis started from the remarkable vision of Jim Gray on science evolution (the fourth paradigm: the eScience), just when the World and humankind are experiencing such complex and fast changes in the technology and science domains, facing unprecedented volume and diversity of available data which make difficult to estimate the future and the right strategy to approach it. We think, on the other hand, that, in a complicate circle, ICT has the benefic potential, by continuously improving performances, to solve the complex problems which are associated with extracting information from the Data Deluge at Earth scale and eventually with the generation of knowledge that could be used by ICT too. We also consider that the fundamental and most difficult problem when evaluating these processes remain the content and profile of knowledge, which are time sensitive in a World where ICT exponentially generates changes in every human activity field. This way we consider that solving such complex problems of evaluating knowledge generation and use has to be supported by the most performant ICT advances, where AI is by far the appropriate instrument for data/information high level processing. From these conclusions, the reasons for including DS and advanced AI in the ICT context for supporting the most critical core/part of KBS progress became clear, but this is just the tip of an iceberg we try to timely analyse step by step. The real challenges still begin just from here, because each of these 3 connected areas are very complex and their mutual relations are another complicate issue where knowledge is a common thread, as approaching them could be done only timely following all the impacted processes. We also concluded that evaluating knowledge generation and use is a matter of criteria that is essentially depending on human personality and generally on Earth ecosystem priorities, this way entering a complex circle with economical, social, philosophical and political main points of view. Just observing this (iceberg) circle of complicate interactions, we could understand why in our days it is more and more difficult to extract knowledge and especially to refine knowledge from the huge amount of generated data, if we want to continuously adapt/refine this knowledge to the optimal use and eventual effects for KBS. Based on the fact that ACM (Association of Computing Machinery) recognized Jim Gray s vision on ICT by 1998 ACM Turing Award and in 1999 he expressed the new vision of ICT evolution as Cyberspace is a New World, we considered that, while in the ICT exponential evolution any estimation is time sensitive, it is worth to analyse them by updating the implications of his vision due to the pillars he identified for this evolution. Our opinion is that the essential feature of the ICT amazing evolution, which is manifest lately in each of its steps, is about the necessity to continuously re-invent (redefine) itself and learn from nature s millions of years research and the practical value of Jim Gray s vision goes beyond its concrete pillars and features aimed to support the development of ICT, because it is a sustainable set of ways of thinking about such complex and difficult approach like the ICT amazing evolution. Here we include a systemic way to spread knowledge and the need for it, across all individuals of KBS, beyond the usual approach of considering the ICT specialists, just to contribute and improve at least the interest for the necessary core of knowledge our paper aimed for KBS. In addition, even if some of the goals could become sooner or later obsolete, we have to timely analyse the ICT evolution processes and imagine the best updated milestones, that will be surely better than having nothing ahead just for the reason that the challenges of prediction are overwhelming for such complex and complicate ecosystem at Earth scale. As we are in a spectacular development phase of this DS/AI/ICT/KBS context, its evolution naturally has to be further analysed, along with the appropriate features, consequences and learned lessons provided by ICT for all impact areas of the human activity and Earth ecosystem.
Keywords: fourth paradigm of science; data deluge; big data; knowledge generation; data science; artificial intelligence; cyberspace; telepresence; automatic programmer; knowledge based society; eScience (search for similar items in EconPapers)
JEL-codes: L63 L86 M15 O31 O33 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:rdc:journl:v:12:y:2021:i:1:p:15-26
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