Specifics of Algorithmization in Data Culture

Abstract

Information societies effectively transform existing cultures. New cultures are variously defined, but because of the fact that they are dominated by information, the term “data cultures” seems to be the most relevant name for them. Although, it is possible to create a single global data culture in the future and such predictions prevail in academic and non-academic reflections on this subject, so far in addition to global trends there occur local data cultures, what also dynamizes and enriches both individual and collective identities. As Kazimierz Krzysztofek aptly notes, in this situation: "The greatest contradiction of the civilization of the 21st century is drawn. On the one hand, a continuous imperative: be creative and innovative, on the other hand, an increasing pressure on prediction of people’s behaviour, because unpredictability causes chaos, which cannot be managed". In other words, one of the most important social issues today is to create some order in data culture / cultures (often pictured by columnists and researchers as a "magnetic storm"), to reduce its / their infinite complexity, i.e. simply the algorithmization process. With regard to culture, it is not possible to use unequivocally a mathematical algorithm that is the most precise, or a genetic or hormonal algorithm that functions in nature, because accustoming cultural chaos is always strongly ideologized. The algorithm should be treated as a metaphor used to explain cultural phenomena, especially their developmental tendencies. For the researcher of contemporary societies, it is very important to answer the question: what proportions of structure and network are the most beneficial for the survival of data culture / cultures? This answer also directs reflection on the quality of life of individuals and societies, limiting or promoting individualism and collective intelligence in the era of hyper-digitization. These considerations are limited to the initial characterization and evaluation of the information algorithmization of man. The author of the study refers to the concepts of researchers from different countries, highlighting the specificity of today's algorithmization, among others the model of ambient perception, which facilitates participation in the networked information environment, scope and reach of the big data phenomenon, forms of data visualization, personalization of content, Isotype visual language, network custody, data journalism and others. In conclusion, it is pointed out that the information algorithmization of man is constantly growing, which proves that data management strategies weaken the phenomenon of information overload through the logic of numerical civilization, which limits diversity, seeking to count, record and globalize everything.