The impact of widely used algorithms of large language models on information retrieval and the associated potential risks

Thesis. The aim of this work is to perform an analysis concerning the subject of arti- ficial intelligence integration and its application in modern knowledge acquisition. The article will be an overview of scientific research and papers to raise a discussion of the ad- vantages and potential hazards associated with the widespread implementation of large language models. Concept. The main part of the article will focus on describing the AI enhanced tools available on the market and common ways of utilising them. This knowledge will be jux- taposed with psychological research on human consciousness in the context of decision- making, creativity, and held beliefs to list potential threads related. Results. The analysis of tools that have recently been enhanced with algorithms un- equivocally indicates the dominance of the sector providing informational and creative support. These tools possess a measurably high level of reliability among the public, re- sulting in a reduced number of verification actions. A review of existing literature and research on human psychology shows a very strong correlation between the influence of previous social authorities on decision-making behaviour and an uncritical approach to information obtained through AI. Studies have shown that access to these tools, without proper controlling actions of results, exposes users to bias, manipulation, or susceptibility to marketing activities. Alternatively, with proper and rational use of these implemented algorithms, humans are able to obtain extraordinarily precise and knowledge-based sup- port in decision-making. Similar polarisations of results have been observed in the con- text of creativity, innovation, and inquisitiveness. Originality. The article addresses topics that relate to the psychological nature of hu- mans in the context of new and expanded AI augmented tools. The results of the explora- tory study clearly indicate that programmes supported by algorithms show potential in terms of both scientific and social development. Unfortunately, they also present many potential dangers for both, which, discussed in the foundation, provide the groundwork for more in-depth research.