Algorithms of trust in the political and economic development of Central Asia

Research objective. To analyse the relationship between the level of digitalisation, the adoption of artificial intelligence technologies, and the structures of institutional trust in the countries of Central Asia, as well as to analyse their relationship with perceptions of digital technologies and structures of public trust.

Methodology. The methodology includes a comparative analysis of international indices of digital development (E-Government Development Index, Network Readiness Index, Freedom on the Net), data from global surveys on trust in artificial intelligence, national statistics on internet penetration and the use of electronic public services, as well as the results of a comparative survey of respondents in Kazakhstan, Kyrgyzstan, and Uzbekistan.

Scientific novelty and value. Central Asia is examined as a region characterised by asymmetric digital development: Kazakhstan demonstrates high levels of digital transformation, including its inclusion among countries with a very high level of e-government development, while Uzbekistan and Kyrgyzstan remain at stages of catch-up modernisation. The article proposes an analytical model of “hybrid trust” that differentiates among institutional, social, and algorithmic levels of trust. It also introduces the concept of “algorithmic perceptual bias,” reflecting the discrepancy between the objective characteristics of digital systems and the population’s subjective interpretation of their functioning. This approach makes it possible to link macro-level indicators of digitalisation to micro-level effects on perception and political behaviour.

Results. The findings demonstrate that a high level of digital accessibility and active use of electronic services are not accompanied by a proportional increase in trust in algorithmic systems. The observed crosscountry differences identified in the study confirm the presence of a “digital efficienc paradox” and a hybrid configuration of trust in the context of regional digital transformation.

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