This article examines the history of Russian colonization in Kazakhstan, focusing on identity, resistance, and independence within Russia’s neo-imperial ambitions. It addresses the socio-political barriers in postcolonial Kazakhstan due to ties with Russia and explores how the Soviet migration policies shaped Kazakhstan’s demographic and political landscape. The study outlines the phases of Russian colonization, contrasting Russian narratives of a civilizing mission with Kazakh perspectives on exploitation and cultural erasure. Using postcolonial theory, it deconstructs these narratives and reveals power dynamics. Kazakh literature and poetry are analyzed as mediums of resistance, emphasizing the horse as a symbol of cultural identity. The article concludes by discussing the post-Soviet cultural transformations and the role of literature in nation-building, highlighting the importance of reclaiming cultural symbols and myths for understanding Kazakhstan’s colonial history and postcolonial transformation.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.