Abstract
The study seeks to explore the key opportunities and risks associated with the use of AI-based applications in research conducted by Ukrainian universities.
Findings reveal that the use of AI-based applications among Ukrainian university academic staff is limited. However, we identified certain patterns in how respondents perceive the key opportunities and risks in using AI-based applications in research. These perceptions are largely shaped by expert opinions from mass and social media, as well as scientific literature discussing AI's influence on research. In contrast, respondents' personal experience with AI-based applications plays a lesser role in shaping their views. However, there are notable differences in the experiences of using AI-based applications across various fields of expertise.
Among the most significant opportunities identified by respondents are the ability of AI-based applications to automate routine tasks, gather information from numerous sources, and accelerate the processing of large datasets. However, expectations regarding AI-based applications’ potential to enhance research quality, offer unconventional insights, or detect anomalies and patterns are more limited. Respondents also showed little belief in AI-based applications’ capacity to streamline the research process, improve scientific writing quality, boost research efficiency, or develop new skills for researchers.
Alongside these opportunities, respondents pointed to substantial risks, such as the unreliability of published research findings, compromised research integrity, the unethical use of AI-based applications in generating reviews by dishonest reviewers, and the need for more thorough peer review processes. Concerns also included a potential decline in research quality and an increase in plagiarism cases. However, respondents did not express major concerns regarding ethical issues like data privacy, ghost authorship, or dishonesty and irresponsibility in the use of AI systems.
The results underscore the importance of implementing institutional policies and enhancing the skills of academic staff in using AI-based applications to improve research quality.
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