On the Influence of Artificial Intelligence on Human Problem-Solving: Empirical Insights for Wave 1 from a Multinational Longitudinal Pilot Study

The rapid integration of Artificial Intelligence (AI), particularly generative language models, into daily life is fundamentally altering human problem-solving approaches. This pilot study from a multinational longitudinal research program investigates the patterns, perceptions, and consequences of AI use across different task complexities. A survey was administered to a diverse, highly educated sample (N=21), capturing data on demographics, AI usage habits, and ethical perceptions. Crucially, the study employed problem vignettes of graduated complexity to examine actual behavior. Results reveal the emergence of a hybrid problem-solving culture where AI is strategically embedded into workflows, primarily for ideation, formulation, and research. While AI consultation increases with problem difficulty, a critical "verification crisis" emerges as tasks become more complex, participants' self-assessed ability to verify AI output declines sharply, creating a significant gap between their belief in an AI-generated solution's correctness and their ability to prove it. Furthermore, a "belief-performance gap" was identified, where perceived correctness of AI solutions exceeded actual ground-truth accuracy on complex problems. These findings underscore a paradigm shift towards human-AI collaboration and highlight the urgent need for digital literacy frameworks and system designs that prioritize verification skills alongside AI adoption to ensure reliable outcomes.