AI literacy and deepening thinking

This collection examines the transformative impact of AI and GenAI on knowledge work, research, and education, revealing both opportunities and challenges. Core themes include productivity gains (12-40% improvements in consultant performance), capability expansion beyond current skill levels, and the emergence of new human-AI collaboration patterns ('Centaurs' vs 'Cyborgs'). However, the collection highlights critical tensions: AI struggles with tasks outside its capabilities (19% lower correctness), creates new digital divides particularly affecting marginalized communities, and threatens research integrity through authorship ambiguity and potential fabrication. The literacy gap emerges as crucial—fear (52% nervous) rivals excitement (54%) about AI, with underrepresented groups facing disproportionate barriers. The collection suggests AI literacy isn't just technical knowledge but encompasses ethical considerations, responsible use, and an 'engineering mindset' for effective supervision. Strategic implications: Organizations must balance productivity gains against over-reliance risks, while educational systems need comprehensive frameworks (like AILit's 22 competences) to prepare workers and learners. The research automation tools (SPARK) demonstrate AI's potential to transform systematic review processes, yet underscore the need for human oversight in maintaining scholarly integrity.