Advancing a Comprehensive Understanding of AI-Related Risk: From Individual Studies to Collective Insights

Paper 3 identifies substantial growth in AI privacy-protection research alongside geographical concentration, technically dominant research trajectories, and comparatively underdeveloped human-centred, ethical and legal dimensions. Paper 6 identifies divergence between policy-aligned language and executed action in LLM-based agents, while Paper 7 identifies a gap between stated risk awareness and applied risk judgement.

Comparison across the portfolio further identifies recurring patterns concerning surface indicators, blind spots in risk assessment, the multidimensional character of AI-related risk, and the different analytical levels represented across the studies.</p><p dir="ltr">The cross-portfolio synthesis organises these findings through two complementary perspectives: a Meta–Macro–Meso–Micro analytical structure and a comprehensive conceptualisation comprising five interconnected risk domains.

These perspectives are organisational and descriptive syntheses grounded in the domains examined in the portfolio. They provide an analytical reference for considering AI-related risk across different levels, contexts, and dimensions, while their applicability to additional domains requires further validation and may require extension or revision. Together, the portfolio provides a comprehensive but bounded synthesis of AI-related risk across the domains examined. </p><p><br></p>