Research Diversity
Summary
Research diversity in AI is a critical subtopic that examines the breadth and variety of approaches within the field. Recent studies suggest that the rapid adoption of deep learning techniques, particularly by large technology companies, may be leading to a narrowing of AI research trajectories. An analysis of AI research in arXiv reveals that thematic diversity in AI has stagnated in recent years, with private sector research tending to be less diverse but more influential than academic research. There is a notable emphasis on data-intensive and computationally demanding deep learning methods in the private sector, potentially at the expense of other AI approaches, ethical considerations, and applications in sectors like healthcare. This trend raises concerns about the potential limitations on AI’s societal benefits and highlights the need for policy interventions to maintain a diverse research landscape, despite challenges in implementation.