Neurotechnology, neural democratisation and AI safety

A recent paper introduces the "neural democratisation of AI" (Bain & McCay, 2024), suggesting that advanced neurotechnology will increase data and help neuroscientists build better brain models. AI researchers could leverage these insights to create more sample- and energy-efficient, human-like models, lowering the barrier to frontier AI development. However, this democratisation presents economic, regulatory, and geopolitical risks. If a broader range of companies and countries can suddenly develop frontier models, regulation becomes significantly harder, potentially compromising safety. While it is open whether neurotechnology will fundamentally advance AI, emerging approaches already integrate user brain states with multimodal input. For example, EEG wave patterns can improve transformer performance by reweighting attention during token-processing (Short et al., 2026). This lightning talk will outline the hypothesis and its safety implications. Will neural democratisation undermine safety by multiplying regulatory targets, or might brain-inspired AI yield safety gains as Mineault et al. (2025) have suggested? References "The neural democratisation of AI" by M. Bain, A. McCay. AI & Soc 39, 2589–2591 (2024). "Steering Transformer Attention with Human EEG" by C. Short, S. Basart, S. Erisken; Proc. First Workshop on NeuroAI Multimodal Intelligence, PMLR 308:199-204 (2026) “NeuroAI for AI Safety” Preprint https://arxiv.org/abs/2411.18526 (2025), P. Mineault, N Zanichelli, J Z Peng, A Arkhipov, E. Bingham, J Jara-Ettinger, E Mackevicius, A Marblestone, M Mattar, A Payne, S Sanborn, K Schroeder, Z Tavares, A Tolias