A joint initiative of CIFAR and Mila, the AI Insights for Policymakers Program connects decision-makers with leading AI researchers through office hours and policy feasibility testing. The next session will be held on October 9 and 10.
Mila’s AI for Climate Studio aims to bridge the gap between technology and impact to unlock the potential of AI in tackling the climate crisis rapidly and on a massive scale.
Hugo Larochelle appointed Scientific Director of Mila
An adjunct professor at the Université de Montréal and former head of Google's AI lab in Montréal, Hugo Larochelle is a pioneer in deep learning and one of Canada’s most respected researchers.
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Large language models require consistent behavioral patterns for safe deployment, yet their personality-like traits remain poorly understood… (see more). We present PERSIST (PERsonality Stability in Synthetic Text), a comprehensive evaluation framework testing 25+ open-source models (1B-671B parameters) across 500,000+ responses. Using traditional (BFI-44, SD3) and novel LLM-adapted personality instruments, we systematically vary question order, paraphrasing, personas, and reasoning modes. Our findings challenge fundamental deployment assumptions: (1) Even 400B+ models exhibit substantial response variability (SD>0.4); (2) Minor prompt reordering alone shifts personality measurements by up to 20%; (3) Interventions expected to stabilize behavior, such as chain-of-thought reasoning, detailed personas instruction, inclusion of conversation history, can paradoxically increase variability; (4) LLM-adapted instruments show equal instability to human-centric versions, confirming architectural rather than translational limitations. This persistent instability across scales and mitigation strategies suggests current LLMs lack the foundations for genuine behavioral consistency. For safety-critical applications requiring predictable behavior, these findings indicate that personality-based alignment strategies may be fundamentally inadequate.