Can AI help us identify critical safety blind-spots before disaster?
Part 2 interview with Professor Robin Dillon-Merrill who unpacks her 20+ years of research on decision-making under risk, outcome bias, and how organizations misinterpret near misses.
We discuss:
a) why near-miss biases shape human decision-making & how we can build robust systems to counter them catch them
b) why technical experts are uniquely positioned to simulate counterfactuals (what could have happened, but didn’t)
c) how well-intended safety messaging becomes background noise without institutional action
d) how cutting-edge AI & machine learning can triage gigantic incident datasets before catastrophe.
Plus, Robin discusses real-world safety challenges with autonomous vehicles, such as Waymo vehicles illegally passing school buses in Texas.
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#ai #workplacesafety #autonomousvehicles #safetyscience
