Facial Recognition, CNNs and the Cost of Being Wrong
· 3 min read
Wall's article made me think about facial recognition less as a model-accuracy problem and more as a deployment problem: what happens when an organisation treats a CNN score as objective evidence? A convolutional neural network can return a probability or similarity score, but that score does not, by itself, establish a person’s identity. In a photo app, a wrong match can merely be irritating; but in policing, border control, or military use, it can expose someone to surveillance, exclusion, arrest, or harm (Wall, 2019).