Mel Goodale: seminario

Humans can extract visual information from faces to estimate a person’s age. Cues from wrinkling, pigmentation, hair color and facial structure all contribute to these estimates. Yet, human accuracy in age evaluations is imprecise, limited by the observer’s perceptual resolution, top-down influences, and by genetic and environmental factors that cause people’s faces to age differently. I will briefly review the kinds of errors that we typically make when estimating someone’s age and the potential sources of those errors, including facial expression. In addition, I will show how the biases and accuracy of our estimates of someone’s age change as a function of their age. Finally, I will compare the performance of human observers with the performance of several popular Artificial Intelligence (AI) programs that have been developed to estimate people’s age from photos of their faces.