The standard popular framing of human facial recognition treats it as a problem so complex that large brains and specialised neural regions are required to solve it. The human fusiform face area, a section of the temporal lobe that activates specifically when a person looks at a face, has been studied for decades as the neural basis for this ability. The framing is plausible. It is also, by a 2005 finding that has been replicated and extended in the years since, not quite right. Honeybees, with brains roughly one millimetre across containing about a million neurons, can be trained to recognise individual human faces. The result was published in the Journal of Experimental Biology by Adrian Dyer, then at Johannes Gutenberg University in Mainz and the University of Cambridge, working with Christa Neumeyer of Mainz and Lars Chittka of Queen Mary, University of London. According to the team’s 2005 paper, individual bees trained on photographs from a standard human psychology test could discriminate a target face from a similar distractor face with greater than 80 percent accuracy, and could continue to recognise the trained face two days after training. The bees had never previously been exposed to human faces in any evolutionary or developmental sense. They learned the task because Dyer’s team offered them sugar water for getting it right. How the experiment worked The methodology took advantage of the bees’ famously robust associative learning capabilities. Bees are accomplished pattern learners; they have to be, because the flowers they forage from come in an enormous diversity of shapes and colours, and accurate recognition of rewarding flower types is central to their lives. Dyer reasoned that the same machinery might be applicable to any visual pattern, including one with no evolutionary relevance to the bee at all. The team presented bees