Abstract
Taphonomic works aim at discovering how paleontological and archaeofaunal assemblages were formed. They also aim at determining how hominin fossils were preserved or destroyed. Hominins and other mammal carnivores have been co-evolving, at least during the past two million years, and their potential interactions determined the evolution of human behavior. In order to understand all this, taxon-specific carnivore agency must be effectively identified in the fossil record. Until now, taphonomists have been able to determine, to some degree, hominin and carnivore inputs in site formation, and their interactions in the modification of part of those assemblages. However, the inability to determine agency more specifically has hampered the development of taphonomic research, whose methods are virtually identical to those used several decades ago (lagged by a high degree of subjectivity). A call for more objective and agent-specific methods would be a major contribution to the advancement of taphonomic research. Here, we present one of these advances. The use of computer vision (CV) on a large data set of images of tooth marks has enabled the objective discrimination of taxon-specific carnivore agency up to 88% of the testing sample. We highlight the significance of this method in an interdisciplinary interplay between traditional taphonomic-paleontological analysis and artificial intelligence-based computer science. The new questions that can be addressed with this will certainly bring important changes to several ideas on important aspects of the human evolutionary process.