In this thesis, I argue that many identification intuitions, such as one that helps you identify the authorship of a painting you are seeing for the first time, fall under the class of experience-based intuitions. Such identification intuitions cannot arise without intuition generating systems (IGSs) that are shaped by experiences accumulated during one's life. On my view, experience-based intuitions are produced by domain-general learning systems of hierarchical abstraction which may be modeled by deep convolutional neural networks. Owing to the mechanism of such IGSs, the reliability of experience-based intuition X depends on the quality of the experiences underlying the IGS which produces X. Lastly, I suggest that insofar as some philosophical thought experiments elicit experience-based identification intuitions, we can use the case method to glean information about our experiences as well as uncover certain conceptual commitments.