I am an Associate Professor of Philosophy with a background in computer science and artificial intelligence. My work is highly interdisciplinary, integrating philosophy, psychology, neuroscience, and computer science. I use frameworks from philosophers like Aristotle, Ibn Sina, Locke, Hume, and James to help render complex and opaque machine learning models more intelligible to a wider audience, and to provide research ideas for future engineering discoveries. In turn, this helps illuminate how diverse AI architectures may be used to model cognition in human and animal minds in cognitive psychology and neuroscience. I am currently working on an NSF grant to write a book on this theme.  Additionally, the framework is used to help guide model review in the areas of explainable artificial intelligence, to gauge the trustworthiness of scientific applications of deep learning for data analysis and to combat the ethical dangers of algorithmic discrimination.  In particular, I have drawn attention to the idea of processing artifacts in machine learning, which have implications for scientific and medical applications of AI.