Phillip Hintikka Kieval

I am a PhD student in the Department of History and Philosophy of Science at the University of Cambridge where I am generously funded by the Gates Cambridge Scholarship.

In addition to my PhD, I also serve as a Student Fellow at the Leverhulme Centre for the Future of Intelligence.

I work on the history and philosophy of machine learning and applied statistics in science and public life. My dissertation develops a pragmatist epistemology of deep learning in scientific practice. I emphasize the theoretical foundations of statistical learning as a source of pragmatic understanding, which involves empirically tested methods of engineering models that facilitate reliable prediction and control. This approach leads me to consider conceptual issues with prominent validation methods, including cross-validation, calibration, and uncertainty estimation, contrasting these contemporary practices with parallels in the history of scientific instruments.

I also have other projects in the philosophy of cognitive neuroscience, artificial intelligence, general philosophy of science, general epistemology, and social-political philosophy, especially where these areas intersect with aspects of machine learning.

Before Cambridge I was a student at the University of Houston where I earned my BA and MA in Philosophy.

I share my life with my brilliant wife and our two cats Winston and Lumi.