Cameron Beebe, Phd Email & Phone Number

Currently, I'm concerned that the widespread proliferation of generative language models may have introduced a systemic confound for philosophical research going forward. In response, I believe philosophers should consider adapting their methodology. For example, by prioritizing synthesis of historical literature, transparently evidencing note taking and writing, submitting human authenticity affidavits, and being wary of generative AI confounds in philosophical research. My current project "Structural Idealism" uses github updates to transparently show the raw formative and creative process, and provides an affidavit that none of the text was generated by a language model. There is a lot of room to innovate on a better methodology and responsible use of new tools for making philosophical progress over the long term.Previously, my Ph.D. focused on knowledge transfer and model-based reasoning, including aspects of machine learning and artificial intelligence. I have some experience with various deep learning tools including Keras, Pytorch, Anaconda, and have experimented with DL models using Slurm on HPC machines.There is significant overlap between the kinds of problems and solutions that data scientists and machine learning researchers work on, and the methods employed by formal philosophers of science. Increasingly, I believe that responsible AI development will need to merge these viewpoints. Previously, I have also worked extensively on problems in the philosophy and foundations of quantum mechanics in my undergraduate and MA research projects, and have maintained an interest in quantum foundations and quantum information theory.My profile on ResearchGate: https://www.researchgate.net/profile/Cameron_BeebeMy GitHub: https://github.com/CameronBeebe

Listed skills include Microsoft Office, Microsoft Excel, Powerpoint, English, and 10 others.