David Watson is a doctoral candidate at the Oxford Internet Institute, where his research focuses on the epistemological foundations of machine learning.
David Watson is doctoral candidate at the University of Oxford and an enrichment student at The Alan Turing Institute. He received his MSc from the Oxford Internet Institute in 2015, studying under the supervision of Professor Luciano Floridi. He went on to become a Data Scientist at Queen Mary University’s Centre for Translational Bioinformatics before returning to Oxford for his DPhil in 2017. He is passionate about promoting more interpretable techniques for analysing complex systems in the social and life sciences.
David is a founding member of the Digital Ethics Lab, where his research focuses on the epistemological foundations of machine learning. He develops new methods for explaining the outputs of black box algorithms, with the goal of better understanding causal relationships in high-dimensional systems. In addition to his academic work, David is a regular contributor to The Economist, where he writes articles and builds models for the Graphic Detail and Game Theory blogs.
Machine learning, epistemology, open source software, causal inference
- (2019) Testing Conditional Predictive Independence in Supervised Learning Algorithms.
- (2019) "Oncometabolite induced primary cilia loss in pheochromocytoma", Endocrine-Related Cancer. 26 (1) 165-180.
- (2019) "A Framework for Multi-Omic Prediction of Treatment Response to Biologic Therapy for Psoriasis", Journal of Investigative Dermatology. 139 (1) 100-107.
- (2018) "Sex differences in the nitrate-nitrite-NO• pathway: Role of oral nitrate-reducing bacteria", Free Radical Biology and Medicine. 126 113-121.
- (2018) M3C: A Monte Carlo reference-based consensus clustering algorithm.
- (2018) "Bioinformatics for dermatology – why we should learn about code", British Journal of Dermatology. 178 (4) 984.
- (2018) "The RA-MAP Consortium: a working model for academia–industry collaboration", Nature Reviews Rheumatology. 14 (1) 53-60.
- (2017) "Research Techniques Made Simple: Bioinformatics for Genome-Scale Biology", Journal of Investigative Dermatology. 137 (9) e163-e168.
- (2017) "Signatures of inflammation and impending multiple organ dysfunction in the hyperacute phase of trauma: A prospective cohort study", PLOS Medicine. 14 (7) e1002352.
- (2016) "Crowdsourced science: sociotechnical epistemology in the e-research paradigm", Synthese. 195 (2) 741-764.
Oxford Internet Institute Launches Digital Ethics Lab: Tackles Ethical Challenges Posed by Digital Innovation
17 May 2017
The Oxford Internet Institute has today launched the Digital Ethics Lab (“DELab”), which aims to tackle the ethical challenges posed by digital innovation.