Travis Greene
After giving up on academic philosophy’s armchair theorising, I hopped around from San Francisco, to Bangkok, and then finally ended up in Taipei, to work as an English lecturer at a university. Fatefully, I met a statistics professor in my Chinese class who encouraged me to join her MBA program, and try my hand at data science. Teaching English just wasn’t cutting it anymore; I quit my job and never looked back. After finishing the MBA, I realised that I needed a deeper understanding of the theory behind the mathematical techniques used in data science. I also became disillusioned by the hype behind data science. As more human behavioral big data are used to train and evaluate predictive algorithms, data science now resembles social science in many ways. Worryingly, most data scientists have little to no training in human subjects research ethics. Resolved to put my philosophy degrees to good use, my PhD studies focuses on ensuring that data science is used to promote -- not impede -- human flourishing. Questions currently occupying my waking states of consciousness are: What is the relationship between persons, personal data, and personalisation? What perspectives can philosophy and the humanities bring to data science? Is data science really science, and if so, to what extent do ethical and economic influences shape and constrain it?

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Data Protection

Saving Our Digital Selves: Personalisation, Habermas & the GDPR

The motto of the 1933 World’s Fair in Chicago triumphantly reads, “Science Finds, Industry Applies, Man Conforms.” Such a motto paints a deterministic picture of science as unreflectively accumulating bits of knowledge, independent of final ends and applications. Science is