Responsible Data Science at Royal Society Bilateral UK-NL workshop

From 21st to 22nd February the Royal Society and the Royal Netherlands Academy of Arts and Sciences (KNAW) held a UK – Netherlands bilateral international meeting to explore common research interests in the fields of Quantum Physics and Technology, Nanochemistry and Responsible Data Science. UnBias was pleased to participate as part of the Responsible Data Science stream.

The two days featured a full program with three keynote presentation for the combined participants and thirteen talks within each of the three parallel streams. The talks within the Responsible Data Science stream were run in a relaxed workshop atmosphere with lots of discussion throughout each of the presentations. Topics ranged from questions about responsible data collection (privacy, consent, user agency, data reuse/re-purposing); to responsible science practices (reproducibility, statistical methods, data mining vs theory driven); the need for understanding cultural context as part of defining ‘responsible’ in the use of algorithmic systems; a detailed look at ethics review at DeepMind Health; and at the effect of GDPR/privacy regulation on Data Science; the development of an app (IRMA) for providing “distributed, attribute-based authentication technique” that allows people to authenticate their identity for online services without the need to provide a third party mediator with updates about everyone they do online (e.g. not using ‘login using Facebook ID’); a look at the challenges, and a possible solution, to providing explanations for algorithmic ranked recommendation lists; an example of transparency challenges for data supply chains in practical applications (e.g. scientific literature database); conceptual approached to the technology design process aimed at embedding ethical values at the various development levels; and the parasitic filed of “responsible data science” that enlists ethics experts to deflect accountability of practitioners.

Highlights and links to related work can be found on Twitter under #RDSUKNL

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