Responsible Data Science
Tackling the “big issues” requires scientists to more fully embrace the importance of interdisciplinary ecosystems. while the term “interdisciplinarity” is a foundational concept in many institutions to achieve whatever is meant by “responsible” data science, the actual practice of interdisciplinarity is difficult.
This project brings together diverse voices from disparate disciplines like computer science and cultural studies to revive basic definitions and practices of interdisciplinarity, to surface the logistics and struggles of what it means and requires in everyday practice.
We sponsor a series of seminars in 2022 to bring seasoned scholars together with Early Career Researchers to share practices across these levels. Each seminar is unique, but builds from the core premise that today’s “big issues” demand more attention to interdisciplinarity and that everyone benefits when research ecosystems integrate multiple perspectives, even when this is challenging and time consuming.
The outcome of the series will be a best practice guide.
March 31, 2022: Starting the conversation: Core values and challenges for ethical approaches to automation in society, featuring Jenny Zhang and Jey Han Lau
July 19, 2022: Bringing more diverse voices to the concepts of data, science, knowledge, and interdisciplinarity, featuring Winnie Soon and Ane Kathrine Gammelby
September 13, 2022: Logics (Reconciling different systems for inquiry to build better frameworks for collaboration), featuring Jill Walker Rettberg (University of Bergen) and Rob Kitchin (Maynooth University)
October 11, 2022: Layered Frameworks (combining efforts and models without losing discipline-specific definitions and traditions)
November 15, 2022: Large and Small Scales (Focusing on issues and topics of critical global importance from bottom up as well as top down and data driven approaches, combining rather than privileging only certain scales)
December 6, 2022: Wrap-up: An agenda for value propositions and practical guides for interdisciplinary and responsible data science
DERC is co-sponsoring this series on “Interdisciplinary Data Science” with University of Cambridge’s Minderoo Centre for Technology and Democracy
July 5, 2022
anything we call "interdisciplinarity" will include diverse ways of knowing, which means bring many voices to projects, from the outset.
April 22, 2022
Interdisciplinarity: it’s a common enough word in academic settings. It’s a goal in many institutions to blend approaches, to utilize different worldviews effectively in addressing the big issues. Interdisciplinarity is a normative concept; one that strives to value the space between disciplines or moving beyond strict disciplinary thinking in order to conduct research. There have...
March 25, 2022
DERC 2022 co-sponsors a series on "Responsible Data Science" with University of Cambridge's Minderoo Centre on Technology and Democracy