The Ethical and Societal Impacts of Big Science: A Framework for Ethical Big Science

Event Abstract

The objectives of this seminar are to identify the ethical and societal issues that big science brings. The paper defines big data and data analytics, before describing some of the sources of big data.

Ethical issues, such as privacy (and anonymity) and security are looked at, as well as existing legislation and frameworks for ethical analytics, the emergence of the term “data harm” and the impact of big science on the epistemology of knowledge.

Several technological and business cases raising ethical concerns for the big data society are discussed; examples include smart meters (Hive), Care.data and DeepMind.

Finally, the main points are summarised, discussed, and conclusions drawn, leading to the identification of Key Performance Indicators (KPIs) and the proposal of a framework for ethical big science.

Booking

This is an open event; there is no need to book. Please feel free to attend and bring your colleagues, classmates and friends.

Speaker bio

Eur. Ing. Dr. Deryn Graham FHEA, C. Eng, FBCS, CITP, PhD, MSc, MA is a retired Senior Lecturer in the Department of Systems Management and Strategy at the University of Greenwich, United Kingdom (UK), formerly a Visiting Fellow in the School of Computing and Mathematical Sciences at the University of Greenwich and a Reader (Associate Professor) in New Zealand.

Her background is in applied Computer Science and Artificial Intelligence. Eur. Ing. Dr. Graham holds a PhD in Artificial Intelligence from Brunel University, UK, a master’s degree in Computing Science (MSc) and a master’s degree in Education (MA).

She is a European Engineer (Eur. Ing.), a Fellow of both the British Computer Society (FBCS) and the Higher Education Academy (FHEA), a Chartered Engineer (C. Eng.) and a Chartered Information Technology Professional (CITP).

She has held significant grants, including a European FP5 project in Acoustic Emission applied to mechanically loaded Paper (AEP), and has published widely.

Her most recent publications and research interests are in the area of Big Data and Learning. She is currently collaborating as a Data Scientist with Data Analytica.