Menu

Home / Events / Ethics of Big Data Workshop

Ethics of Big Data Workshop

Friday, 10 June 2016, 10.00am to 6.00pm
Location: SG2, Alison Richard Building, Cambridge

Purpose of workshop

The workshop will support an interdisciplinary conversation at the University of Cambridge about the ethics of big data research. Its aims are both to raise awareness of ethical issues associated with big data and to contribute to the development of material for the Research Group’s digital reader - a publicly accessible, interactive online resource on the ethics of big data research.

 

The Ethics of Big Data Research Group will present the conclusions drawn from their work in the 2015-16 academic year, reflecting on the challenges of ethical practice in big data research and drawing on case studies from research using administrative data, social media data, health data and data from development projects in Africa previously explored in the seminar series. In addition, we welcome a range of expert speakers to provide their perspectives on the Ethics of Big Data.

  

Keynote speaker:

Jake Metcalf, PhD, Data and Society Institute and Founding Partner, Ethical Resolve

Jacob Metcalf, PhD is a Researcher at the Data & Society Research Institute, where he conducted policy and ethics research for the Council for Big Data, Ethics and Society. His research focuses on the changing norms and policies of research ethics in data science and practice. His most recent paper, co-authored with Kate Crawford, "Where are the human subjects in big data? The emerging ethics divide," is in the spring 2016 issue of Big Data & Society. He also runs a consulting firm, Ethical Resolve, dedicated to helping data and tech companies develop ethics review practices. 

 

Panel discussion: How do we engage people with thinking ethically about big data?

 

Panelists

Bendert Zevenbergen, Oxford Internet Institute

Ben Zevenbergen joined the Oxford Internet Institute to pursue a DPhil on the intersection of privacy law, technology, social science, and the Internet. He runs a side project that aims to establish ethics guidelines for Internet research, as well as working in multidisciplinary teams such as the EU funded Network of Excellence in Internet Science. He has worked on legal, political and policy aspects of the information society for several years. Most recently he was a policy advisor to an MEP in the European Parliament, working on Europe’s Digital Agenda. Previously Ben worked as an ICT/IP lawyer and policy consultant in the Netherlands. Ben holds a degree in law, specialising in Information Law.

 

Madeleine Greenhalgh, Cabinet Office

Madeleine Greenhalgh will present a perspective from government, including the UK Government’s Data Science Ethical Framework.

 

Panel respondent: Dr Julia Powles, University of Cambridge

Julia Powles is a postdoctoral researcher working at the interface of law and technology. She has expertise in data protection, privacy, intellectual property, internet governance, regulation and business law, and her current research addresses technical and legal mechanisms for the control, transfer and analysis of data. She obtained her PhD from the Faculty of Law, University of Cambridge.

 

For questions about the workshop content or programme, please contact Clare Dyer-Smith (coordinator@bigdata.cam.ac.uk). 

More information about this event…

Forthcoming talks

Achieving Consistent Low Latency for Wireless Real-Time Communications with the Shortest Control Loop

Thursday, 18 August 2022, 4.00pm to 5.00pm
Speaker: Zili Meng, Tsinghua Unversity
Venue: FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMTnppckJtNWhFVTBKK0REZz09

Real-time communication (RTC) applications like video conferencing or cloud gaming require consistent low latency to provide a seamless interactive experience. However, wireless networks including WiFi and cellular, albeit providing a satisfactory median latency, drastically degrade at the tail due to frequent and substantial wireless bandwidth fluctuations. We observe that the control loop for the sending rate of RTC applications is inflated when congestion happens at the wireless access point (AP), resulting in untimely rate adaption to wireless dynamics. Existing solutions, however, suffer from the inflated control loop and fail to quickly adapt to bandwidth fluctuations. In this paper, we propose Zhuge, a pure wireless AP based solution that reduces the control loop of RTC applications by separating congestion feedback from congested queues. We design a Fortune Teller to precisely estimate per-packet wireless latency upon its arrival at the wireless AP. To make Zhuge deployable at scale, we also design a Feedback Updater that translates the estimated latency to comprehensible feedback messages for various protocols and immediately delivers them back to senders for rate adaption. Trace-driven and real-world evaluation shows that Zhuge reduces the ratio of large tail latency and RTC performance degradation by 17% to 95%.

Speaker Bio: Zili is a 3rd-year PhD student in Tsinghua University. His current research interest focuses on real-time video communications. He has published several papers in SIGCOMM / NSDI and received the Microsoft Research Asia PhD Fellowship, Gold Medal of SIGCOMM 2018 Student Research Competition, and two best paper awards.

BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"

Monday, 22 August 2022, 4.30pm to 5.30pm
Speaker: David Balding, Honorary Professor of Statistical Genetics at UCL Genetics Institute and University of Melbourne
Venue: Seminar Rooms 1 & 2, School of Clinical Medicine, Hills Road, Cambridge CB2 0SP

Although simultaneous analysis of genome-wide SNPs has been popular for over a decade, the problems posed by more SNPs than study participants (more parameters than data points), and correlations among the SNPs, have not been adequately overcome so that almost all published genome-wide analyses are suboptimal. While there has been much attention paid to the shape of prior distributions for SNP effect sizes, we argue that this attention is misplaced. We focus on what we call the "heritability model": a low-dimensional model for the expected heritability at each SNP, which is key to both individual-data and summary-statistic analyses. The 1-df uniform heritability model has been implicitly adopted in a wide range of analyses. Replacing it with better heritability models, using predictors based on allele frequency, linkage disequilibrium and functional annotations, leads to substantial improvements in estimates of heritability and selection parameters over traits, and over genome regions, as well as improvements in gene-based association testing and prediction. Key collaborators Doug Speed, Aarhus, Denmark and Melbourne PhD student Anubhav Kaphle.

Statistics Clinic Summer 2022 III

Wednesday, 31 August 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

If you would like to participate, please fill in the following "form":https://forms.gle/b1UzrTNBig7hkr1e7. The deadline for signing up for a session is 12pm on Monday the 29th of August. Subject to availability of members of the Statistics Clinic team, we will confirm your in-person or remote appointment.

This event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.

Statistics Clinic Summer 2022 IV

Wednesday, 21 September 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

Abstract not available

Title to be confirmed

Monday, 26 September 2022, 3.00pm to 4.00pm
Speaker: Christopher Yau, University of Manchester
Venue: CRUK CI Lecture Theatre

Abstract not available