• Data for Policy 2019
  • CFP Topics
  • Committee Members
  • Summaries from report

Data for policy 2019

4th International Conference
Data for Policy 2019:
Digital Trust and Personal Data
11-12 June 2019, London

Data science technologies, pioneered in the private sector, are now ripe for transforming the public sector. However, both government policy and technology providers need to address two pressing public concerns: DIGITAL TRUST (privacy and security) and PERSONAL DATA (ownership and beneficial exploitation).

The impact from ‘smartification’ of public infrastructure and services will be far more significant in comparison to any other sector given the government’s function and importance to every individual and institution. Potential applications range from public engagement through natural text and speech Chatbots, to providing decision support for civil servants via AI-based Robo-advisors, to real-time management of the public infrastructure through the Internet of Things and blockchain, to securing public records using distributed ledgers, and, encoding and codifying laws using smart contracts. However, in many cases current uses of automated decision-making systems have been shown to cause adverse impacts on important life events of individuals – examples range from bias in recruitment of job-applicants, to credit scoring in loans and insurance, and to sentencing of criminals. Also, state surveillance and manipulation of voter behaviour have become the early examples of how such developments may amplify the asymmetry of power (between citizen and those utilising such technologies) causing severe damage to the democratic processes. The Bitcoin ‘hype’, with its correlating energy usage, has also shown the environmental cost of the highly complex computations, as well as indicating other potential unpredicted and unintended consequences. On the other hand, the cost of not using – or the slow uptake of – data science technologies in the public sector is also potentially huge, given that all other aspects of our lives are changing fast under the ongoing digital revolution. It then follows that the stakes could be much higher in both the use and the avoidance of these technologies for public decision making and service delivery. This will require a careful cost/benefit analysis before implementation at scale.

The fourth conference in the Data for Policy series therefore highlights ‘Digital Trust and Personal Data’ as its main theme. The conference will also welcome contributions in the broader data science for government and policy discussions. In particular, submissions around the value and harm of using data in the public sector, deployment experience in government, ‘digital ethics’ and ‘ethics engineering’ concepts, personal data sharing frameworks and technologies, transparency in machine learning processes, analytics at source, and secure data transaction methodologies are encouraged.

Topics invited include but are not limited to the following:

  • Data, Government and Policy: Digital era governance and democracy, data and politics, asymmetry of power, data- and evidence-driven public service delivery, algorithmic government and regulation, open-source and open-data movements, multinational companies and privatization of public services, sharing economy and peer-to-peer services, online communities, crowdsourcing, citizen science, public opinion, data literacy, policy laboratories, case studies and best practices.

  • Technologies: Artificial Intelligence, Big Data, blockchain distributed ledger and smart contract technologies, behavioural and predictive analytics, the Internet of Things, platforms, Global Positioning Systems (GPS), biometric identifiers, augmented and virtual reality, robotics, and other relevant technologies.

  • Systems & Infrastructure: Data collection, capture, storage, processing and visualisation technologies; platforms and web services, mobile applications, meta-data, standards and interoperability, databases and data warehousing, high performance computing, algorithms, programming, decision support systems, user-interaction technologies, and other relevant topics.

  • Data Processing & Knowledge Generation:Data representation and pre-processing, integration, real-time and historical data analysis, mathematical and statistical models, ‘data-driven’ analysis, human-in-the-loop (HITL); mixed methodologies, secondary data analysis, web mining; Randomised Controlled Trials (RCTs), gaps in theory and practice, other relevant topics.

  • Policy for Data & Management: Data governance and regulatory frameworks; General Data Protection Regulation (GDPR); data collection, storage, curation and access; data security, ownership, linkage; data provenance and expiration; private/public sector/non-profit collaboration and partnership;capacity-building and knowledge sharing within government; institutional forms and regulatory tools for data governance.

  • Privacy, Security, Ethics & Law: Ethical concerns around data, algorithms, and interactions (both human-machine and machine-machine interactions) and associated technology responses; legal status of digital systems; bias, transparency and accountability of digital systems; public rights, free speech, dialogue and trust.

When

11 - 12 June, 2019

Where

UCL, London, UK

CFP Topics

Topics invited include but are not limited to the following:

Data, Government and Policy: Digital era governance and democracy, data and politics, asymmetry of power, data- and evidence-driven public service delivery, algorithmic government and regulation, open-source and open-data movements, multinational companies and privatization of public services, sharing economy and peer-to-peer services, online communities, crowdsourcing, citizen science, public opinion, data literacy, policy laboratories, case studies and best practices.

Technologies: Artificial Intelligence, Big Data, blockchain distributed ledger and smart contract technologies, behavioural and predictive analytics, the Internet of Things, platforms, Global Positioning Systems (GPS), biometric identifiers, augmented and virtual reality, robotics, and other relevant technologies.

Systems & Infrastructure: Data collection, capture, storage, processing and visualisation technologies; platforms and web services, mobile applications, meta-data, standards and interoperability, databases and data warehousing, high performance computing, algorithms, programming, decision support systems, user-interaction technologies, and other relevant topics.

Data Processing & Knowledge Generation:Data representation and pre-processing, integration, real-time and historical data analysis, mathematical and statistical models, ‘data-driven’ analysis, human-in-the-loop (HITL); mixed methodologies, secondary data analysis, web mining; Randomised Controlled Trials (RCTs), gaps in theory and practice, other relevant topics.

Policy for Data & Management: Data governance and regulatory frameworks; General Data Protection Regulation (GDPR); data collection, storage, curation and access; data security, ownership, linkage; data provenance and expiration; private/public sector/non-profit collaboration and partnership; capacity-building and knowledge sharing within government; institutional forms and regulatory tools for data governance.

Privacy, Security, Ethics & Law: Ethical concerns around data, algorithms, and interactions (both human-machine and machine-machine interactions) and associated technology responses; legal status of digital systems; bias, transparency and accountability of digital systems; public rights, free speech, dialogue and trust.

Committee Members

International Organisation Committee:  

Emanuele Baldacci – European Commission  
Jon Crowcroft – University of Cambridge, Alan Turing Institute  
Zeynep Engin – University College London  
Innar Liiv – Tallinn University of Technology, Estonia  
Stefaan Verhulst – New York University  
Barbara Ubaldi – OECD, Paris   

Special Track Chairs:  

Anil Bharath – Imperial College London 
 
Bilal Gokpinar – University College London  
Catherine Mulligan – World Economic Forum, UN Digital Cooperation  
Tom Smith– ONS Data Science Campus   

Advisory Committee:  

Niall Adams– Imperial College London  
Leigh Anderson – University of Washington
Jean Bacon – University of Cambridge  
Kenneth Benoit – London School of Economics and Political Science  
Gabrielle Demange – Paris School of Economics  
Anthony Finkelstein – UK Government Office for Science  
Rayid Ghani – University of Chicago  
David Hand – Winton Capital Management; Imperial College  
Helen Margetts – University of Oxford; The Alan Turing Institute  
Beth Noveck – New York University  
Alan Penn – University College London  
Rob Procter – University of Warwick; The Alan Turing Institute  
Peter Smith – University of Southampton  
Tom Smith – Office for National Statistics, UK  
John Shawe-Taylor – University College London  
John Taysom – Privitar  
Philip Treleaven– University College London  
Sir David Wallace – University of Cambridge  
Dame Alison Wolf – King’s College London  
Derek Wyatt – Royal Trinity Hospice; All Party Parliamentary Group on Data Analytics 
Milan Vojnovic– London School of Economics and Political Science   

Programme Committee:  

Thomas Baar – University of Leiden  
David Bounie – Telecom ParisTech  
Daniel Castro – Centre for Data Innovation  
Suleyman Demirsoy – Intel  
Yves-Alexandre de Montjoye – Imperial College London  
Seth Flaxman – Imperial College London  
Jasmine Grimsley – Office for National Statistics, UK  
Jose Manuel Magallanes – University of Washington; Pontificia Universidad Catolica del Peru 
Scott Matthews – Carnegie Mellon University  
Eric T. Meyer – The University of Texas at Austin, University of Oxford  
Slava Mikhaylov – University of Essex  
Suzy Moat – University of Warwick; The Alan Turing Institute  
Mirco Musolesi – University College London; The Alan Turing Institute  
Martijn Poel – Ministry of Education, Culture and Science, the Netherlands  
Tobias Preis – University of Warwick; The Alan Turing Institute  
Ralph Schroder – University of Oxford  
Jatinder Singh – University of Cambridge  
Akin Unver – Kadir Has University  
Michael Veale – University College London  
Diana Vlad-Calcic – European Commission  
Andrew Young – New York University  
Louisa Zanoun – UK Science and Innovation Network   

UCL Local Committee:  

Lauro Bovo – Innovation & Enterprise  
Graca Carvalho – Strategic Alliances  
Sarah Chaytor – Office of the UCL Vice-Provost (Research)  
Louise Chisholm – E-research Domain  
George Dibb – Industrial Strategy & Policy Engagement  
Siobhan Morris – Global Challenges for Justice and Equality  
Olivia Stevenson – UCL Public Policy 

Summaries from Report

11 – 12 June, London 

The 2019 conference was held at UCL, highlighting “Digital Trust and Personal Data” as its central theme, capturing growing worldwide concerns and interest in the topic following the EU’s introduction of the General Data Protection Regulation – GDPR (Engin, 2018) (Page, et al., 2019) (Calzada, et al., 2019) (Jay, et al., 2019) (Jacobs, et al., 2019) (Giorgia, 2019) (Sander, 2019) (Lopez, et al., 2019) (Carr, et al., 2019) (Stalla-Bourdillon, et al., 2019) (Thornton, et al., 2019) (Janssen, et al., 2019) (Mureddu, 2019). It brought up issues emerging from the automation of decision-making processes with direct impact on human lives (for example, recruitment, criminal sentencing, loans and insurance), as well from the mass surveillance, and manipulation of voter behaviour.  The hype around Bitcoin at the time was a harbinger of the potential environmental cost of such highly advanced computational processes (de Vries, 2018). There was also a proactive effort to balance these concerns with the potential cost of not using,or the slow uptake of,data science technologies in the public sector.  The Data for Policy 2019 conference also hosted the launch of a new peer-reviewed open-access publication venue – the Data & Policy journal published in collaboration with Cambridge University Press (CUP). The journal became the second major activity stream for the Data for Policy community, providing a dedicated platform to collect and store cutting-edge research and cross-sector thinking shaping the field, as well as facilitating new forms of engagement with different stakeholders involved in this community. The 2019 edition of the conference hosted 231 registered delegates overall. 

Keynote Speakers 

Margot James MP UK State Minister for Digital & the Creative Industries 

Christoph Luetge, Technical University of Munich 

Jon Crowcroft, University of Cambridge; Alan Turing Institute  

Plenary Speakers 

Christopher Holmes, UK House of Lords 

Aaron Maniam, Government of Singapore 

Laura Rodríguez Mendaro, Government of Uruguay 

Junseok Hwang, Seoul National University 

Diego Kuonen, University of Geneva 

Julia Stoyanovich, New York University 

Nicholas Wright, UCL; Georgetown University  

Natasha McCarthy, The Royal Society, UK 

Lee Rowley MP, All Party Parliamentary Group on Data Analytics, UK 

Partners 

University College London & GovTech Lab 

Cambridge University Press 

Office for National Statistics 

University of Cambridge 

New York University –The Government Laboratory (GovLab) 

UK Science and Innovation Network  

The Alan Turing Institute 

Imperial College London  

University of Oxford -Oxford Internet Institute  

The London School of Economics and Political Science  

European Commission  

All Party Parliamentary Group on Data Analytics, UK Parliament 

The Royal Statistical Society