Data for Policy 2017

Data for Policy 2017 – Government by Algorithm?

6-7 September 2017

Governments are being transformed under the impact of the digital revolution, although the speed of change is behind that of the commercial sector. Policy-makers in all domains are facing increasing pressures to interact with citizens more efficiently, and make better decisions in the light of data flooding in all forms, sophisticated computing technologies, and analytics methods.  The hierarchical structures of governments are also being challenged as these technologies equip individuals and informal networks with the necessary tools to better participate in public decision making processes, and have a societal impact at a much faster pace than ever before.  The concepts and tools from artificial intelligence, machine learning, big data analytics, Internet of Things (IoT), and now blockchain technologies are also likely to automate many services in the public sector, greatly increasing its efficiency but at the cost of potentially millions of jobs. ‘Smartification’ of people, devices, institutions, cities, and governments also brings constant, ubiquitous surveillance which, together with inference and recognition technologies, creates the potential to regulate human behaviour and may even threaten democracy.

Governments are being transformed under the impact of the digital revolution, although the speed of change is behind that of the commercial sector. Policy-makers in all domains are facing increasing pressures to interact with citizens more efficiently, and make better decisions in the light of data flooding in all forms, sophisticated computing technologies, and analytics methods.  The hierarchical structures of governments are also being challenged as these technologies equip individuals and informal networks with the necessary tools to better participate in public decision making processes, and have a societal impact at a much faster pace than ever before.  The concepts and tools from artificial intelligence, machine learning, big data analytics, Internet of Things (IoT), and now blockchain technologies are also likely to automate many services in the public sector, greatly increasing its efficiency but at the cost of potentially millions of jobs. ‘Smartification’ of people, devices, institutions, cities, and governments also brings constant, ubiquitous surveillance which, together with inference and recognition technologies, creates the potential to regulate human behaviour and may even threaten democracy.

The third of the Data for Policy conference series highlights ‘Government by Algorithm?’ as its main theme, while also welcoming contributions from the broader Data Science and Policy discussions. All relevant formats including research and policy presentations, workshops, fringe events and other innovative formats will be considered by the committees.

Topics invited include but are not limited to the following:

  • Government & Policy: Digital era governance and democracy, data-driven service delivery in central and local government, algorithmic governance/regulation, open source and open data movements, sharing economy, digital public, multinational companies (Google, Amazon, Uber, etc.) and privatization of public services, public opinion and participation in democratic processes, data literacy, policy laboratories, case studies and best practices.
  • Policy for Data & Management: Data governance; data collection, storage, curation, and access; distributed databases and data streams, psychology and behaviour of decision; 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.
  • Data Sources: Open, commercial, personal, proprietary sources; administrative data, official statistics, user-generated web content (blogs, wikis, discussion forums, posts, chats, tweets, podcasting, pins, digital images, video, audio files, advertisements, etc.), search engine data, data gathered by connected people and devices (e.g. wearable technology, mobile devices, Internet of Things), tracking data (including GPS/geolocation data, traffic and other transport sensor data, CCTV images etc.,), satellite and aerial imagery, and other relevant data sources.
  • Data Analysis: Computational procedures for data collection, storage, and access; large-scale data processing, real-time and historical data analysis, spatial and temporal analysis, forecasting and nowcasting, dealing with biased/imperfect/missing/uncertain data, human interaction with data, statistical and computational models, networks & clustering, dealing with concept drift and dataset shift, other technical challenges, communicating results, visualisation, and other relevant analysis topics.
  • Methodologies: Qualitative/quantitative/mixed methods, secondary data analysis, web mining, predictive models, randomised controlled trials, sentiment analysis, Blockchain distributed ledger and smart contract technologies, machine learning, Bayesian approaches and graphical models, biologically inspired models, simulation and modeling, small area estimation, correlation & causality based models, gaps in theory and practice, other relevant methods.
  • Policy/Application Domains: Public administration, cities and urban analytics, policing and security, health, economy, finance, taxation, law, science and innovation, energy, environment, social policy areas (education, migration, etc.), humanitarian and development policy, crisis response, public engagement and other relevant domains.
  • Citizen Empowerment: Online platforms and communities, crowdsourcing, citizen science, community driven research, citizen expertise for local & central decision-making, mobile applications, user communities, other relevant topics.
  • Ethics, privacy, security: Data and algorithms in the law; licensing and ownership; using personal or proprietary data; transparency, accountability, participation in data processing; discrimination- and fairness-aware data mining and machine learning; privacy-enhancing technologies (PETs) in the public sector; public rights, free speech, dialogue and trust.

Publications from Data for Policy 2017 Conference:

Allen, James T. (2017, September 4). The long-term effects of inherited wealth on social equality. Zenodo. http://doi.org/10.5281/zenodo.884495 Read more>>

Anderson, C. Leigh, Biscaye, Pierre E., Hayes, Adam L., Klawitter, Marieka M., & Travis, W. Reynolds. (2017, September 4). Public policy and the promise of digital credit for financial inclusion. Zenodo. http://doi.org/10.5281/zenodo.884186 Read more>>

Anderson, C. Leigh, Biscaye, Pierre E., & Reynolds, Travis W. (2017, September 4). National ID Programs: A Multi-Country Review and Analysis of Policy and Practical Challenges. Zenodo. http://doi.org/10.5281/zenodo.884178 Read more>>

Bauhr, Monika, Czibik, Agnes, Fazekas, Mihaly, & de Fine Licht, Jenny. (2017, September 19). Lights on the Shadows of Public Procurement. Zenodo. http://doi.org/10.5281/zenodo.896046 Read more>>

Chang, Marina, Huang, C. H., & Mian, I.S. (2017, September 4). Economic policy, “alternative data” and global agriculture: from the trans-Atlantic slave trade to agroecology Zenodo. http://doi.org/10.5281/zenodo.884503 Read more >>

De Ford, Peter, Cuervo, Javier, Khan, Farooq, & Johnson, Samuel. (2017, September 4). Indicators of humanitarian aid performance using online data: case-study of Afghanistan in 2015. Zenodo. http://doi.org/10.5281/zenodo.884482 Read more>>

Delacroix, Sylvie. (2017, September 21). Pervasive Data Profiling, Moral equality and Civic Responsibility. Zenodo. http://doi.org/10.5281/zenodo.903488 Read more>>

Desai, Tanvi. (2017, September 20). Disseminate Access Not Data. Zenodo. http://doi.org/10.5281/zenodo.897833 Read more>>

Edwards, Liz, Mullagh, Louise, Towe, Ross, Nundloll, Vatsala, Dean, Claire, Dean, Graham, … Blair, Gordon. (2017, September 4). Data-driven decisions for flood risk management. Zenodo. http://doi.org/10.5281/zenodo.884180 Read more>>

Heijlen, Roel, & Crompvoets, Joep. (2017, September 4). Clean data for cleaner air? Case study research about data streams concerning low-emission zones and car-free zones. Zenodo. http://doi.org/10.5281/zenodo.884076 Read more>>

Henman, Paul. (2017, September 4). The computer says ‘DEBT’: Towards a critical sociology of algorithms and algorithmic governance. Zenodo. 10.5281/zenodo.884116 Read more>>

Liccardi, Alexandre, Coudercy, Laurent, Dembski, Samuel, & Mauclerc, Anthony. (2017). An open source strategy for public online algorithms and data services: the French water information system experience. Zenodo. http://doi.org/10.5281/zenodo.1025783 Read More>>

Lowe, Sarah. (2017, September 25). The value of safe settings in evidence based policy making. Zenodo. http://doi.org/10.5281/zenodo.996037 Read more>>

Mateos-Garcia, Juan, Stathoulopoulos, Konstantinos, & Bashir Mohamed, Sahra. (2017). An (increasingly) visible college: Mapping and strengthening research and innovation networks with open data. Zenodo. http://doi.org/10.5281/zenodo.1014743 Read more>>

Mian, I.S, Twisleton, D., & Timm, D. (2017, September 4). What is the resource footprint of a computer science department? Place, People and Pedagogy. Zenodo. http://doi.org/10.5281/zenodo.884492 Read more>>

Myers, Hannah, & Naimpally, Rohit. (2017). Building Momentum for Evidence-Based Policymaking in State and Local Governments. http://doi.org/10.5281/zenodo.1053445 Read more >>

Naryan, Shivangi. (2017, September 4). What ails smart policing in India?. Zenodo. http://doi.org/10.5281/zenodo.884078 Read more>>

Ogbuju, Emeka. (2017, September 4). Towards a Data-driven Smart Governance in Nigeria. Zenodo. http://doi.org/10.5281/zenodo.884103 Read more>>

Peshave, Akshay, Memon, Siraj, Chavan, Vedmurtty, & Oates, Tim. (2017, September 4). Baltimore Housing Prices Disparity for Comparable Neighborhoods: A Case for Enabling Interactive,Visual Exploration of Neighborhoods. Zenodo. http://doi.org/10.5281/zenodo.884488 Read more>>

Phillips, Andelka M., & Mian, I.S. (2017, September 19). Governance and Assessment of Future Spaces: A Discussion of Some Issues Raised by the Possibilities of Human-Machine Mergers. Zenodo. http://doi.org/10.5281/zenodo.896110 Read more>>

Ritchie, Felix. (2017, September 20). ‘The Five Safes’: a framework for planning, designing and evaluating data access solutions. Zenodo. http://doi.org/10.5281/zenodo.897821 Read more>>

Sel, Marc, Diedrich, Henning, Demeester, Sander, & Stieber, Harald. (2017, September 4). How smart contracts can implement “report once”. Zenodo. http://doi.org/10.5281/zenodo.884497 Read more >>

Sluban, Borut, & Battiston, Stefano. (2017, September 15). Policy Co-creation in the Era of Data Science Zenodo. http://doi.org/10.5281/zenodo.892390 Read more >>

Welpton, Richard. (2017, September 20). Research Data Centres: The role of brokers for negotiating access to data. Zenodo. http://doi.org/10.5281/zenodo.897829 Read more>>

Williams, Dawn, Howarth, James, Cheng, Tao, & Blangiardo, Marta. (2017, September 4). Small Area Estimation of Public Confidence. Zenodo. http://doi.org/10.5281/zenodo.884184 Read more>>

Zilberman, Noa. (2017, September 4). Revolutionising Computing Infrastructure For Citizen Empowerment. Zenodo. http://doi.org/10.5281/zenodo.884160 Read more>>

Multimedia from Data for Policy 2017 Conference: 

  

Reflections:

               

 

Partners & Sponsors of Data for Policy 2017 Conference: 

  • University College London – Department of Computer Science and UCL Public Policy
  • University of Cambridge – Computer Laboratory and Centre for Science and Policy (CSaP)
  • UK Government Data Science Partnership – Government Office for Science (GOScience),
  • Office for National Statistics (ONS), and Government Digital Service (GDS)
  • All Party Parliamentary Group on Data Analytics, UK Parliament
  • Imperial College London – Data Science Institute
  • London School of Economics and Political Science – Department of Methodology
  • The Alan Turing Institute – UK National Institute for Data Science
  • The Royal Statistical Society
  • European Commission – Joint Research Centre and Eurostat
  • University of Oxford – Oxford Internet Institute
  • New York University – The Government Laboratory (GovLab) and the Open Governance Research Exchange (OGRX)
  • University of Essex – Institute for Analytics and Data Science
  • Essex County Council
  • UK Administrative Data Research Network (ADRN)
  • Privitar
  • CognitionX

CONFERENCE VENUE

The Data for Policy 2017 Conference is being hosted by the Government Data Science Partnership at the premier 1VS Conference Centre, the venue of choice for all UK government conferences. Accommodating over 250 delegates in twenty conference rooms, 1VS boasts modern audio-visual suites as well as atmospheric controls and in-house catering. 1VS is used throughout the year for conferences hosted by a variety of different government departments including HM Treasury, the Department for Education and the Ministry of Defence. Situated on the venerable thoroughfare of Victoria Street, 1VS is a two-minute walk from the Houses of Parliament, the seat of British political power and a ten minute walk from Buckingham Palace, the residence of Her Majesty Queen Elizabeth II, the longest reigning Queen-regnant in history. A short walk from 1VS the visitor can find Westminster Abbey, the site of all the coronations of English monarchs since William the Conqueror in 1066 and the neo-Byzantine-style Westminster Cathedral, Mother Church of England and Wales. The art lovers, the National Portrait Gallery is a ten minute bus journey away, as is Tate Britain; whilst those who prefer a more rural feel, the beautiful St. James park a five minute walk from the conference centre. In the streets around Westminster numerous cafes, restaurants and bistros are to be found offering a cosmopolitan dining experience, with cuisine from around the world. For the more adventurous, the River Thames flows nearby and on the far bank is the world-famous London Eye, offering breath-taking panoramic views of this city which is at once ancient and thrillingly vibrant.

 

Address: 

BIS Conference Centre,

1 Victoria Street

London

SW1H 0ET

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