[Air-L] CfP: Data for Policy 2017 - Government by Algorithm?, 6-7 September, London

Zeynep Engin ds.engin at gmail.com
Sun Mar 19 10:09:51 PDT 2017


*Call for papers, presentations, sessions, and workshops – Deadline:
8th May*



3rd Annual International Conference



*DATA FOR POLICY 2017*

Government by Algorithm?





6-7 September 2017 | London



dataforpolicy.org  | @dataforpolicy <https://twitter.com/dataforpolicy>




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.


Extended abstracts for individual submissions should not exceed 1000 words
and group/special session submissions are limited to 4500 words (including
general session description and abstracts for each of the presentations in
the session).  All submissions will also be considered for post conference
publications and those selected will be invited to submit full discussion
papers prior to the conference.



*Submissions are accepted through the official conference website – *
*dataforpolicy.org* <http://dataforpolicy.org/>



Special discounts with conference registration fees will be applied to
students and early career researchers. Limited funding is also available to
support travel expenses of exceptional candidates. For those wishing to be
considered for travel support please send a CV and covering letter to the
conference team after completing your submission and before the submission
deadline.



Partnership and exhibition opportunities are available and organisations
can get in touch with the Data for Policy Team (team at dataforpolicy.org) to
discuss opportunities for collaboration.



All general enquiries about the conference should be directed to the Data
for Policy Team at team at dataforpolicy.org



*Important Dates: *



Abstract submission deadline: Monday, 8 May 2017

Notification of acceptance: Wednesday, 14 June 2017

Presenters’ registration deadline: Tuesday, 1 August 2017

Discussion Paper submission deadline:  Friday, 18 August 2017

Public registration deadline: Friday, 25 August 2017

Conference: Wednesday-Thursday, 6-7 September 2017





*Organising Bodies & Institutions: *



*Data for Policy* is an independent initiative launched in 2015 at its
inaugural conference *“Policy-making in the Big Data Era: Opportunities and
Challenges” *that was hosted by the University of Cambridge. The second
conference *“Frontiers of Data Science for Government: Ideas, Practices,
and Projections”* was also held at the same venue in 2016. The series has
proven to be a key international discussion forum around the theory and
applications of Data Science as relevant to governments and policy
research, and supported by a large number of key stakeholders including
prestigious academic institutions, government departments, international
agencies, non-profit institutions, and businesses.



The *Government Data Science Partnership* brings together capability from
ONS, GDS and GO-Science to support departments in applying data science and
big data techniques to challenges. There are four activity streams:


   - Working in an open and ethical way
   - Unlocking practical barriers
   - Creating and developing data science projects
   - Building data science capability across government

The Government Data Science Partnership vision is to improve government
capacity to use data science to underpin decision-making, policy
development, tailor services, and work efficiently. In doing so the UK
government will be recognised as world leading in its use of open and
ethical data science.



The *All-Party Parliamentary Group on Data Analytics* is a new cross-party
group of MPs and peers established by Daniel Zeichner MP to connect
Parliament with business, academia and civil society to promote better
policy making on big data and data analytics. *Policy Connect* is a
not-for-profit social enterprise with two decades in policy work,
overseeing the research and delivery of more than 50 key publications. We
have a long history of success in running engaging forums, commissions and
All-Party Parliamentary Groups.



Data for Policy is grateful to the following institutions for their
continuing support:


   - University College London
   - University of Cambridge
   - UK Government Data Science Partnership: Office for National Statistics
   (ONS), Government Digital Service (GDS), Government Office for Science
   (GO-Science)
   - All Party Parliamentary Group on Data Analytics
   - Imperial College London
   - London School of Economics and Political Science
   - University of Oxford
   - The Alan Turing Institute
   - Royal Statistical Society
   - European Commission
   - New York University
   - Leiden University



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