[Air-L] Fwd: [CfP Deadline: 28th January] Data for Policy 2019 - Digital Trust and Personal Data, 11-12 June, London

Zeynep Engin ds.engin at gmail.com
Wed Jan 16 05:17:33 PST 2019


Dear All,

Below is the *final CfP reminder* for the upcoming Data for Policy 2019
conference in London. We will appreciate if you could help us circulate
this as widely as possible in relevant networks. *CfP Deadline: Jan 28th.*

Best wishes,

Zeynep

---------- Forwarded message ---------
We invite contributions for the Data for Policy 2019 conference - Deadline:
28th January

Call for Papers, Presentations, Sessions and Demos
*Extended Abstract Submission Deadline: January, 28th*

4th International Conference

*Data for Policy 2019:*

Digital Trust and Personal Data

11-12 June 2019, London

dataforpolicy.org
<https://dataforpolicy.us9.list-manage.com/track/click?u=0e48a758fb1eccb009ec5c754&id=82439179ca&e=5b0bc1e683>
  | @dataforpolicy
<https://dataforpolicy.us9.list-manage.com/track/click?u=0e48a758fb1eccb009ec5c754&id=188316eac0&e=5b0bc1e683>

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.

We also invite submissions for the following Special Tracks:

   - *Trading Data for Health: Balancing Ethics, Economics and Technology *-
   Track Chair: Anil *Bharath*, Imperial College London
   - *Data Practices, Lessons and Challenges: A Private-Sector (Business)
   Perspective* - Track Chair: Bilal *Gokpinar*, University College London
   - *Blockchain & Data Governance* - Track Chair: Catherine *Mulligan*,
   World Economic Forum, UN Digital Cooperation, Imperial, UCL
   - *Successful Uses of Data and AI for Public Good *– Track Chair: Tom
   *Smith*, Office for National Statistics, UK

Contributions can be proposed in the following categories (please see the
guidelines for more details).

   - *Individual Research/Policy/Practitioner Proposals (1000-word max.): *An
   extended abstract should be submitted, which includes a title, the
   research/policy question, the research methodology and data used, and key
   findings.
   - *Session Proposals (4500-word max.):* Session proposals are welcome.
   This combines 3-4 presentations from researchers and/or practitioners each
   providing a max. 1000-word abstract. A max. 500-word description of the
   panel should also be submitted.
   - *Demo Proposals:* The Demonstration Track is intended to provide an
   opportunity to showcase new tools, technological advances, and services
   offered in this emerging field. The contributions must demonstrate
   state-of-the-art technology and must be run live, preferably with some
   interactive parts. A max. 1000-word description of the session should be
   submitted, which includes the technology demonstrated, the elements of
   novelty, the live-action part, the interactive part, the equipment brought
   by the demonstrators, and the equipment required from the track organisers.
   - *Poster Submissions:* All individual submissions to the conference
   will first be considered for oral presentation and then for poster sessions
   at the conference. Those who wish to make submission for the poster
   sessions only should make a standard submission indicating at the top that
   they are only interested in presenting a poster.

*Official conference website - dataforpolicy.org*
<https://dataforpolicy.us9.list-manage.com/track/click?u=0e48a758fb1eccb009ec5c754&id=9059e6702d&e=5b0bc1e683>

*Make a submission here*
<https://dataforpolicy.us9.list-manage.com/track/click?u=0e48a758fb1eccb009ec5c754&id=c9d43d7fe7&e=5b0bc1e683>

Please note that this is a fee-paying event and all conference
participants, including presenters, will be responsible for arranging their
own travel and accommodation. We have limited funding to support student
participation: those who wish to be considered for these grants should send
a CV and cover letter explaining their case to team at dataforpolicy.org. This
should be done *after completion of abstract submission*.

All general enquiries about the conference should be sent to
team at dataforpolicy.org

*Important Dates: *

Submission Deadline for Extended Abstracts 28 January 2019
Notification of Acceptance 4 March 2019
Registration Deadline for Presenters 8 April 2019
Deadline for Discussion Paper submissions 13 May 2019
Deadline for Public Registration 31 May 2019 (may close earlier if all
places are taken)
Conference in London 11-12 June 2019
*Conference Partnership & Sponsorship:*

Data for Policy conference series is an independent non-for-profit
initiative and fully funded by the income raised through conference
registrations and partner/sponsor contributions. Organisations interested
in our flexible partnership/sponsorship packages should get in touch with
our team via email (team at dataforpolicy.org).

*Call for Bids to Host Future Data for Policy Conferences: *

We welcome bids from academic, government and private sector stakeholders
to host future Data for Policy conferences. Consortium bids bringing
together a host country’s academic and government stakeholders are
encouraged and demonstration of further industry support would also be an
advantage. Interested organisations should send a brief Statement of
Interest to team at dataforpolicy.org, outlining the partnership model
proposed and the commitments offered. Bids will be considered on a rolling
basis.

*Supporting Institutions: *
*Copyright © 2019 Data for Policy, All rights reserved.*



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