Data for Policy 2021

All conference contributions will be considered for peer-reviewed publication in Data & Policy, a Data for Policy – Cambridge University Press collaboration supported by the Alan Turing Institute, Office for National Statistics and UCL.

Save the dates:

• 14 – 16 September 2021

Where?

• Wilkins Building
  Gower St, Bloomsbury,
  London WC1E 6BT

More information and registration here.

The Special tracks for the conference are as follows:

1. ‘Showcasing innovative data services from EU Member States – Paving the way towards transparent documentation’ Track Chairs: Seth van Hooland, Emanuele Baldacci, Blanca Martinez De Aragon and Joao Rodrigues Frade
2. ‘Governance of the digital transformation of health systems’ Track Chairs: Tugce Schmitt and Mujaheed Shaikh
3. ‘Arguments, algorithms and tools: what do we need to shape policy and confront misinformation post-pandemic?’ Track Chairs: Jaron Porciello, Ulrike Hahn and Stephan Lewandowsky
4. ‘Ethical Technology Adoption in Public Administration Services’ Track Chairs: Francesco Mureddu, Giovanna Galasso and Francesco Paolo Schiavo
5. ‘AI and public decision-making processes’ Track Chairs: Sarah Giest, Bram Klievink and Alex Ingrams
6. ‘Rethinking the open data movement through an intersectional feminist lens’ Track Chairs: Anjali Mehta, Gülsen Güler and Amanda Greene
7. ‘Facilitating Data-Driven Innovation for Sustainability: Policy Frameworks and Measures for Data Governance’ Track Chairs: Masaru Yarime
8. ‘Towards a data-driven economy: Data Mexico’ Track Chairs: Luis Godoy, Ana Cruz and Fiorentina Garcia

The standard tracks of the conference are as follows:

• Data-driven Transformations in Governance & Policy – this standard track focuses on the high-level vision for philosophy, ideation, formulation and implementation of new approaches leading to paradigm shifts, innovation and efficiency gains in collective decision-making processes. Topics may include:
  • From data to decisions: scientific innovation in knowledge generation processes, data-driven insights, evidence-based policy making;
  • Applications in public, private and voluntary sector governance and policy-making (local, national, international)
  • Real-time management, future planning, and rethinking/reframing of governance and policy-making in the digital era;
  • Government-private sector-citizen interactions: data and digital power dynamics, asymmetry of information;
  • Democracy, public opinion and involvement, citizen services, media and digital platforms;
  • Interactions between human, institutional and algorithmic decision-making processes; psychology and behaviour of decision-making;
  • Socio-technical and cyber-physical systems, and their policy and governance implications.

The remaining categories represent more specifically the current applications, methodologies, strategies which underpin the broad aims of Data for Policy’s vision:

• Data Technologies & Analytics for Policy & Governance
  • Data sources: Personal, proprietary & administrative data, official statistics, open & public data;
  • Technologies: GovTech/RegTech, AI, blockchain, IoT, cloud, platforms, visualisation & user interaction;
  • Methodologies & Analytics: Theory & data-driven models, statistics, computational social science,
  • Machine Learning, edge analytics, mixed methods, real-time & historical data processing, geospatial analysis, gaps in theory & practice.

• Policy Frameworks, Governance and Management of Data-driven Innovations – this track focusses on governance practices and management issues involved in implementation of data-driven solutions:
  • Data collection, storage and circulation;
  • Data and algorithm design, value assessment;
  • Data supply chains, ownership, provenance, sharing, linkage, curation, and expiration;
  • Assignment of accountability;
  • Governance models and frameworks;
  • Data literacy, translation, communication;
  • Data intermediaries, trusts, collaboratives;
  • Data and algorithms in the law, regulation;
  • Meta-data, standards and interoperability.

• Ethics, Equity and Trust in Policy Data Interactions – this track examines the issues which must be considered in technology design and assessment.
  • Digital Ethics: Data, algorithms and interaction models;
  • Privacy, data sharing and consent;
  • Digital identification and services;
  • Uncertainties, bias, imperfections in data and data-driven systems;
  • Algorithmic behaviour: equity and fairness, transparency , explainability, accountability, interpretability and reliability;
  • Human control, rights, democratic values and self-determination;
  • Responsibility and maliciousness.

The following are areas which fall within the above categories, but are highlighted as being of special interest:

• Algorithmic Governance:
  • Algorithm agency along with human and institutional decision-making processes; black-box processing, data-driven insights;
  • Governance automation: citizen service delivery, supporting civil servants, managing national public records and physical infrastructure, statutes and compliance,  public policy development;
  • Good governance with/by/of algorithms: participation, consensus orientation, accountability, transparency, responsiveness, effectiveness and efficiency, equity and inclusiveness, the rule of law.

• Data to Tackle Global Issues and Dynamic Societal Threats:
  • Human existence and the planet;
  • International collaboration for global risk management and disaster recovery;
  • Global health, emergency response, Covid-19 and pandemics;
  • Sustainable development, climate change and the environment;
  • Humanitarian data science and international migration;
  • Racial justice and gender-based issues;
  • International security, organised crime and hostile environments.