Data for Policy 2021
The sixth International Data for Policy Conference will take place in London in September 2021. The conference series is the premier global forum for multiple disciplinary and cross-sector discussions around the theories, applications and implications of data science innovation in governance and the public sector.
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
- Wilkins Building
Gower St, Bloomsbury,
London WC1E 6BT
More information and registration here.
The Special tracks for the conference are as follows:
- ‘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
- ‘Governance of the digital transformation of health systems’ Track Chairs: Tugce Schmitt and Mujaheed Shaikh
- ‘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
- ‘Ethical Technology Adoption in Public Administration Services’ Track Chairs: Francesco Mureddu, Giovanna Galasso and Francesco Paolo Schiavo
- ‘AI and public decision-making processes’ Track Chairs: Sarah Giest, Bram Klievink and Alex Ingrams
- ‘Rethinking the open data movement through an intersectional feminist lens’ Track Chairs: Anjali Mehta, Gülsen Güler and Amanda Greene
- ‘Facilitating Data-Driven Innovation for Sustainability: Policy Frameworks and Measures for Data Governance’ Track Chairs: Masaru Yarime
- ‘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.