Abstract submission deadline: Monday, 8 May 2017
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.
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.
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.
Source: DATA FOR POLICY 2017