Data for policy 2024 - Decoding the Future: Trustworthy Governance with AI?

We invite researchers, practitioners, and policymakers to join us in charting a path towards more trustworthy decision-making and governance with the transformative potential of AI. We are seeking conference submissions that transcend boundaries, from cutting-edge generative AI technologies re-shaping government-citizen interactions to enhanced surveillance capabilities that influence centralised power dynamics. In a world where AI-powered technologies are becoming integral to critical decision-making processes, it is time to chart a new course.

We welcome submissions covering a wide range of topics, including but not limited to:

• AI applications for policy formulation and implementation
• Impact of Generative AI on public service delivery and citizen engagement
• Machine agency in governance and decision-making
• Human-AI collaboration and decision-making in governance
• AI-driven decision support systems for public administration
• Legal and regulatory frameworks for AI in governance
• Safety, transparency, fairness, accountability, and trust in AI-driven decision-making
• Data and infrastructure technologies working in tandem with AI to transform decision-making in governance (chatbots, platforms, distributed ledger systems, digital twins, augmented reality, etc.)
• Governance models and frameworks for effective utilisation of AI options in decision-making processes to enhance good governance practices

The Data for Policy 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. The general chairs Dr Zeynep Engin (Founder, Data for Policy), Jon Crowcroft (University of Cambridge) and Stefaan Verhulst (NYU) are delighted to be working with local chairs from our host Imperial College, Professor Mark Kennedy and Dr Rosella Arcucci for the 2024 edition in this conference series. Data for Policy is an independent non-profit initiative, registered as a community interest company in the UK.

For any enquiries or further information, please contact team@dataforpolicy.org or check https://dataforpolicy.org/data...

We welcome submissions covering a wide range of topics, including but not limited to:

• AI applications for policy formulation and implementation
• Impact of Generative AI on public service delivery and citizen engagement
• Machine agency in governance and decision-making
• Human-AI collaboration and decision-making in governance
• AI-driven decision support systems for public administration
• Legal and regulatory frameworks for AI in governance
• Safety, transparency, fairness, accountability, and trust in AI-driven decision-making
• Data and infrastructure technologies working in tandem with AI to transform decision-making in governance (chatbots, platforms, distributed ledger systems, digital twins, augmented reality, etc.)
• Governance models and frameworks for effective utilisation of AI options in decision-making processes to enhance good governance practices

The Data for Policy 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. The general chairs Dr Zeynep Engin (Founder, Data for Policy), Jon Crowcroft (University of Cambridge) and Stefaan Verhulst (NYU) are delighted to be working with local chairs from our host Imperial College, Professor Mark Kennedy and Dr Rosella Arcucci for the 2024 edition in this conference series. Data for Policy is an independent non-profit initiative, registered as a community interest company in the UK.

For any enquiries or further information, please contact team@dataforpolicy.org or check https://dataforpolicy.org/data...

Standard tracks

Data for Policy has six non-domain specific and overarching areas of interest for the conference and journal. The areas are interrelated and do not indicate siloed activity. They are rather an articulation of the breadth and depth of the vision and mission for improved data-driven decisions and policymaking, which is the ethos of the Data for Policy community. The six areas are the bases for the conference’s standard tracks, as follows:

AREA 1: DIGITAL & DATA-DRIVEN TRANSFORMATIONS IN GOVERNANCE

• From data to decisions: knowledge generation and evidence formation;
• Process, psychology and behaviour of decision-making in digital era;
• Government operations and services;
• Government-citizen interactions; and open government;
• Democracy, public deliberation, public infrastructure, justice, media;
• Public, private and voluntary sector governance and policy-making.

AREA 2: TECHNOLOGIES & ANALYTICS

• Data Science and Artificial Intelligence;
• Behavioural and predictive analytics;
• Large language models – foundation models;
• Digital Twins, Ledger Systems, Platforms, Cloud Technologies etc.
• Edge analytics and federated learning;
• User interaction and experience;
• GovTech, RegTech, LegalTech, CivicTech etc.

AREA 3: POLICY & LITERACY FOR DATA

• Governance, law and management of data and associated technologies;
• Design principles and impact assessment;
• Literacy, translation, communication;
• Intermediaries, trusts, collaboratives;
• Regulation of data-based services and processes;
• Open science, open research infrastructure, and FAIR (Findable, Accessible, Interoperable and Reusable) practice.

AREA 4: ETHICS, EQUITY & TRUSTWORTHINESS

• Privacy, data sharing and consent;
• Uncertainties, error and
bias in data-driven processes;
• Human rights, values and self-determination;
• Information and power asymmetry;
• Responsibility, benevolence, and maliciousness;
• Fairness, transparency, explainability, accountability, interpretability and reliability;
• Validation, assurance and certification of data-driven services.

AREA 5: ALGORITHMIC GOVERNANCE

• Automation of government/governance processes and services;
• Good governance through/with/by/of algorithms;
• Algorithm agency in decision-making: potentials and perils;
• Algorithmic behaviour in socio-economic contexts;
• Human agency in algorithmic governance;
• Human-machine collaboration models in critical decision-making.

AREA 6: GLOBAL CHALLENGES & DYNAMIC THREATS

• Human existence and the planet;
• Inequalities and discrimination;
• Sustainability and environment;
• Global shocks and resilience;
• Population health and pandemics;
• Security, organised crime and hostile environments;
• International collaboration.