Professor Sharyn O'Halloran

Title

Predicting Resilience: AI-enhanced approaches for adaptive policymaking

Summary

Governments struggle to manage today"s complex global challenges. The ADAPT project leverages artificial intelligence (AI) to
identify the governance traits that enable advanced democracies to withstand and recover from crises. This research programme
develops insights into how well-designed institutions can help societies manage uncertainties.
ADAPT is structured around constructing three core benchmarks:
1) The ADAPT Database"an extensive archive of structured and unstructured data documenting resilience across 23 jurisdictions in
15 languages over 70 years;
2) A dynamic, multilingual NLP model that extracts adaptive features from legal texts; and
3) A Resilience Governance Measure designed to predict countries" capacity to resist and react to crises.
The ADAPT Database integrates economic metrics, legal texts, legislative records, and governance documents, setting a new standard
in resilient governance research. Using an iterative approach, broadly known as Theory-Guided Artificial Intelligence (TGAI)"which
combines theoretical frameworks with data-driven methods"ADAPT refines adaptive policymaking models by linking theory with
practical data-driven applications. Through advanced NLP and machine learning (ML) techniques, including deep learning, ADAPT"s
dynamic, multilingual model classifies laws and regulations, developing resilience measures that reflect a nation"s ability to respond
to economic, social, and environmental crises.
ADAPT reimagines democratic resilience by integrating AI methods with theories of adaptive policymaking. The synergistic results of
ADAPT's diverse team of experts will catalyze a new wave of scholarship, setting a standard for interdisciplinary research at the nexus
of AI and public policy. Its scalable and flexible framework provides policymakers and researchers with actionable policy insights and
tools, crafting systematic responses to crises and strengthening governance in an uncertain world.

Funding Agency

ERC

Date From

01/01/2026

Date To

01/01/2032

Title

Democratic Resilience in the Digital Era (DRIDE)

Summary

Democratic Resilience in the Digital Era (DRIDE) will deliver a Horizon Europe Cluster 2 project that supports the call"s objective to reinvigorate and shield European democracy. DRIDE makes democratic resilience measurable, comparable, and actionable by combining comparative governance theory with interpretable, theory-guided analytical methods, including AI, applied to legal and regulatory frameworks. The project analyses how institutional rules, procedures, and governance arrangements shape accountability, transparency, trust, and inclusive participation under conditions of crisis, digital disruption, and external pressure.

DRIDE develops a policy-focused Institutional Resilience Scorecard and decision-support tools to assist
democratic actors to:
" Assess governance features that enhance resilience or expose systems to rigidity and legitimacy risks.
" Identify accountability gaps and decision-making bottlenecks that arise during crises.
" Compare the design and robustness of democratic safeguards across countries and sectors to inform
evidence-based reforms and policy design.
DRIDE provides policy-making bodies and civil society with interpretable evidence to navigate core democratic trade-offs, including speed versus oversight, discretion versus accountability, and flexible response versus participation. The Resilience Scorecard is designed for practical use by policy
institutions and civil society, enabling benchmarking and stress-testing of governance frameworks to support evidence-based policymaking. The project delivers reusable outputs that promote EU-wide learning and enable structured comparisons across institutional contexts, time periods, and policy domains.

Funding Agency

Enterprise Ireland

Date From

September 2026

Date To

September 2028

Title

Competition and Regulation of Technology (CORETEXT)

Summary

Technological developments are central to understanding rapid changes in power structures in society, as market power is augmented by data and by hardware and software technologies (such as platforms and search) that are controlled by a few players. Efforts to address power and ensure that new companies can succeed without hindrance rely on a combination of regulation and competition. Meanwhile, European success in creating durable technical enterprises has been limited, posing enduring questions about how to succeed in the economy of the future. The CORETEXT Doctoral Networks (DN) will train the next generation of scientists in a range of interdisciplinary and cross-sector methods to make significant progress in understanding how to regulate existing companies and motivate new ones. Training is structured around two interdisciplinary research themes: Understanding: analysis, theories of societal risks, harm, and benefits, and remedies, and Application: law and governance. Both involve extensive, systematic co-supervision and collaboration across sites, with vigorous interplay between academic beneficiaries and associated partners. In turn, we expect improved governance and laws to emerge, with associated societal and economic benefits. The training of the cohort of Doctoral Candidate (DC) fellows is based on innovative PhD training approaches, providing not only interdisciplinary training but also peer-assisted methods and in-depth work-based expertise. This will produce a cohort of highly skilled researchers who will be highly employable, given the potential contribution they will make to future research and innovation in the public and private sectors.

Funding Agency

European Research Council

Title

Danu Irish National Centre for AI and Data Science

Summary

The Danu Centre for AI and Data Science is a world-leading Research Ireland (formerly SFI) centre focusing on human-centric AI-driven technology and data science applications that empower people to engage more effectively in a digital world. It is a multi-institutional hub coordinated by Trinity College Dublin and co-hosted by Dublin City University (DCU).

Funding Agency

Research Ireland (formerly SFI)

Date From

2026_06_01

Date To

2033_05_31