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AI Accountability Lab

@aial.ie

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Trinity College Dublin’s Artificial Intelligence Accountability Lab (https://aial.ie/) is founded & led by Dr Abeba Birhane. The lab studies AI technologies & their downstream societal impact with the aim of fostering a greater ecology of AI accountability

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AI Accountability Lab

@aial.ie

The AIAL is looking for a highly driven Post-Doctoral Researcher who can design and implement research that improves transparency and accountability regarding the use of generative AI in public services

Application closes on Dec 02, 2025

More information: aial.ie/hiring/postd...

About AIAL

The AI Accountability Lab (AIAL) is a research lab hosted in the ADAPT Research Centre and the School of Computer Science and Statistics in Trinity College Dublin. We are driven by the urgent need to demystify, critically assess, and publicly communicate the operations and functionality of AI systems by looking under the hood as well as their downstream impact on the public with the aim of shaping public knowledge, shifting power, and reserving fundamental rights, freedoms, and autonomy. The AIAL is an innovative lab at the cutting-edge of AI dedicated to greater transparency on the use of AI systems in the public domain and concrete accountability for the downstream societal impact of these technologies.

The AIAL operates under the core principle that academic research, particularly research in AI, should be of a high-relevance and utility to the public. Thus, we actively engage and partner with local communities, civil society, and rights groups to ensure our work is grounded in real challenges and remains relevant and useful to these stakeholders. We are deeply committed to ensuring our work contributes to fostering transparency and driving a culture of AI accountability. Academic freedom and autonomy are of utmost importance to us and we take great care to ensure our lab is free from direct conflict of interest or implicit influence or pressure from the industry that we are studying. We are funded by philanthropic organisations such as the MacArthur foundation and European grants.

About the role

There is currently a growing move by governments worldwide, including the Irish government, to integrate generative AI technologies into public sector operations. However, information on the where, how, why, and when such technologies are being used remains scarce. Without this knowledge, it is difficult to understand, assess, and ensure the integrity of public services. The AIAL seeks to understand this challenge better and to conduct high-quality, high-impact research that helps uphold the principles of transparency, accountability, and equity.

To directly tackle this urgent problem, the AIAL is looking for a highly driven Post-Doctoral Researcher who can design and implement research that improves transparency and accountability regarding the use of generative AI in public services. The researcher will particularly focus on uncovering and critically examining the integration, procurement, and governance practices of generative AI in government functions and public service operations. The output of this work is expected to be a public-facing database that acts as a knowledge-base and provides transparency and critical evaluation into the use of generative AI with the aim of expanding public knowledge and feeding into regulations and standards. Applications are invited from suitably qualified candidates for a 2-year, in-person, full-time fixed term position as a Post-Doctoral Researcher at the AIAL.

Responsibilities

Identify and map public sector organisations and government bodies that are integrating generative AI into internal as well as public-facing processes, in particular where these constitute decision making. The scope for this work will be Ireland in the initial stages
Identify similar initiatives with value-aligned researchers/organisations across Europe and establish collaborations with the aim of painting a fuller-picture as well as performing cross-country comparisons and analysis. The appointed candidate will be expected to establish this collaboration to share findings from Ireland and learn from other EU initiatives to develop a pan-EU analysis
Develop a public-facing database detailing the use of generative AI in public sectors. The database will provide key information such as modality, model version, vendor information, contractual agreements (if any), known risks, and will also facilitate information such as how it was procured, and where it is being used, for what purpose as well as any prior audits or testing done and main findings
Identify and analyse contractual agreements and policies regarding the procurement and use of generative AI in public services. The appointed candidate will be expected to understand the procurement system involving government bodies and technology vendors, and the means to achieve this information where it isn’t readily available – such as through freedom of information requests. The analysis of obtained information will be through the lens of relevant European regulations to identify key information and transparency, accountability and equity concerns
Assess the impact of generative AI in decision-making processes in government and the implications for institutional transparency, governance and accountability

Requirements

Hold a PhD in the following disciplines: computer science, machine learning, artificial intelligence, AI policy research, investigative journalism, management sciences, information systems studies, science and technology studies or cognate disciplines
In-depth experience and publication track-record examining governance structures, power asymmetries and EU regulations
Demonstrable experience in data visualisation, statistical analysis and a history of working with freedom of information (FoI) requests
In-depth knowledge of European legislations and regulations such as the AI Act, DSA, GDPR
Comprehensive knowledge (with a publication track record) of the AI audit landscape. Hands on experience with black-box auditing as well as executing qualitative and quantitative audits, particularly of generative AI
Self-driven, passionate, and committed to transforming institutional transparency from a theoretical concept to a concrete, operationalisable, and practical mechanism for expanding public knowledge and fostering accountability
Ambitious and passionate communicator who is well able to articulate transparency (lack thereof) and accountability in this domain, even when there is considerable pushback
Experience working with civil society organisations and community organising with a particular focus on AI transparency, accountability, equity and the rule of law

October 30, 2025 at 7:44 PM

AI Accountability Lab

@aial.ie

We are seeking to appoint a Postdoctoral Researcher to work on developing a justice-oriented audit framework synthesising computational methods, theories of justice, and existing regulations to premeditatively focus audits towards meaningful accountability. www.adaptcentre.ie/careers/post...

Research project/Challenge
The AIAL (AI Accountability Lab) is seeking to appoint a Postdoctoral Researcher to work on developing a justice-oriented audit framework synthesising computational methods, theories of justice, and existing regulations to premeditatively focus audits towards meaningful accountability. The goal of the framework is to provide audit practitioners with practical tools such as guiding questions and rubrics that shape perspectives towards rigorous justice oriented audits.

The position corresponds to work in one or more of the following areas:
Accountability
Mapping accountability mechanisms and governance structures and their alignments with fundamental rights and freedoms and legal frameworks.
Challenging existing accountability mechanisms that do not consider or sufficiently address social inequalities, power and resource asymmetries.
Developing new methods for ensuring accountability beyond technical and organisational considerations that provide empirical evidence for holding stakeholders accountable for AI development, provision, and deployments.
Auditing
Developing audit methodologies for specific stages in the AI lifecycle focused on ensuring justice, accountability, and transparency beyond merely satisfying legal requirements.
Development of verifiable, replicable, and reproducible design methodologies and frameworks and using these in the execution of audits.
Developing audit tools and frameworks to evaluate AI development and deployments with a specific focus on risk and harm mitigations beyond technical and organisational issues.

April 2, 2025 at 3:26 PM

AI Accountability Lab

@aial.ie

Time for the second fireside chat between David Leslie (Alan Turing Institute), Delaram Golpayegani (@adaptcentre.bsky.social) Olga Cronin (Irish Council for Civil Liberties), and Patricia Scanlon (SoapBox Labs)