Tessera
Folgen

AI Accountability Lab

@aial.ie

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

38 Posts3760 Follower46 Folgt
AI Accountability Lab @aial.ie · 2mo ago

Will you be at FAccT next week? Come hang out with us & learn about our work. We’ll discuss pathways to meaningful accountability, theories of change, & what brings us joy along the way over iconic bagels & TimBits in the park Sat June 27th, 18:00 - 20:00, Jeanne-Mance Park aial.ie/news/facct20...

AI Accountability Lab at FAccT 2026

Members of the AIAL will be at the ACM Conference on Fairness, Accountability, and Transparency (FAccT) in Montreal, presenting our work and hosting a social for the community. Come hang out with the ...

aial.ie

Foxglove Legal@foxglovelegal.bsky.social · 2mo ago

ICYMI: why it's a bad idea for the UK government to give US tech giant Palantir a role at the heart of the state - and why ministers need to take the chance to kick them out of the NHS: www.lbc.co.uk/article/pala...

A firm obsessed with dominance like Palantir shouldn’t be at the centre of our state | LBC

Should we really be handing more and more parts of our public services to Big Tech firms, whose leaders are not particularly keen on democracy? writes Donald Campbell

lbc.co.uk

The ADAPT Centre@adaptcentre.bsky.social · 2mo ago

SCREENING SAT JUNE 6th - Ghost in the Machine w/ Q&A with Dr. @abeba.blacksky.app, Director of @aial.ie @tcddublin.bsky.social and chaired by @elaineburke.bsky.social host of @fortechssakepod.bsky.social TICKETS: ifi.ie/film/ghost-i...

GHOST IN THE MACHINE + Q&A - Irish Film Institute

SCREENING SATURDAY JUNE 6th Valerie Veatch’s gripping documentary exposes the hidden history of AI, not as a neutral system of algorithms, but as a technology shaped by racism, misogyny, eugenics, and...

ifi.ie

Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

In our conclusion, we stress that industry capture is not just an urgent academic concern but a pressing real-world issue with global consequences. While, gegulators may engage with industry, governance must ultimately protect the public interest, not corporate power. 11/

Bild
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

Civil society orgs and investigative journalists are doing indispensable work: promoting counter narratives and resistance, exposing lobbying and deregulation, documenting harms, advancing strategic litigation... Support them. Fund them. Amplify their work. 10/

BildBild
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

We survey and highlight transferable lessons from adjacent movements, namely Big Oil, Big Tobacco and Big Pharma. We advocate for supporting grassroots groups, CSOs and independent academics that are doing amazing work to hold Big AI and regulators accountable and to ensure the rule of law. 9/

Lessons from adjacent movements. Many of the mechanisms of capture used by Big AI, that we have discussed in this paper, mirror strategies that have historically been applied by similar industries such as Big Tobacco, Big Pharma, and Big Oil. Civil society’s efforts to hold big corporations accountable in these sectors is ongoing and has been met with significant challenges and has often fallen short of meaningfully countering corporate power [45, 50, 118]. Yet, there are remain lesson to be learned from these efforts and the braoder scholarship on corporate capture. For example, the OECD report on preventing policy capture in public decision-making [85] recommends to (i) level the playing field by engaging diverse stakeholders, (ii) ensure transparency and access to information, (iii) promote accountability via external control, effective competition, and regulatory policies, and (iv) define clear institutional codes of conduct, promote cultures of integrity, and establish appropriate frameworks for risk-management. Similarly, in the context of Big Tobacco, Lee [63] calls for appropriate separation between public and private interests, binding rules for government-industry interactions to manage conflicts-of-interests, enforcement of transparency and accountability practices, and safeguarding academic knowledge production from undue industry influence. A 2024 report [5] further calls for applying transferable lessons from the US Food and Drug Administration on how to regulate and hold Big AI accountable
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

These conflicts of interest endanger public trust in institutions’ ability to scrutinise corporations and enforce the law while raising serious questions about the growing integration of Big AI infrastructure into state power under the banner of "government efficiency" 8/

Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

Across the US, EU and UK, our findings show regulatory capture isn’t just driven by Big AI - governments and public officials are deeply entangled too. Revolving doors, blurr regulator-industry boundaries & ownership/direct financial stakes in companies are undermining democratic accountability 7/

Prior work has typically adopted a dichotomous theoretical lens – distinguishing information capture from influence on policymaking [108], whereas the most recurring mechanisms in our evidence also include the Elusion of law. These recurring violations and contentious interpretations of antitrust, privacy, copyright and labour laws call into question the effectiveness of enforcement. Such pressures, along with weakening the mandates of regulatory agencies, risk the normalisation of a de facto law in which Big AI operates outside the bounds of regulatory scrutiny. Furthermore, the stochastic nature of the underlying technology–where the technology cannot be reliably tested–coupled with the economic power of Big AI corporations enables a normalisation of “algorithmic states of exception” at scale. Defined by McQuillan [71], this indicates the application of algorithms as the de facto authority in contexts where their behaviour has not been or cannot be tested, creating conditions akin to martial law. The conjunction of law-flouting practice and technological affordances thus raises urgent concerns regarding the contemporary integrity of lawmaking institutions over their respective jurisdictions. Our annotation of narratives employed provide another qualitative avenue for insight into capture strategies, which can be further studied to understand the causal or system impact of different narratives on discourse, public conceptions of AI, and knowledge production. Our finding that there is substantial growth over time in the Discourse & Epistemic Influence (see Figure 2b) indicates that how AI is framed is becoming increasingly important. The consistent co-occurrence of each D&EI mechanism with approximately one corresponding mechanism from other categories indicates the significant role that public-facing campaigns play.
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

49 out of the 100 articles we analysed contain narrative(s) that attempt to justify capture: 'Regulation stifles innovation,' 'Red tape,' 'National interest' were amongst the most frequently invoked 6/

BildBild
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

Big AI’s most powerful regulatory tool may be narrative capture -> Epistemic & Discourse Influence: getting regulators to adopt industry talking points as common sense. Close behind is Elusion of law: violations and contentious interpretations of antitrust, privacy, copyright and labour laws 5/

Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

Applying the taxonomy to a dataset of 100 articles, specifically published around four critical events between 2023 and 2025 ( the EU AI Act trilogues and the global AI summits in the UK, South Korea and France), we find 249 cases fitting capture patterns. 4/

Bild
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

Through extensive scoping review of grey and academic literature, we first develop our taxonomy of mechanisms related to capture of AI regulation, spanning 5 dimensions: Direct Influence on Policy, Conflicting Involvement, Market Influence, Elusion of Law, & Epistemic & Discourse Influence 3/

a table describing Taxonomy of capture mechanisms. highlighted concepts denote five broad, high-level categories, each further comprising a set of detailed mechanism categories and descriptions.
Dr Abeba Birhane@abeba.blacksky.app · 3mo ago

We define Big AI “handful companies that develop & mass deploy large-scale AI built on massive datasets collected through vast, centralised infrastructures, which, with increased integration into societal infrastructure, continue to exert outsized epistemic, economic, political & societal influence”

We use the term ‘Big AI’ to refer to the handful of companies that develop and mass deploy large-scale AI technologies – such as large pre-trained models – built on massive datasets collected through vast, centralised infrastructures, which, with increased integration into societal infrastructure, continue to exert outsized epistemic, economic, political, and societal influence. The term ‘Big AI ’ also encapsulates the structural consolidation of AI technologies by Big Tech as their core value proposition, central to their infrastructure, resources, and strategic investments [121]. While new entities such as OpenAI, Anthropic, DeepSeek and xAI are included in our definition due to their significant geo-political influence, ‘Big AI’ also marks the shift of existing Big Tech companies – Alphabet, Meta, Amazon, Microsoft, Apple, NVIDIA – towards becoming “AI-first” companies, further expanding their unprecedented power and influence across all economic sectors and aspects of public life.