Read the report here.

People are unable to scrutinise or challenge decisions that affect their rights because current mechanisms for finding information about the use of artificial intelligence (AI) and automated decision-making by public bodies are failing, finds new research by PLP. 

Public bodies across the UK are increasingly using automated tools, including AI, to make or support important decisions about people’s lives such as social security, tax or adult social care services. Yet those affected often cannot find out whether a tool was used in their case, let alone how it works or whether it treated them fairly. 

Missing Pieces: Transparency and Accountability in Public Body Automated (and Automated Assisted) Decision-making, funded by the Nuffield Foundation, finds a patchwork of transparency mechanisms that both individually and collectively fail to provide people with the information they need, in the time they require it. The report sets out how to close these gaps and turn the government’s commitment to transparency, accountability, and contestability into reality. 

The report is published amid growing calls for legislative reform on AI, including from the Joint Committee on Human Rights. 

Key findings include: 

• People are rarely told whether a tool has been used to make a decision. As a result, they are unable to effectively contest the use of tools or decisions made using them.  

• High-risk systems are missing from the government’s own register. Of 15 automated systems identified in the research that are believed to still be in use, only four appear on the government’s public register of algorithmic tools, the Algorithmic Transparency Recording Standard (ATRS), even though several fall within its mandatory scope. 

• Information about the risk of discrimination is especially thin. Of the 125 ATRS entries reviewed, researchers found only one linked to an Equality Impact Assessment (the document public bodies  use to evaluate the risks of discrimination posed by a policy or decision).

• Public bodies often withhold information under Freedom of Information exemptions, most commonly on law enforcement grounds. Other challenges include information withheld due to concerns about commercial confidentiality. 

• Notification requirements under data protection law are inadequate: current provisions under data protection law draw a binary distinction between decisions which are “solely” automated and those where there is a “human-in-the-loop”. Rights to be notified and informed do not apply where AI or automation is used to shape, inform or assist decisions made about them. 

• People working in public bodies support transparency but face barriers. Public body participants, without exception, were supportive of transparency but identified challenges to meeting requirements in practice. These include lack of technical capacity, concerns about public trust and difficulty obtaining information from third-party suppliers. 

• Information gaps create a “vicious circle” in judicial review litigation. Without enough information to assess the merits of a case, claimants find it too risky to issue a claim so never reach the stage when full disclosure is required. 

What needs to happen? 

The report concludes that the legal and regulatory framework for an increasingly automated state cannot be left to evolve through the courts alone. PLP recommends that: 

• Governance, engagement and design processes are informed by public law considerations from the outset. 

• The ATRS be placed on a statutory footing, to strengthen monitoring, compliance and enforcement. 

• A legal requirement is introduced that requires people to be notified when and how automated systems have been used to support individual decisions about them, with enforceable individual rights to information about those systems.

Image: Summary of extent to which current transparency mechanisms apply to automated and automated assisted decision making systems

Read Annexes1-3 here. 

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Parliament’s Joint Committee on Human Rights (the Committee) has concluded its inquiry into Artificial Intelligence (AI) regulation. Public Law Project (PLP) welcomes its report as perhaps the most thorough parliamentary treatment we have had of how AI is affecting (and may yet affect) people’s rights, including through its use in the public sector.

The Committee’s central conclusion is that the UK is not doing enough to regulate AI and protect people’s rights. Their report warns us that, in racing to realise the promises of AI, we risk taking power away from people by making decisions that affect them harder to understand and challenge. PLP’s evidence to the inquiry was focused on how this accountability problem arises in the public sector. This blog explains and comments on the relevant Committee findings.

Lack of transparency

The Committee has concluded that “the current legal framework does not provide for adequate transparency in relation to the development and deployment of AI systems” (at [130]). In the public sector, this transparency problem can be seen at two levels.¹

At a systemic level (i.e. the general picture of how government is using AI), the Committee cited PLP’s Tracking Automated Government Register as evidence that government is insufficiently transparent about its use of AI in decision-making. It concluded that, although the Algorithmic Transparency Recording Standard (‘ATRS’) (a mandatory transparency requirement for certain central government algorithmic tools) “provides some transparency concerning the use of AI systems”, it is “limited in its coverage” (at [133]).

This systemic transparency problem should be addressed by any AI Bill aimed at safeguarding human rights (such as that recommended by the Committee). Placing the ATRS on a statutory footing would be a good way to start – it is already mandatory for central government, but compliance with it is low. Giving a suitable body a statutory responsibility for enforcing the ATRS could improve that.

At an individual level (i.e. the information given to individuals about how AI has been used in a decision affecting them), the Committee concluded that there is strong evidence to suggest that individuals have been unable to challenge human rights violations because they have not been told about AI use (at [131]).

The Committee agreed with PLP’s evidence that public bodies’ obligations to tell people when AI has influenced a decision affecting them need to be made clearer (at [215] and [217]). Although the UK GDPR requires that people be informed where a significant decision about them is taken solely through automated means,² the requirement does not apply where a human decision maker is assisted by AI. Extending the requirement to AI-assisted decisions, and clarifying what information must be provided, could help people understand whether and how AI shaped decisions affecting them and assess whether a human was meaningfully involved in it (for example, by assessing whether the decision-maker had enough time and information to meaningfully review an automated output).

Fragmented regulation

The Committee concluded that “the present regulatory framework is fragmented and difficult to navigate” and that, as a result, a dedicated AI oversight body is needed to plug gaps in protection, including by auditing AI systems, issuing codes of practice and transparency requirements, investigating alleged breaches and sanctioning non-compliance (at [224]-[227]).

In the public sector, fragmentation can weaken accountability in three ways: first, by creating uncertainty about how existing legal standards apply when AI is used in decision-making; second, by making it harder to enforce those standards; and, third, by risking leaving gaps where types of harm are not properly addressed. Weak enforcement can make uncertainty worse, including by limiting opportunities for courts to clarify the law. So, the Committee is right to address both problems through its proposed AI Bill and new oversight body.

AI-assisted public decision-making may require targeted reform. PLP’s evidence details how public bodies using AI in decision-making have to navigate overlapping requirements across public law, human rights, equality law, and data protection – with considerable uncertainty about how each applies in this context (see our response to Question 2). As we have argued elsewhere, this has given a heightened significance to clear rules which are easier to apply. It is more straightforward, for example, to ensure that there is human involvement in significant decisions,³ than it is to assess, case by case, whether broader public law requirements such as fairness have been met. Targeted reform (including through the Law Commission’s review of public sector automated decision-making) could help clarify such requirements and prevent clearer, more easily applied rules from crowding them out.

Diffuse responsibility for AI

The Committee concluded that AI “deployers are the primary holders of responsibility for harms arising from AI systems” and “existing laws do not take due account of the complexity of the AI lifecycle and supply chain and are not directed to the actor that may be best placed to identify and avert the source of risks” (at [104]).

The concern is that responsibility for making sure systems are fair, lawful and non-discriminatory may not clearly attach to the actor(s) best able to identify and prevent connected risks. When a public body uses an AI system, it may be practically difficult for them to take meaningful responsibility for it if actors in the supply chain are not subject to complementary upstream obligations concerning, for example, the system’s design.

PLP has observed this play out as public bodies seek to comply with transparency requirements for automated decision-making. It is right that public bodies adopting AI systems to support their decision-making should be responsible for meeting relevant transparency requirements. However, as our upcoming research ‘Public Law Litigation in the Automated State’ will show, transparency mechanisms’ practical effectiveness can be undermined where upstream actors such as system developers are not required to provide public bodies with the information they need – particularly technical information, such as training data, which can be harder to obtain after deployment. Requiring developers to do so would make it easier for public bodies to meet both their transparency obligations and obligations to ensure decisions are fair, lawful and non-discriminatory decision.

Transparency is just one example of how diffuse responsibility can undermine accountability. So, the Committee is right to focus both on who should be liable for different AI risks, and on when in the AI lifecycle obligations must take effect. A failure to do so would be particularly problematic when public bodies use AI to assist with rights-critical decisions, with potentially harmful consequences for marginalised individuals and communities who are often most reliant on public services (a point which PLP included in its evidence and which the Committee agreed with at [134]). For example, bias in a system may originate in training data or a system’s design, shaped by upstream decisions made by its developer.⁴

Conclusion 

The Committee’s report rightly emphasises that any AI Bill must ensure that public decision-making does not become less accountable through AI use. This cannot be done by focusing exclusively on frontier systems. It will require us to make public-sector AI use more transparent; clarify and enforce the legal standards that govern AI-assisted decision-making; and ensure responsibility sits with the right actors at the right stages of the AI lifecycle. 

Read Public Law Project’s full evidence here.

References

¹ Reflecting the distinction drawn in Leslie, M. (2024) ‘Securing meaningful transparency of public sector use of AI: comparative approaches across five jurisdictions‘, Public Law Project. 

² Article 22C, UK GDPR (as amended by the Data (Use and Access) Act 2025). 

³ As was generally required under the UK GDPR (subject to specified exemptions) before the Data (Use and Access) Act 2025 weakened the requirement so that it only applies where special category data (as defined in Article 9) has been used. 

⁴ See, notably, R (Bridges) v Chief Constable of South Wales Police [2020] EWCA Civ 1058. 

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Read the evidence here 

PLP welcomes the Committee’s findings on human rights and AI regulation. The Committee has today concluded that the UK’s approach to AI regulation is “patchy” and is not doing enough to protect people’s rights. It has called for a dedicated AI Bill and a new independent oversight body with the powers to effectively hold both developers and deployers of AI to account. 

The report draws on PLP’s evidence in several areas. The Committee has called for greater transparency and safeguards around government automated decision-making – agreeing with PLP that public bodies should be clearer with individuals when decisions about them are taken using AI, so people have enough information to understand and challenge such decisions. It also highlights PLP’s warning that the risks of poorly governed AI are likely to fall hardest on marginalised people and communities, particularly those who rely most on public services.

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Public bodies increasingly use automation for rights-critical decisions. As of 2025, PLP’s ‘Tracking Automated Government’ register has recorded 55 algorithmic tools used in administrative decision-making.

Automation has huge potential to improve the efficiency, accuracy, quality, and transparency of administrative decision-making. However, a lack of judicial scrutiny risks automated decision-making developing unlawfully, thereby undermining trust and hampering the realisation of potential benefits.

This project addresses the gap by examining transparency measures in public law litigation, asking the questions:

1. What information is required about automated public decision-making systems, and automated assisted decision-making systems, and at what stage, to bring effective public law litigation?
2. To what extent do existing transparency mechanisms meet the requirements identified in answer to question 1?
3. How can current mechanisms be reformed to meet the requirements identified in answer to question 1?
4. What are the considerations, challenges, and opportunities from a public body perspective in meeting the transparency requirements identified in answer to question 1?

What it will involve

PLP researchers Arianne Griffith, Caroline Selman, and Joseph Summers will be leading the project. They can be reached at pllias@publiclawproject.org.uk with any questions.

The research will be completed in three phases:

• Phase 1: Mapping the existing Judicial Review litigation landscape relevant to automated decision-making and doing detailed case analysis, focusing on key points in the litigation journey and the role of information availability in strategic decisions. Conducting semi-structure interviews and focus groups with legal practitioners, individuals and organisations involved in litigation regarding automated decision-making, and focus groups with public officials.
• Phase 2: Analysing existing transparency mechanisms against the information requirements identified in Phase 1.
• Phase 3: Formulating recommendations for improving transparency mechanisms, tested through workshops with interviewees and government officials.

How it will make a difference

Beyond the project, findings will also be used to develop practical training materials for practitioners and civil society organisations. Findings are likely to be relevant to existing transparency mechanisms, including the Government’s Automated Transparency Recording Standard; the UK General Data Protection Regulation; the Freedom of Information Act 2000; and the duty of candour in Judicial Review proceedings.

About Nuffield

The Nuffield Foundation is an independent charitable trust with a mission to advance social well-being. It funds research that informs social policy, primarily in Education, Welfare, and Justice. The Nuffield Foundation is the founder and co-funder of the Nuffield Council on Bioethics, the Ada Lovelace Institute and the Nuffield Family Justice Observatory. The Foundation has funded this project, but the views expressed are those of the authors and not necessarily the Foundation.

Bluesky: @nuffieldfoundation.org

LinkedIn: Nuffield Foundation

Website: nuffieldfoundation.org 

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