Despite its intentions to be a tech superpower, the UK may lack the key infrastructure necessary to participate – let alone lead – in the AI boom, according to the latest white paper form the Open Data Institute (ODI).

The ODI outlined some of the main weaknesses in the UK’s tech infrastructure, including a lack of robust governance frameworks for data protection and AI adoption and deployment.

The paper argues that the potential for emerging AI technologies to transform industries such as diagnostics and personalised education shows great promise. Yet significant challenges and risks are attached to wide scale adoption, including the reliance on a handful of machine learning datasets in the case of generative AI.

The UK’s non-statutory approach to AI regulations has meant that a lack of robust governance could pose significant risk to both adoption and deployment, as inadequate data governance can lead to biases and unethical practices, undermining the trust and reliability of AI applications in critical areas such as healthcare, finance, and public services.

The ODI also found that the UK public needs safeguarding against the risk of personal data being used illegally to train AI models, and steps must be taken to address the ongoing risks of AI models leaking personal data inadvertently via user prompts.

These risks are exacerbated by a lack of transparency that is hampering efforts to address biases, remove harmful content, and ensure compliance with legal standards.

Key transparency information about data sources, copyright, and inclusion of personal information and more is rarely included by systems flagged within Partnership for AI’s AI Incidents Database, which collects alerts and date designed to mitigate potential risks associated with AI.

Also key to this is an update to intellectual property law to protect creative industries.

The ODI also found that labour rights will need to be safeguarded as AI continues to be adopted and deployed, and the AI market will require scrutiny as the increasing price of high-quality AI training data excludes potential innovators and academia.

Based on its research, the ODI is calling for the new government to take five actions that will allow the UK to benefit from the opportunities presented by AI while mitigating potential harms:

1. Ensure broad access to high-quality, well-governed public and private sector data to foster a diverse, competitive AI market.
2. Enforce data protection and labour rights in the data supply chain
3. Empower people to have more of a say in the sharing and use of data for AI
4. Update our intellectual property regime to ensure AI models are trained in ways that prioritise trust and empowerment of stakeholders
5. Increase transparency around the data used to train high-risk AI models

To provide a clearer picture of how data transparency varies across different types of system providers, the ODI is developing a new ‘AI data transparency index.’

“If the UK is to benefit from the extraordinary opportunities presented by AI, the government must look beyond the hype and attend to the fundamentals of a robust data ecosystem built on sound governance and ethical foundations,” Sir Nigel Shadbolt, executive chair and co-founder of the ODI, said.

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“We must build a trustworthy data infrastructure for AI because the feedstock of high-quality AI is high-quality data.

“The UK has the opportunity to build better data governance systems for AI that ensure we are best placed to take advantage of technological innovations and create economic and social value whilst guarding against potential risks.”

Before the General Election, Labour’s Manifesto outlined plans for a National Data Library to bring together existing research programmes and help deliver data-enabled public services.

However, the ODI says that, first, the UK government needs to ensure the data is AI-ready. As well as being accessible and trustworthy, data must meet agreed standards, which require a data assurance and quality assessment infrastructure.

The ODI’s recent research has also found that currently – with a few exceptions – AI training datasets typically lack robust governance measures throughout the AI life cycle, posing safety, security, trust, and ethical challenges related to data protection and fair labour practices. These are all issues that need to be addressed if the government is to make good on its plans.