DeepSeek or DeepShock? What the public sector needs to know
DeepSeek, a China-based AI developer, is shaking up the market with the unveiling of affordable, open source large language models (LLMs) that run on minimal processing power.
The government has an ambitious and exciting strategy to position the UK as a global leader in artificial intelligence and to use this strategy to transform the ways that it delivers public services.
But AI is only as effective as the data that fuels it. So to bring its vision to life, the government must treat its vast data resources as a strategic asset. This means ensuring that data is accurate, well structured, representative, accessible and inclusive across government and the civil service. And there’s an appealing side benefit too - public data carries significant economic value. The Open Data Institute believes that public-sector data sharing could generate social and economic benefits worth between 0.1% and 1.5% of the UK GDP.
There’s more to the government’s vision for AI than operational efficiency and cost savings. It views AI as an important tool to fundamentally improve citizen perceptions of public services, and the ways citizens interact with them.
For much too long, these services have been criticised for being slow, rigid, impersonal, difficult to navigate or resource-heavy. Data-driven AI offers a chance for government to change this narrative by delivering modern digital services that are personalised, efficient, and intuitive.
For much too long, public services have faced criticism for being slow, rigid, impersonal, or difficult to navigate. But the digital transformation efforts we’ve witnessed over the past decade in the public sector have made significant strides in addressing these issues. This focus on digital transformation has enabled new services that are more user-friendly and efficient.
Data-driven AI has the potential to accelerate this progress even further, adding new dimensions, greater personalisation, efficiency, and intuitive interactions to the ways that citizens are serviced.
It means that by building on top of the existing successes of digital transformation, a data-driven AI public service can become even more responsive and people-focused. It creates an exciting ‘next-generation’ way to align closely with the expectations of today’s digitally driven and time-poor society.
For data-driven systems to serve the needs of all citizens, they must be built with data quality and inclusivity at their core. Ensuring the data reflects the reality and diversity of society must be treated as an integral part of the critical path to their discovery, development and implementation.
This is because incomplete or biased datasets have the potential to increase inequality, creating negative social commentary and eroding citizen trust in public services. It could even inadvertently exclude or not recognise citizens who have protected characteristics. All of this means that relying on incomplete or biased datasets could result in far-reaching political consequences or even hamper takeup of the service.
Inclusivity in the public sector must address everything - from ensuring technology is accessible to those with disabilities, colour blindness, or comprehension challenges, to supporting individuals who lack the skills or confidence to navigate digital services like some elderly people.
By analysing data and identifying where these groups face barriers, AI tools can be designed and configured to simplify and automate digital interactions. This could become an iterative process of continuously adding and adapting more accessible interfaces, providing access to alternative channels like call centres (which in themselves could be automated using AI), or human in-person support thanks to the capacity savings that AI brings.
Ensuring that the data is of the right quality, and is inclusive, helps address many blind spots, ensuring that services are equitable, accessible and consumable by all, regardless of individual levels of human or technological ability.
The moment the quality of data is nailed, it becomes a powerful tool to improve efficiency and service delivery. And in this sense, data can help the public sector to move from reactive to proactive service delivery.
The potential use cases are vast - most will be routine, but many are impactful too. For example, the public sector will be able to rely on AI to analyse its data sources to proactively tackle common blockers and the way that it responds to national incidents or crises.
Imagine if weather caused both the M1 and M6 motorways to close, causing major disruptions to the critical national backbones that connect many of Britain’s largest cities. AI could help keep the nation moving by helping National Highways plan its response, prioritising cleanups and repairs, and automatically rerouting traffic via alternative roads. And by rapidly analysing historical data on freight movement, commuter patterns, and congestion levels, AI could find other non-road transportation and connection possibilities. This would allow civil servants to proactively contain the economic fallout of the disruption, protecting critical supply chains and maintaining workforce productivity.
The power of data-driven AI lies not only in its ability to respond to incidents but also in its potential to transform day-to-day interactions. By analysing patterns and identifying efficiencies in routine activities, the public sector can deliver services that feel seamless, proactive and citizen-centric.
This isn’t just a step forward in efficiency, it’s a once in a generation opportunity to rethink how public services are offered. Proactivity, enabled by data-driven AI, is Public Sector 2.0
Here are five practical actions that should ideally be taken to achieve good standards of data quality and inclusivity:
Establish clear policies and accountability structures for data collection, storage, sharing, and usage. It helps to ensure that data remains consistently accurate, secure, and accessible between departments. A robust governance framework also goes a long way to identifying gaps, preventing duplication, and creating a unified approach.
Adopt universal standards for data formats and classifications to enable interoperability between systems. It lessens the effort in adapting fragmented or siloed datasets and ensures smoother integration of AI tools across various public services. On top of this, standardisation also simplifies the process of linking datasets as a way of uncovering detailed insights. The government’s AI Opportunities Action Plan addresses this through a National Data Library that will serve as an integrated and accessible data infrastructure that runs across the public sector, providing vast social and economic benefits.
Implement ongoing quality checks and validation processes. This helps to find and rectify errors or inconsistencies in the data. It is also helpful to regularly audit datasets for accuracy, completeness, and relevance because it’ll maintain trust in the insights the data generates. Innovate regularly to further improve efficiency and reliability.
Design data collection processes to reflect the full diversity of the population, including the vulnerable and less-represented groups in society. It is also sensible to constantly question how extensive the data’s diversity really is, and to dig into areas where it might be incomplete or biased.
Engage with colleagues across departments to build levels of data literacy and encourage a mindset that values data as a critical asset to aid decision-making. A culture of cross-departmental collaboration and innovation ensures the entire Public Sector remains agile and responsive to fresh opportunities and evolving needs.
The potential of the government’s AI strategy is remarkable. If it reaches just a fraction of its potential in the public sector, data-driven AI won’t just be another tool to bring about efficiency, but it’ll become a catalyst for deep transformation.
This is an exciting transformational moment in the way that the public sector serves citizens.
But achieving the strategy relies on embedding data quality, inclusivity, and accessibility into every layer of the approach. It demands a cultural shift that recognises data as the cornerstone of decision-making and the driving force behind meaningful AI innovation. With this foundation in place, the delivery of public services can be impactful and benefit generations to come.
DeepSeek, a China-based AI developer, is shaking up the market with the unveiling of affordable, open source large language models (LLMs) that run on minimal processing power.
The government has an ambitious and exciting strategy to position the UK as a global leader in artificial intelligence and to use this strategy to transform the ways that it delivers public services. But AI is only as effective as the data that fuels it.
The UK government has now unveiled its AI Opportunities Action Plan, accepting all 50 recommendations made by tech entrepreneur and Advanced Research and Invention Agency chair, Matt Clifford CBE. It hopes to position Britain as a global leader in artificial intelligence, enhancing public services and driving economic growth.
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