Development Archives | Page 4 of 545 | Digital Watch Observatory

Code for America highlights challenges in measuring AI use in public services in the US states

According to Code for America, AI is reshaping how public services are delivered across the United States, yet adoption remains uneven and difficult to measure. They added that state governments are rapidly embracing AI through low-risk pilot programmes while still lacking clear frameworks to evaluate impact.

The report describes AI adoption as following a staged progression beginning with readiness, where leadership structures, workforce skills and infrastructure are developed.

Piloting then introduces experimentation through sandboxes and limited deployments, while implementation embeds AI into operational systems such as fraud detection, document automation, research support and citizen-facing chat assistants.

The report also notes that despite growing experimentation, most US states have not yet transitioned into fully operational and measurable systems.

Leading states, including Utah, New Jersey, Pennsylvania, North Carolina, Maryland, Texas and Vermont, are advancing institutional capabilities required to govern AI as a long-term public asset. Others, such as West Virginia, Wyoming, Nebraska, Alaska, Florida and Kansas, remain at earlier stages of readiness and adoption.

The report identifies measuring outcomes as a key challenge. It states that while AI promises efficiency gains and cost reductions, short-term deployment often increases workload for public employees before benefits materialise.

It adds that evaluation frameworks remain underdeveloped, leaving governments with strong governance structures but limited visibility into real performance improvements.

According to Amanda Renteria, CEO of Code for America, the opportunity extends beyond adoption alone, as governments must shape AI in ways that are human-centred and grounded in measurable public outcomes.

The report suggests that states that succeed in aligning technology with real community impact will move beyond experimentation and define the future of public service in the AI era.

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DeepSeek V4 trails US frontier by eight months, according to CAISI evaluation

The Centre for AI Standards and Innovation, a unit within the US National Institute of Standards and Technology, has published an evaluation of DeepSeek V4, finding that it is the most capable Chinese-developed model it has assessed to date, but that it still trails leading US models overall.

According to the evaluation, DeepSeek V4 was tested in April 2026 and lagged top US frontier models by about eight months in CAISI’s aggregate capability measure. The report says the model performed strongly across several domains and was the most capable PRC model assessed by CAISI so far.

The findings highlight DeepSeek V4’s strongest results in mathematics, software engineering, and natural sciences. In mathematics, the model achieved particularly strong scores on benchmarks such as OTIS-AIME-2025 and PUMaC 2024, while still lagging the top US systems in overall capability.

CAISI also says DeepSeek V4 is more cost-efficient than other models of similar capability. Compared with the most cost-competitive US reference model, GPT-5.4 mini, it was more cost-efficient on five of seven benchmarks, ranging from 53% less expensive to 41% more expensive depending on the task.

The report notes that CAISI selected a US reference model for comparison and evaluated both benchmark performance and token pricing. It adds that DeepSeek’s lower cost profile makes it notable in the current frontier model landscape, even though it remains behind the leading US systems in aggregate capability.

The Center for AI Standards and Innovation (CAISI), a unit within the US National Institute of Standards and Technology (NIST), has published an evaluation of DeepSeek V4 Pro. has published an evaluation of DeepSeek V4 Pro, finding that the model is the most capable Chinese-developed model it has assessed to date, but still trails leading US models overall.

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US military expands AI deployment across classified networks

The US Department of Defence has announced agreements with leading technology firms to deploy advanced AI capabilities across classified military networks. The initiative forms part of a broader effort to position the United States as a more AI-enabled military power.

Companies including OpenAI, Google, Microsoft, Amazon Web Services, NVIDIA, and SpaceX are reported to be involved in supporting deployment within high-security Impact Level 6 and 7 environments. The integration is intended to improve data synthesis, situational awareness, and operational decision-making across defence systems.

The department’s internal platform, GenAI.mil, is also being presented as a central part of this push, with senior officials describing it as a way to put advanced AI tools into the hands of personnel across the department and across different classification levels.

Officials have emphasised that maintaining access to a range of AI providers is important to avoid vendor lock-in and preserve long-term flexibility. In that sense, the move reflects a wider attempt to strengthen national security through advanced technology while keeping the military AI stack diversified rather than dependent on a single company or model family. However, this is an inference based on the reported Pentagon framing of the agreements.

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Victorian officials outline approach to managing AI risks in public sector

Ian Pham at the Victorian Managed Insurance Authority (VMIA) outlined approaches to managing AI adoption during the PSN Victorian Government Cyber Security Showcase. Organisations face the challenge of adopting AI while maintaining effective risk management as these systems become more embedded in government operations.

Cybersecurity teams have traditionally operated with a risk-averse approach focused on minimising threats. Such an approach can slow innovation when applied to AI systems used in public sector environments.

A shift towards managing risk in line with organisational objectives is presented as necessary. This includes prioritising relevant risks and moving from reactive responses towards supporting decision-making processes.

AI adoption involves secure environments for experimentation with defined guardrails, including synthetic or non-sensitive data, monitoring mechanisms, usage conditions, and identity and access controls. Exposure can then be increased gradually, supported by governance and continuous reassessment.

Risks linked to AI systems include data leakage, privacy concerns, unauthorised use, and data quality issues. These risks are described as requiring visibility and management, alongside organisational awareness and engagement to support confidence in AI use.

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Singapore’s HTX signs agreements to advance public safety technologies

The Home Team Science and Technology Agency has signed 10 agreements with partners across government, industry and academia to advance public safety technologies. The announcement was made at MTX 2026.

The partnerships focus on areas including AI, space technology and cybersecurity, aiming to accelerate development of next-generation capabilities for public safety operations.

Several agreements involve industry collaboration to apply commercial innovations, while others expand research links with academic institutions to deepen expertise in areas such as forensics and autonomous systems.

HTX said the partnerships will strengthen collaboration, innovation and knowledge sharing across the public safety ecosystem. The agreements were announced at an event in Singapore.

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Brazil’s Ceará state introduces AI assistant for document review

The Junta Comercial do Estado do Ceará has launched an AI-powered document analysis assistant, marking the first public-facing AI service by the Government of the State of Ceará in Brazil. The initiative was announced through an official statement.

The tool is integrated into the Jucec services portal and acts as a pre-analysis system. It reviews documents, cross-checks data and identifies inconsistencies before formal submission.

Officials say the AI system allows users to correct errors in advance, reducing delays and improving efficiency. The analysis is conducted quickly and clearly highlights issues for businesses and accountants.

The initiative is part of wider efforts to modernise public services and support digital transformation in Brazil.

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New MIT research hub targets future of advanced computation

IBM and the MIT Schwarzman College of Computing have launched the MIT-IBM Computing Research Lab, expanding their long-running partnership into a broader research agenda focused on AI, algorithms, and quantum computing.

The initiative builds on the earlier MIT-IBM Watson AI Lab and reflects the rapid shift towards AI deployment and emerging quantum technologies.

The lab aims to explore the convergence of AI and quantum systems, including hybrid computing models that combine classical infrastructure with next-generation quantum hardware.

Research priorities include efficient AI architectures, advanced optimisation methods, and new algorithmic frameworks designed to improve reliability, transparency, and real-world applicability of machine learning systems.

Alongside AI development, the lab will focus on quantum algorithms for complex scientific problems in fields such as chemistry, biology, and materials science. Work will also address the mathematical foundations of modelling dynamic systems, with potential applications ranging from improved weather prediction to financial forecasting and supply chain optimisation.

Leaders from both MIT and IBM describe the lab as a platform for shaping the next generation of computing systems through integrated advances in AI and quantum technologies.

Why does it matter?

The launch of the MIT-IBM Computing Research Lab signals a broader shift in how foundational computing breakthroughs are now being shaped through close academic–industry collaboration.

As AI and quantum computing converge, the boundaries of what machines can model, predict, and optimise are being fundamentally redefined.

From a wider perspective, these developments could reshape entire sectors, including healthcare, finance, climate science, and global logistics, by enabling faster and more accurate problem-solving at scales that classical systems cannot handle.

The direction of this research also matters for technological sovereignty, as countries and institutions compete to lead in next-generation computing capabilities that will underpin future economic and scientific power.

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European Commission urges fast rollout of EU age verification app

The European Commission has adopted a recommendation urging member states to accelerate the rollout of the EU age verification app and make it available by the end of the year. The recommendation says the app can be deployed either as a standalone solution or integrated into a European Digital Identity Wallet.

According to the Commission, the app is intended to let users prove they meet a required age threshold without disclosing their exact age, identity, or other personal details. The Commission has also published a blueprint for the system, leaving it to member states to customise and produce the app for their citizens.

The recommendation sets out actions for member states to support rapid availability and interoperability, including implementation plans and coordination to ensure the swift rollout of the solution across the EU.

The measure forms part of the EU’s wider approach to protecting minors online under the Digital Services Act, which requires online platforms to ensure a high level of privacy, safety, and security for minors.

Executive Vice-President Henna Virkkunen said: ‘Effective and privacy-preserving age verification is the next piece of the puzzle that we are getting closer to completing, as we work towards an online space where our children are safe and empowered to use positively and responsibly without restricting the rights of adults.’

Why does it matter?

The move takes age verification in the EU from a general policy objective to a more concrete implementation phase. Rather than leaving platforms and member states to develop separate solutions, the Commission is trying to steer the bloc towards a common privacy-preserving model that can work across borders.

That matters for both child protection and regulatory coherence, because if countries adopt incompatible systems or move at very different speeds, enforcement under the Digital Services Act could become uneven in practice.

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UK links digital waste tracking to enforcement in Waste Crime Action Plan

The UK Department for Environment, Food & Rural Affairs (Defra) has linked the rollout of digital waste tracking to its wider effort to tackle waste crime in England, presenting stronger traceability as part of its Waste Crime Action Plan.

Defra says waste crime costs the economy an estimated £1 billion a year and continues to damage communities, the environment, and legitimate businesses. Its Waste Crime Action Plan for England combines tighter regulation, stronger enforcement, and faster clean-up of the most harmful illegal waste sites.

A central part of that approach is digital waste tracking. Defra says the system will create a near real-time record of where waste goes at each stage of its journey, making it harder for criminal operators to exploit gaps in the existing system. Better-quality data across the waste chain is also intended to support a more intelligence-led approach to regulation and enforcement.

The department has presented the launch of the public beta for the ‘Report Receipt of Waste’ service as a major step in that process. The service allows waste receivers to submit data on the waste they handle. It is intended to support a more accountable system in which waste movements can be tracked, verified, and audited.

Defra describes digital waste tracking as a shift away from a largely paper-based and bureaucratic system. For legitimate businesses, the department says the new approach should reduce administrative burdens while improving clarity and confidence across the sector.

The rollout will take place in phases. Defra says the first phase begins with the public beta and will become mandatory from October 2026 for licensed or permitted operators of waste receiving sites, including recycling centres, landfills, and treatment facilities. Around 12,000 permitted waste receiving sites will be covered in the first phase, with more than 100,000 operators expected to come into scope as the service expands.

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Latvia shows average AI tool adoption levels

Recent data from Eurostat and the Central Statistical Bureau of Latvia highlights that around one-third of people in Latvia use AI tools. Latvian Public Media reports that usage broadly matches the EU average.

In Latvia, 35.1 percent of internet users reported using AI in 2025, slightly above the EU figure of 33 percent. Adoption is highest among younger people, with nearly three-quarters of those aged 16 to 24 using such tools.

Usage varies across demographics, with higher rates among educated users and employed individuals. Men use AI slightly more than women, while regional differences show stronger uptake in the Riga area.

Many non-users say they see no need for AI, while others cite a lack of skills or awareness. The findings were reported based on official data in Latvia.

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