Science and technology’s contribution to the UK economy

Curated on Posted on by Stefaan Verhulst

UK House of Lords Primer: “It is difficult to accurately pinpoint the economic contribution of science and technology to the UK economy. This is because of the way sectors are divided up and reported in financial statistics. 

 For example, in September 2024 the Office for National Statistics (ONS) reported the following gross value added (GVA) figures by industry/sector for 2023:

  • £71bn for IT and other information service activities 
  • £20.6bn for scientific research and development 

This would amount to £91.6bn, forming approximately 3.9% of the total UK GVA of £2,368.7bn for 2023. However, a number of other sectors could also be included in these figures, for example: 

  • the manufacture of computer, certain machinery and electrical components (valued at £38bn in 2023) 
  • telecommunications (valued at £34.5bn) 

If these two sectors were included too, GVA across all four sectors would total £164.1bn, approximately 6.9% of the UK’s 2023 GVA. However, this would likely still exclude relevant contributions that happen to fall within the definitions of different industries. For example, the manufacture of spacecraft and related machinery falls within the same sector as the manufacture of aircraft in the ONS’s data (this sector was valued at £10.8bn for 2023).  

Alternatively, others have made estimates of the economic contribution of more specific sectors connected to science and technology. For example: 

  • Oxford Economics, an economic advisory firm, has estimated that, in 2023, the life sciences sector contributed over £13bn to the UK economy and employed one in every 121 employed people 
  • the government has estimated the value of the digital sector (comprising information technology and digital content and media) at £158.3bn for 2022
  • a 2023 government report estimated the value of the UK’s artificial intelligence (AI) sector at around £3.7bn (in terms of GVA) and that the sector employed around 50,040 people
  • the Energy and Climate Intelligence Unit, a non-profit organisation, reported estimates that the GVA of the UK’s net zero economy (encompassing sectors such as renewables, carbon capture, green and certain manufacturing) was £74bn in 2022/23 and that it supported approximately 765,700 full-time equivalent (FTE) jobs…(More)”.

Navigating Generative AI in Government

Curated on Posted on by Stefaan Verhulst

Report by the IBM Center for The Business of Government: “Generative AI refers to algorithms that can create realistic content such as images, text, music, and videos by learning from existing data patterns. Generative AI does more than just create content, it also serves as a user-friendly interface for other AI tools, making complex results easy to understand and use. Generative AI transforms analysis and prediction results into personalized formats, improving explainability by converting complicated data into understandable content. As Generative AI evolves, it plays an active role in collaborative processes, functioning as a vital collaborator by offering strengths that complement human abilities.

Generative AI has the potential to revolutionize government agencies by enhancing efficiency, improving decision making, and delivering better services to citizens, while maintaining agility and scalability. However, in order to implement generative AI solutions effectively, government agencies must address key questions—such as what problems AI can solve, data governance frameworks, and scaling strategies, to ensure a thoughtful and effective AI strategy. By exploring generic use cases, agencies can better understand the transformative potential of generative AI and align it with their unique needs and ethical considerations.

This report, which distills perspectives from two expert roundtable of leaders in Australia, presents 11 strategic pathways for integrating generative AI in government. The strategies include ensuring coherent and ethical AI implementation, developing adaptive AI governance models, investing in a robust data infrastructure, and providing comprehensive training for employees. Encouraging innovation and prioritizing public engagement and transparency are also essential to harnessing the full potential of AI…(More)”

What’s the Value of Privacy?

Curated on Posted on by Stefaan Verhulst

Brief by New America: “On a day-to-day basis, people make decisions about what information to share and what information to keep to themselves—guided by an inner privacy compass. Privacy is a concept that is both evocative and broad, often possessing different meanings for different people. The term eludes a common, static definition, though it is now inextricably linked to technology and a growing sense that individuals do not have control over their personal information. If privacy still, at its core, encompasses “the right to be left alone,” then that right is increasingly difficult to exercise in the modern era. 

The inability to meaningfully choose privacy is not an accident—in fact, it’s often by design. Society runs on data. Whether it is data about people’s personal attributes, preferences, or actions, all that data can be linked together, becoming greater than the sum of its parts. If data is now the world’s most valuable resource, then the companies that are making record profits off that data are highly incentivized to keep accessing it and obfuscating the externalities of data sharing. In brief, data use and privacy are “economically significant.” 

And yet, despite the pervasive nature of data collection, much of the public lacks a nuanced understanding of the true costs and benefits of sharing their data—for themselves and for society as a whole. People who have made billions by collecting and re-selling individual user data will continue to claim that it has little value. And yet, there are legitimate reasons why data should be shared—without a clear understanding of an issue, it is impossible to address it…(More)”.

G7 Toolkit for Artificial Intelligence in the Public Sector

Curated on Posted on by Stefaan Verhulst

Toolkit by OECD: “…a comprehensive guide designed to help policymakers and public sector leaders translate principles for safe, secure, and trustworthy Artificial Intelligence (AI) into actionable policies. AI can help improve the efficiency of internal operations, the effectiveness of policymaking, the responsiveness of public services, and overall transparency and accountability. Recognising both the opportunities and risks posed by AI, this toolkit provides practical insights, shares good practices for the use of AI in and by the public sector, integrates ethical considerations, and provides an overview of G7 trends. It further showcases public sector AI use cases, detailing their benefits, as well as the implementation challenges faced by G7 members, together with the emerging policy responses to guide and coordinate the development, deployment, and use of AI in the public sector. The toolkit finally highlights key stages and factors characterising the journey of public sector AI solutions…(More)”

Exploring New Frontiers of Citizen Participation in the Policy Cycle

Curated on Posted on by Stefaan Verhulst

OECD Discussion Paper: “… starts from the premise that democracies are endowed with valuable assets and that putting citizens at the heart of policy making offers an opportunity to strengthen democratic resilience. It draws on data, evidence and insights generated through a wide range of work underway at the OECD to identify systemic challenges and propose lines of action for the future. It calls for greater attention to, and investments in, citizen participation in policy making as one of the core functions of the state and the ‘life force’ of democratic governance. In keeping with the OECD’s strong commitment to providing a platform for diverse perspectives on challenging policy issues, it also offers a collection of thoughtprovoking opinion pieces by leading practitioners whose position as elected officials, academics and civil society leaders provides them with a unique vantage point from which to scan the horizon. As a contribution to an evolving field, this Discussion Paper offers neither a prescriptive framework nor a roadmap for governments but represents a step towards reaching a shared understanding of the very real challenges that lie ahead. It is also a timely invitation to all interested actors to join forces and take concerted action to embed meaningful citizen participation in policy making…(More)”.

Cross-border data flows in Africa: Continental ambitions and political realities

Curated on Posted on by Stefaan Verhulst

Paper by Melody Musoni, Poorva Karkare and Chloe Teevan: “Africa must prioritise data usage and cross-border data sharing to realise the goals of the African Continental Free Trade Area and to drive innovation and AI development. Accessible and shareable data is essential for the growth and success of the digital economy, enabling innovations and economic opportunities, especially in a rapidly evolving landscape.

African countries, through the African Union (AU), have a common vision of sharing data across borders to boost economic growth. However, the adopted continental digital policies are often inconsistently applied at the national level, where some member states implement restrictive measures like data localisation that limit the free flow of data.

The paper looks at national policies that often prioritise domestic interests and how those conflict with continental goals. This is due to differences in political ideologies, socio-economic conditions, security concerns and economic priorities. This misalignment between national agendas and the broader AU strategy is shaped by each country’s unique context, as seen in the examples of Senegal, Nigeria and Mozambique, which face distinct challenges in implementing the continental vision.

The paper concludes with actionable recommendations for the AU, member states and the partnership with the European Union. It suggests that the AU enhances support for data-sharing initiatives and urges member states to focus on policy alignment, address data deficiencies, build data infrastructure and find new ways to use data. It also highlights how the EU can strengthen its support for Africa’s datasharing goals…(More)”.

A shared destiny for public sector data

Curated on Posted on by Stefaan Verhulst

Blog post by Shona Nicol: “As a data professional, it can sometime feel hard to get others interested in data. Perhaps like many in this profession, I can often express the importance and value of data for good in an overly technical way. However when our biggest challenges in Scotland include eradicating child poverty, growing the economy and tackling the climate emergency, I would argue that we should all take an interest in data because it’s going to be foundational in helping us solve these problems.

Data is already intrinsic to shaping our society and how services are delivered. And public sector data is a vital component in making sure that services for the people of Scotland are being delivered efficiently and effectively. Despite an ever growing awareness of the transformative power of data to improve the design and delivery of services, feedback from public sector staff shows that they can face difficulties when trying to influence colleagues and senior leaders around the need to invest in data.

A vision gap

In the Scottish Government’s data maturity programme and more widely, we regularly hear about the challenges data professionals encounter when trying to enact change. This community tell us that a long-term vision for public sector data for Scotland could help them by providing the context for what they are trying to achieve locally.

Earlier this year we started to scope how we might do this. We recognised that organisations are already working to deliver local and national strategies and policies that relate to data, so any vision had to be able to sit alongside those, be meaningful in different settings, agnostic of technology and relevant to any public sector organisation. We wanted to offer opportunities for alignment, not enforce an instruction manual…(More)”.

Emerging technologies in the humanitarian sector

Curated on Posted on by Stefaan Verhulst

Report and project by Rand: “Emerging technologies have often been explored in the humanitarian sector through small scale pilot projects, testing their application in a specific context with limited opportunities to replicate the testing across various contexts. The level of familiarity and knowledge of technological development varies across the specific types of humanitarian activities undertaken and technology areas considered.

The study team identified five promising technology areas for the humanitarian sector that could be further explored out to 2030:

  • Advanced manufacturing systems are likely to offer humanitarians opportunities to produce resources and tools in an operating environment characterised by scarcity, the rise of simultaneous crises, and exposure to more intense and severe climate events.
  • Early Warning Systems are likely to support preparedness and response efforts across the humanitarian sector while multifactorial crises are likely to arise.
  • Camp monitoring systems are likely to support efforts not only to address security risks, but also support planning and management activities of sites or the health and wellbeing of displaced populations.
  • Coordination platforms are likely to enhance data collection and information-sharing across various humanitarian stakeholders for the development of timely and bespoke crisis response.
  • Privacy-enhancing technologies (PETs) can support ongoing efforts to comply with increased data privacy and data protection requirements in a humanitarian operating environment in which data collection will remain necessary.

Beyond these five technology areas, the study team also considered three innovation journey opportunities:

  • The establishment of a technology horizon scanning coalition
  • Visioning for emerging technologies in crisis recovery
  • An emerging technology narrative initiative.

To accompany the deployment of specific technologies in the humanitarian sector, the study team also developed a four-step approach aimed to identify specific guidance needs for end-users and humanitarian practitioners…(More)”.

External Researcher Access to Closed Foundation Models

Curated on Posted on by Stefaan Verhulst

Report by Esme Harrington and Dr. Mathias Vermeulen: “…addresses a pressing issue: independent researchers need better conditions for accessing and studying the AI models that big companies have developed. Foundation models — the core technology behind many AI applications — are controlled mainly by a few major players who decide who can study or use them.

What’s the problem with access?

  • Limited access: Companies like OpenAI, Google and others are the gatekeepers. They often restrict access to researchers whose work aligns with their priorities, which means independent, public-interest research can be left out in the cold.
  • High-end costs: Even when access is granted, it often comes with a hefty price tag that smaller or less-funded teams can’t afford.
  • Lack of transparency: These companies don’t always share how their models are updated or moderated, making it nearly impossible for researchers to replicate studies or fully understand the technology.
  • Legal risks: When researchers try to scrutinize these models, they sometimes face legal threats if their work uncovers flaws or vulnerabilities in the AI systems.

The research suggests that companies need to offer more affordable and transparent access to improve AI research. Additionally, governments should provide legal protections for researchers, especially when they are acting in the public interest by investigating potential risks…(More)”.

Machines of Loving Grace

Curated on Posted on by Stefaan Verhulst

Essay by Dario Amodei: “I think and talk a lot about the risks of powerful AI. The company I’m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I’m a pessimist or “doomer” who thinks AI will be mostly bad or dangerous. I don’t think that at all. In fact, one of my main reasons for focusing on risks is that they’re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.

In this essay I try to sketch out what that upside might look like—what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I’m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one…(More)”.