Trust in official statistics remains high but there’s still work to do

Curated on Posted on by Stefaan Verhulst

Article by Ian Diamond (UK): “..I’m excited about the potential of new data sources, and I want everyone in the UK to have the skills to understand and use the stats they allow us to create. With this in mind, we’re launching a whole host of new projects to bring our stats to the people:

How to videos

To benefit from stats, and be confident that they are reliable, we need to understand more about the data they have been derived from and how to read and use them.

Our new set of video guides are a great place to start, covering topics such as why data matters to how the ONS de-identifies them and where we get them from.

They are all available to watch on our YouTube channel.

Playground survey

During the 2023/2024 school year, we teamed up with the BBC and the Micro:bit Foundation to give children in primary schools the opportunity to take part in a nationwide playground survey.

The BBC Micro:bit Playground Survey is a wonderful way for children to learn data skills at an early age, getting to grips with data collection and analysis in a way that is relevant to their everyday lives, in a familiar and fun setting.

If children become data-literate now, they will be well prepared to navigate and take advantage of the huge amounts of data that will no doubt play an important role in their adult lives.

Keep an eye out for the results in October.

Navigating numbers – the ONS data education programme

We’ve also been busy developing a data education programme for students in further education or sixth form.

Navigating numbers: how data are used to create statistics includes a series of five classroom toolkits, exploring topics such as gender pay gaps, inflation, and health.

Created with the support of the Association of Colleges (AoC), this learning resource is free for teachers to use and available for download on the ONS website.

The ONS’s educational webinar series: Bringing data to life

If you want to learn more about measuring the cost of living or our nation’s health, then our new webinar series has you covered. These and other topics will be brought to life in this new series of online events, launching in September 2024…(More)”

A Diamond in the Rough: How Energy Consumption Data Can Boost Artificial Intelligence Startups and Accelerate the Green Transition

Curated on Posted on by Stefaan Verhulst

Policy brief by David Osimo and Anna Pizzamiglio: “…explores how the reuse of energy consumption data can foster a dynamic cleantech ecosystem and contribute to achieving the goals of the European Green Deal. Drawing on insights from EDDIE, a decentralised platform that standardises data formats and enhances data management across Europe, the brief outlines five key recommendations for shifting from a focus on data regulation to fostering innovation. These recommendations include: Enhancing User Experience, Nurturing the Cleantech Ecosystem, Strengthening Data Stewardship, Clarifying GDPR Guidelines, Eliminating Barriers to the Single Market…(More)”.

Making the Global Digital Compact a reality: Four steps to establish a responsible, inclusive and equitable data future.

Curated on Posted on by Stefaan Verhulst

Article by Stefaan Verhulst: “In September of this year, as world leaders assemble in New York for the 78th annual meeting of the United Nations (UN) General Assembly, they will confront a weighty agenda. War and peace will be at the forefront of conversations, along with efforts to tackle climate change and the ongoing migration crisis. Alongside these usual topics, however, the gathered dignitaries will also turn their attention to digital governance.

In 2021, the UN Secretary General proposed that a Global Digital Compact (GDC) be agreed upon that would “outline shared principles for an open, free and secure digital future for all”. The development of this Compact, which builds on a range of adjacent work streams at the UN, including activities related to the Sustainable Development Goals (SDGs), has now reached a vital inflection point. After a wide-ranging process of consultation, the General Assembly is expected to ratify the latest draft of the Digital Compact, which contains five key objectives and a commitment to thirteen cross-cutting principles. We have reached a rare moment of near-consensus in the global digital ecosystem, one that offers undeniable potential for revamping (and improving) our frameworks for global governance.

The Global Digital Compact will be agreed upon by UN Member States at the Summit of the Future at the United Nations Headquarters in New York, establishing guidelines for the responsible use and governance of digital technologies. 

The growing prominence of these objectives and principles at the seat of global governance is a welcome development. Each is essential to developing a healthy, safe and responsible digital ecosystem. In particular, the emphasis on better data governance is a step forward, as is the related call for an enhanced approach for international AI governance. Both cannot be separated: data governance is the bedrock of AI governance.

Yet now that we are moving toward ratification of the Compact, we must focus on the next crucial—and in some ways most difficult – step: implementation. This is particularly important given that the digital realm faces in many ways a growing crisis of credibility, marked by growing concerns over exclusion, extraction, concentrations of power, mis- and disinformation, and what we have elsewhere referred to as an impending “data winter”.

Manifesting the goals of the Compact to create genuine and lasting impact is thus critical. In what follows, we explore four key ways in which the Compact’s key objectives can be operationalized to create a more vibrant, responsive and free global digital commons…(More)”.

The Complexities of Differential Privacy for Survey Data

Curated on Posted on by Stefaan Verhulst

Paper by Jörg Drechsler & James Bailie: “The concept of differential privacy (DP) has gained substantial attention in recent years, most notably since the U.S. Census Bureau announced the adoption of the concept for its 2020 Decennial Census. However, despite its attractive theoretical properties, implementing DP in practice remains challenging, especially when it comes to survey data. In this paper we present some results from an ongoing project funded by the U.S. Census Bureau that is exploring the possibilities and limitations of DP for survey data. Specifically, we identify five aspects that need to be considered when adopting DP in the survey context: the multi-staged nature of data production; the limited privacy amplification from complex sampling designs; the implications of survey-weighted estimates; the weighting adjustments for nonresponse and other data deficiencies, and the imputation of missing values. We summarize the project’s key findings with respect to each of these aspects and also discuss some of the challenges that still need to be addressed before DP could become the new data protection standard at statistical agencies…(More)”.

Toward a citizen science framework for public policy evaluation

Curated on Posted on by Stefaan Verhulst

Paper by Giovanni Esposito et al: “This study pioneers the use of citizen science in evaluating Freedom of Information laws, with a focus on Belgium, where since its 1994 enactment, Freedom of Information’s effectiveness has remained largely unexamined. Utilizing participatory methods, it engages citizens in assessing transparency policies, significantly contributing to public policy evaluation methodology. The research identifies regional differences in Freedom of Information implementation across Belgian municipalities, highlighting that larger municipalities handle requests more effectively, while administrations generally show reluctance to respond to requests from perceived knowledgeable individuals. This phenomenon reflects a broader European caution toward well-informed requesters. By integrating citizen science, this study not only advances our understanding of Freedom of Information law effectiveness in Belgium but also advocates for a more inclusive, collaborative approach to policy evaluation. It addresses the gap in researchers’ experience with citizen science, showcasing its vast potential to enhance participatory governance and policy evaluation…(More)”.

Collaboration in Healthcare: Implications of Data Sharing for Secondary Use in the European Union

Curated on Posted on by Stefaan Verhulst

Paper by Fanni Kertesz: “The European healthcare sector is transforming toward patient-centred and value-based healthcare delivery. The European Health Data Space (EHDS) Regulation aims to unlock the potential of health data by establishing a single market for its primary and secondary use. This paper examines the legal challenges associated with the secondary use of health data within the EHDS and offers recommendations for improvement. Key issues include the compatibility between the EHDS and the General Data Protection Regulation (GDPR), barriers to cross-border data sharing, and intellectual property concerns. Resolving these challenges is essential for realising the full potential of health data and advancing healthcare research and innovation within the EU…(More)”.

Definitions, digital, and distance: on AI and policymaking

Curated on Posted on by Stefaan Verhulst

Article by Gavin Freeguard: “Our first question is less, ‘to what extent can AI improve public policymaking?’, but ‘what is currently wrong with policymaking?’, and then, ‘is AI able to help?’.

Ask those in and around policymaking about the problems and you’ll get a list likely to include:

  • the practice not having changed in decades (or centuries)
  • it being an opaque ‘dark art’ with little transparency
  • defaulting to easily accessible stakeholders and evidence
  • a separation between policy and delivery (and digital and other disciplines), and failure to recognise the need for agility and feedback as opposed to distinct stages
  • the challenges in measuring or evaluating the impact of policy interventions and understanding what works, with a lack of awareness, let alone sharing, of case studies elsewhere
  • difficulties in sharing data
  • the siloed nature of government complicating cross-departmental working
  • policy asks often being dictated by politics, with electoral cycles leading to short-termism, ministerial churn changing priorities and personal style, events prompting rushed reactions, or political priorities dictating ‘policy-based evidence making’
  • a rush to answers before understanding the problem
  • definitional issues about what policy actually is making it hard to get a hold of or develop professional expertise.  

If we’re defining ‘policy’ and the problem, we also need to define ‘AI’, or at least acknowledge that we are not only talking about new, shiny generative AI, but a world of other techniques for automating processes and analysing data that have been used in government for years.

So is ‘AI’ able to help? It could support us to make better use of a wider range of data more quickly; but it could privilege that which is easier to measure, strip data of vital context, and embed biases and historical assumptions. It could ‘make decisions more transparent (perhaps through capturing digital records of the process behind them, or by visualising the data that underpins a decision)’; or make them more opaque with ‘black-box’ algorithms, and distract from overcoming the very human cultural problems around greater openness. It could help synthesise submissions or generate ideas to brainstorm; or fail to compensate for deficiencies in underlying government knowledge infrastructure, and generate gibberish. It could be a tempting silver bullet for better policy; or it could paper over the cracks, while underlying technical, organisational and cultural plumbing goes unfixed. It could have real value in some areas, or cause harms in others…(More)”.

Using internet search data as part of medical research

Curated on Posted on by Stefaan Verhulst

Blog by Susan Thomas and Matthew Thompson: “…In the UK, almost 50 million health-related searches are made using Google per year. Globally there are 100s of millions of health-related searches every day. And, of course, people are doing these searches in real-time, looking for answers to their concerns in the moment. It’s also possible that, even if people aren’t noticing and searching about changes to their health, their behaviour is changing. Maybe they are searching more at night because they are having difficulty sleeping or maybe they are spending more (or less) time online. Maybe an individual’s search history could actually be really useful for researchers. This realisation has led medical researchers to start to explore whether individuals’ online search activity could help provide those subtle, almost unnoticeable signals that point to the beginning of a serious illness.

Our recent review found 23 studies have been published so far that have done exactly this. These studies suggest that online search activity among people later diagnosed with a variety of conditions ranging from pancreatic cancer and stroke to mood disorders, was different to people who did not have one of these conditions.

One of these studies was published by researchers at Imperial College London, who used online search activity to identify signals of women with gynaecological malignancies. They found that women with malignant (e.g. ovarian cancer) and benign conditions had different search patterns, up to two months prior to a GP referral. 

Pause for a moment, and think about what this could mean. Ovarian cancer is one of the most devastating cancers women get. It’s desperately hard to detect early – and yet there are signals of this cancer visible in women’s internet searches months before diagnosis?…(More)”.

Frontier AI: double-edged sword for public sector

Curated on Posted on by Stefaan Verhulst

Article by Zeynep Engin: “The power of the latest AI technologies, often referred to as ‘frontier AI’, lies in their ability to automate decision-making by harnessing complex statistical insights from vast amounts of unstructured data, using models that surpass human understanding. The introduction of ChatGPT in late 2022 marked a new era for these technologies, making advanced AI models accessible to a wide range of users, a development poised to permanently reshape how our societies function.

From a public policy perspective, this capacity offers the optimistic potential to enable personalised services at scale, potentially revolutionising healthcare, education, local services, democratic processes, and justice, tailoring them to everyone’s unique needs in a digitally connected society. The ambition is to achieve better outcomes than humanity has managed so far without AI assistance. There is certainly a vast opportunity for improvement, given the current state of global inequity, environmental degradation, polarised societies, and other chronic challenges facing humanity.

However, it is crucial to temper this optimism with recognising the significant risks. In their current trajectories, these technologies are already starting to undermine hard-won democratic gains and civil rights. Integrating AI into public policy and decision-making processes risks exacerbating existing inequalities and unfairness, potentially leading to new, uncontrollable forms of discrimination at unprecedented speed and scale. The environmental impacts, both direct and indirect, could be catastrophic, while the rise of AI-powered personalised misinformation and behavioural manipulation is contributing to increasingly polarised societies.

Steering the direction of AI to be in the public interest requires a deeper understanding of its characteristics and behaviour. To imagine and design new approaches to public policy and decision-making, we first need a comprehensive understanding of what this remarkable technology offers and its potential implications…(More)”.

Policies must be justified by their wellbeing-to-cost ratio

Curated on Posted on by Stefaan Verhulst

Article by Richard Layard: “…What is its value for money — that is, how much wellbeing does it deliver per (net) pound it costs the government? This benefit/cost ratio (or BCR) should be central to every discussion.

The science exists to produce these numbers and, if the British government were to require them of the spending departments, it would be setting an example of rational government to the whole world.

Such a move would, of course, lead to major changes in priorities. At the London School of Economics we have been calculating the benefits and costs of policies across a whole range of government departments.

In our latest report on value for money, the best policies are those that save the government more money than they cost — for example by getting people back to work. Classic examples of this are treatments for mental health. The NHS Talking Therapies programme now treats 750,000 people a year for anxiety disorders and depression. Half of them recover and the service demonstrably pays for itself. It needs to expand.

But we also need a parallel service for those addicted to alcohol, drugs and gambling. These individuals are more difficult to treat — but the savings if they recover are greater. Again, it will pay for itself. And so will the improved therapy service for children and young people that Labour has promised.

However, most spending policies do cost more than they save. For these it is crucial to measure the benefit/cost ratio, converting the wellbeing benefit into its monetary equivalent. For example, we can evaluate the wellbeing gain to a community of having more police and subsequently less crime. Once this is converted into money, we calculate that the benefit/cost ratio is 12:1 — very high…(More)”.