Uniting the UK’s Health Data: A Huge Opportunity for Society’

Curated on Posted on by Stefaan Verhulst

The Sudlow Review (UK): “…Surveys show that people in the UK overwhelmingly support the use of their health data with appropriate safeguards to improve lives. One of the review’s recommendations calls for continued engagement with patients, the public, and healthcare professionals to drive forward developments in health data research.

The review also features several examples of harnessing health data for public benefit in the UK, such as the national response to the COVID-19 pandemic. But successes like these are few and far between due to complex systems and governance. The review reveals that:

  • Access to datasets is difficult or slow, often taking months or even years.
  • Data is accessible for analysis and research related to COVID-19, but not to tackle other health conditions, such as other infectious diseases, cancer, heart disease, stroke, diabetes and dementia.
  • More complex types of health data generally don’t have national data systems (for example, most lab testing data and radiology imaging).
  • Barriers like these can delay or prevent hundreds of studies, holding back progress that could improve lives…

The Sudlow Review’s recommendations provide a pathway to establishing a secure and trusted health data system for the UK:

  1. Major national public bodies with responsibility for or interest in health data should agree a coordinated joint strategy to recognise England’s health data for what they are: a critical national infrastructure.
  2. Key government health, care and research bodies should establish a national health data service in England with accountable senior leadership.
  3. The Department of Health and Social Care should oversee and commission ongoing, coordinated, engagement with patients, public, health professionals, policymakers and politicians.
  4. The health and social care departments in the four UK nations should set a UK-wide approach to streamline data access processes and foster proportionate, trustworthy data governance.
  5. National health data organisations and statistical authorities in the four UK nations should develop a UK-wide system for standards and accreditation of secure data environments (SDEs) holding data from the health and care system…(More)”.

The need for climate data stewardship: 10 tensions and reflections regarding climate data governance

Curated on Posted on by Stefaan Verhulst

Paper by Stefaan Verhulst: “Datafication—the increase in data generation and advancements in data analysis—offers new possibilities for governing and tackling worldwide challenges such as climate change. However, employing data in policymaking carries various risks, such as exacerbating inequalities, introducing biases, and creating gaps in access. This paper articulates 10 core tensions related to climate data and its implications for climate data governance, ranging from the diversity of data sources and stakeholders to issues of quality, access, and the balancing act between local needs and global imperatives. Through examining these tensions, the article advocates for a paradigm shift towards multi-stakeholder governance, data stewardship, and equitable data practices to harness the potential of climate data for the public good. It underscores the critical role of data stewards in navigating these challenges, fostering a responsible data ecology, and ultimately contributing to a more sustainable and just approach to climate action and broader social issues…(More)”.

Normative Foundations for International Data Governance: Goals and Principles

Curated on Posted on by Stefaan Verhulst

Proposed Foundations by the United Nations System Chief Executives Board for Coordination: “…suggests a set of common goals and principles that could form the normative basis for international data governance. The document does not present universally agreed goals and principles but seeks to provide an input to ongoing and future deliberations on the topic, including within the context of follow-up to the Global Digital Compact and other intergovernmental processes. Prepared by the HLCP Working Group on international data governance, the document seeks to complement existing standards and principles and builds on the Group’s previous paper “International Data Governance: Pathways to Progress”,  which outlined a vision and steps towards the promotion of data governance grounded in human rights and sustainable development through a multistakeholder consultative approach.

Central to the document are three overarching goals: value, trust, and equity. Value highlights the necessity for an enabling environment that fosters responsible data use and reuse, alongside the critical importance of interoperability to facilitate effective data sharing. Trust is cultivated through a human rights-based approach, prioritizing data protection and privacy, while ensuring accountability and high standards of data quality throughout the lifecycle. Equity is promoted by empowering individuals and communities exercise control over their personal data and ensuring that the benefits of data access are distributed fairly, particularly to vulnerable and marginalized groups…(More)”.

Once Upon a Crime: Towards Crime Prediction from Demographics and Mobile Data

Curated on Posted on by Stefaan Verhulst

Paper by Andrey Bogomolov, Bruno Lepri, Jacopo Staiano, Nuria Oliver, Fabio Pianesi, and Alex Pentland: “In this paper, we present a novel approach to predict crime in a geographic space from multiple data sources, in particular mobile phone and demographic data. The main contribution of the proposed approach lies in using aggregated and anonymized human behavioral data derived from mobile network activity to tackle the crime prediction problem. While previous research efforts have used either background historical knowledge or offenders’ profiling, our findings support the hypothesis that aggregated human behavioral data captured from the mobile network infrastructure, in combination with basic demographic information, can be used to predict crime. In our experimental results with real crime data from London we obtain an accuracy of almost 70% when predicting whether a specific area in the city will be a crime hotspot or not. Moreover, we provide a discussion of the implications of our findings for data-driven crime analysis…(More)”.

Towards effective governance of justice data

Curated on Posted on by Stefaan Verhulst

OECD working paper: “…explores the role of data governance in advancing people-centred justice systems. It outlines the objectives, values, and practices necessary to harness data effectively, drawing on OECD policy instruments. The paper provides actionable insights for policymakers aiming to implement data-driven justice reforms. It also addresses the challenges and opportunities presented by digital transformation in the justice sector, advocating for a strategic approach that balances innovation with the protection of fundamental rights. It incorporates lessons from data governance activities and experiences in justice and other relevant sectors. This paper is essential reading for those involved in modernisation of justice and data governance…(More)”.

Determinants of behaviour and their efficacy as targets of behavioural change interventions

Curated on Posted on by Stefaan Verhulst

Paper by Dolores Albarracín, Bita Fayaz-Farkhad & Javier A. Granados Samayoa: “Unprecedented social, environmental, political and economic challenges — such as pandemics and epidemics, environmental degradation and community violence — require taking stock of how to promote behaviours that benefit individuals and society at large. In this Review, we synthesize multidisciplinary meta-analyses of the individual and social-structural determinants of behaviour (for example, beliefs and norms, respectively) and the efficacy of behavioural change interventions that target them. We find that, across domains, interventions designed to change individual determinants can be ordered by increasing impact as those targeting knowledge, general skills, general attitudes, beliefs, emotions, behavioural skills, behavioural attitudes and habits. Interventions designed to change social-structural determinants can be ordered by increasing impact as legal and administrative sanctions; programmes that increase institutional trustworthiness; interventions to change injunctive norms; monitors and reminders; descriptive norm interventions; material incentives; social support provision; and policies that increase access to a particular behaviour. We find similar patterns for health and environmental behavioural change specifically. Thus, policymakers should focus on interventions that enable individuals to circumvent obstacles to enacting desirable behaviours rather than targeting salient but ineffective determinants of behaviour such as knowledge and beliefs…(More)”

Innovation amnesia: Technology as a substitute for politics

Curated on Posted on by Stefaan Verhulst

Paper by Nathan Schneider: “…outlines a theory of amnesia in the face of innovation: when apparent technological innovations occasion the disregard of preexisting cultural, legal, and infrastructural norms. Innovation amnesia depends on cultural patterns that appear to be increasingly widespread: the valorization of technological innovation and the sensation of limited political space for reforming social arrangements. The resulting amnesia is by default an extension of existing structural inequalities. If innovations arise through deploying concentrated private wealth, the amnesia will likely target institutions that facilitate collective power among less powerful people. Up and down social hierarchies, however, achieving amnesia through innovation can bear irresistible allure. When other paths for structural change become mired in inertia or gridlock, amnesia may appear to be the only available pathway to reform. The purpose of a theory of amnesia is to assist affected communities in noticing it when it occurs and wielding it to their advantage, particularly through mobilizing self-governance around moments of innovation…(More)”.

The Rise of AI-Generated Content in Wikipedia

Curated on Posted on by Stefaan Verhulst

Paper by Creston Brooks, Samuel Eggert, and Denis Peskoff: “The rise of AI-generated content in popular information sources raises significant concerns about accountability, accuracy, and bias amplification. Beyond directly impacting consumers, the widespread presence of this content poses questions for the long-term viability of training language models on vast internet sweeps. We use GPTZero, a proprietary AI detector, and Binoculars, an open-source alternative, to establish lower bounds on the presence of AI-generated content in recently created Wikipedia pages. Both detectors reveal a marked increase in AI-generated content in recent pages compared to those from before the release of GPT-3.5. With thresholds calibrated to achieve a 1% false positive rate on pre-GPT-3.5 articles, detectors flag over 5% of newly created English Wikipedia articles as AI-generated, with lower percentages for German, French, and Italian articles. Flagged Wikipedia articles are typically of lower quality and are often self-promotional or partial towards a specific viewpoint on controversial topics…(More)”

AI and Data Science for Public Policy

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue by Kenneth Benoit: “Artificial intelligence (AI) and data science are reshaping public policy by enabling more data-driven, predictive, and responsive governance, while at the same time producing profound changes in knowledge production and education in the social and policy sciences. These advancements come with ethical and epistemological challenges surrounding issues of bias, transparency, privacy, and accountability. This special issue explores the opportunities and risks of integrating AI into public policy, offering theoretical frameworks and empirical analyses to help policymakers navigate these complexities. The contributions explore how AI can enhance decision-making in areas such as healthcare, justice, and public services, while emphasising the need for fairness, human judgment, and democratic accountability. The issue provides a roadmap for harnessing AI’s potential responsibly, ensuring it serves the public good and upholds democratic values…(More)”.

Federated Data Infrastructures for Scientific Use

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Policy paper by the German Council for Scientific Information Infrastructures: “…provides an overview and a comparative in-depth analysis of the emerging research (and research related) data infrastructures NFDI, EOSC, Gaia-X and the European Data Spaces. In addition, the Council makes recommendations for their future development and coordination. The RfII notes that access to genuine high-quality research data and related core services is a matter of basic public supply and strongly advises to achieve coherence between the various initiatives and approaches…(More)”.