The Overlooked Importance of Data Reuse in AI Infrastructure

Curated on Posted on by Stefaan Verhulst

Essay by Oxford Insights and The Data Tank: “Employing data stewards and embedding responsible data reuse principles in the programme or ecosystem and within participating organisations is one of the pathways forward. Data stewards are proactive agents responsible for catalysing collaboration, tackling these challenges and embedding data reuse practices in their organisations. 

The role of Chief Data Officer for government agencies has become more common in recent years and we suggest the same needs to happen with the role of the Chief Data Steward. Chief Data Officers are mostly focused on internal data management and have a technical focus. With the changes in the data governance landscape, this profession needs to be reimagined and iterated. Embedded in both the demand and the supply sides of data, data stewards are proactive agents empowered to create public value by re-using data and data expertise. They are tasked to identify opportunities for productive cross-sectoral collaboration, and proactively request or enable functional access to data, insights, and expertise. 

One exception comes from New Zealand. The UN has released a report on the role of data stewards and National Statistical Offices (NSOs) in the new data ecosystem. This report provides many use-cases that can be adopted by governments seeking to establish such a role. In New Zealand, there is an appointed Government Chief Data Steward, who is in charge of setting the strategic direction for government’s data management, and focuses on data reuse altogether. 

Data stewards can play an important role in organisations leading data reuse programmes. Data stewards would be responsible for responding to the challenges with participation introduced above. 

A Data Steward’s role includes attracting participation for data reuse programmes by:

  • Demonstrating and communicating the value proposition of data reuse and collaborations, by engaging in partnerships and steering data reuse and sharing among data commons, cooperatives, or collaborative infrastructures. 
  • Developing responsible data lifecycle governance, and communicating insights to raise awareness and build trust among stakeholders; 

A Data Steward’s role includes maintaining and scaling participation for data reuse programmes by:

  • Maintaining trust by engaging with wider stakeholders and establishing clear engagement methodologies. For example, by embedding a social license, data stewards assure the digital self determination principle is embedded in data reuse processes. 
  • Fostering sustainable partnerships and collaborations around data, via developing business cases for data sharing and reuse, and measuring impact to build the societal case for data collaboration; and
  • Innovating in the sector by turning data to decision intelligence to ensure that insights derived from data are more effectively integrated into decision-making processes…(More)”.

Democratic Resilience: Moving from Theoretical Frameworks to a Practical Measurement Agenda

Curated on Posted on by Stefaan Verhulst

Paper by Nicholas Biddle, Alexander Fischer, Simon D. Angus, Selen Ercan, Max Grömping, andMatthew Gray: “Global indices and media narratives indicate a decline in democratic institutions, values, and practices. Simultaneously, democratic innovators are experimenting with new ways to strengthen democracy at local and national levels. These both suggest democracies are not static; they evolve as society, technology and the environment change.

This paper examines democracy as a resilient system, emphasizing the role of applied analysis in shaping effective policy and programs, particularly in Australia. Grounded in adaptive processes, democratic resilience is the capacity of a democracy to identify problems, and collectively respond to changing conditions, balancing institutional stability with transformative. It outlines the ambition of a national network of scholars, civil society leaders, and policymakers to equip democratic innovators with practical insights and foresight underpinning new ideas. These insights are essential for strengthening both public institutions, public narratives and community programs.

We review current literature on resilient democracies and highlight a critical gap: current measurement efforts focus heavily on composite indices—especially trust—while neglecting dynamic flows and causal drivers. They focus on the descriptive features and identify weaknesses, they do not focus on the diagnostics or evidence to what strengths democracies. This is reflected in the lack of cross-sector networked, living evidence systems to track what works and why across the intersecting dynamics of democratic practices. To address this, we propose a practical agenda centred on three core strengthening flows of democratic resilience: trusted institutions, credible information, and social inclusion.

The paper reviews six key data sources and several analytic methods for continuously monitoring democratic institutions, diagnosing causal drivers, and building an adaptive evidence system to inform innovation and reform. By integrating resilience frameworks and policy analysis, we demonstrate how real-time monitoring and analysis can enable innovation, experimentation and cross-sector ingenuity.

This article presents a practical research agenda connecting a national network of scholars and civil society leaders. We suggest this agenda be problem-driven, facilitated by participatory approaches to asking and prioritising the questions that matter most. We propose a connected approach to collectively posing key questions that matter most, expanding data sources, and fostering applied ideation between communities, civil society, government, and academia—ensuring democracy remains resilient in an evolving global and national context…(More)”.

Policymaking assessment framework

Curated on Posted on by Stefaan Verhulst

Guide by the Susan McKinnon Foundation: “This assessment tool supports the measurement of the quality of policymaking processes – both existing and planned – across  sectors. It provides a flexible framework for rating public policy processes using information available in the public domain. The framework’s objective is to simplify the path towards best practice, evidence-informed policy.

It is intended to accommodate the complexity of policymaking processes and reflect the realities and context within which policymaking is undertaken. The criteria can be tailored for different policy problems and policy types and applied across sectors and levels of government.

The framework is structured around five key domains:

  1. understanding the problem
  2. engagement with stakeholders and partners
  3. outcomes focus
  4. evidence for the solution, and
  5. design and communication…(More)”.

Must NLP be Extractive?

Curated on Posted on by Stefaan Verhulst

Paper by Steven Bird: “How do we roll out language technologies across a world with 7,000 languages? In one story, we scale the successes of NLP further into ‘low-resource’ languages, doing ever more with less. However, this approach does not recognise the fact that – beyond the 500 institutional languages – the remaining languages are oral vernaculars. These speech communities interact with the outside world using a ‘con-
tact language’. I argue that contact languages are the appropriate target for technologies like speech recognition and machine translation, and that the 6,500 oral vernaculars should be approached differently. I share stories from an Indigenous community where local people reshaped an extractive agenda to align with their relational agenda. I describe the emerging paradigm of Relational NLP and explain how it opens the way to non-extractive methods and to solutions that enhance human agency…(More)”

Social licence for health data

Curated on Posted on by Stefaan Verhulst

Evidence Brief by NSW Government: “Social licence, otherwise referred to as social licence to operate, refers to an approval or consensus from the society members or the community for the users, either as a public or private enterprise or individual, to use their health data as desired or accepted under certain conditions. Social licence is a dynamic and fluid concept and is subject to change over time often influenced by societal and contextual factors.
The social licence is usually indicated through ongoing engagement and negotiations with the public and is not a contract with strict terms and conditions. It is, rather, a moral and ethical responsibility assumed by the data users based on trust and legitimacy, It supplements the techno-legal mechanisms to regulate the use of data.
For example, through public engagement, certain values and principles can emerge as pertinent to public support for using their data. Similarly, the public may view certain activities relating to their data use as acceptable and beneficial, implying their permission for certain activities or usecase scenarios. Internationally, although not always explicitly referred to as a social licence, the most common approach to establishing public trust and support and identifying common grounds or agreements on acceptable practices for use of data is through public engagement. Engagement methods and mechanisms for gaining public perspectives vary across countries (Table 1).
− Canada – Health Data Research Network Canada reports on social licence for uses of health data, based on deliberative discussions with 20 experienced public and patient advisors. The output is a list of agreements and disagreements on what uses and users of health data have social licence.
− New Zealand – In 2022, the Ministry of Health commissioned a survey on public perceptions on use of personal health information. This report identified conditions under which the public supports the re-use of their data…(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)”

Harnessing the feed: social media for mental health information and support 

Curated on Posted on by Stefaan Verhulst

Report by ReachOut: “…highlights how a social media ban could cut young people off from vital mental health support, including finding that 73 per cent of young people in Australia turn to social media when it comes to support for their mental health.

Based on research with over 2000 young people, the report found a range of benefits for young people seeking mental health support via social media (predominantly TikTok, YouTube and Instagram). 66 per cent of young people surveyed reported increased awareness about their mental health because of relevant content they accessed via social media, 47 per said they had looked for information about how to get professional mental health support on social media and 40 per cent said they sought professional support after viewing mental health information on social media. 

Importantly, half of young people with a probable mental health condition said that they were searching for mental health information or support on social media because they don’t have access to professional support. 

However, young people also highlighted a range of concerns about social media via the research. 38 per cent were deeply concerned about harmful mental health content they have come across on platforms and 43 per cent of the young people who sought support online were deeply concerned about the addictive nature of social media.  

The report highlights young people’s calls for social media to be safer. They want: an end to addictive features like infinite scroll, more control over the content they see, better labelling of mental health information from credible sources, better education and more mental health information provided across platforms…(More)”.

Data-driven decisions: the case for randomised policy trials

Curated on Posted on by Stefaan Verhulst

Speech by Andrew Leigh: “…In 1747, 31-year-old Scottish naval surgeon James Lind set about determining the most effective treatment for scurvy, a disease that was killing thousands of sailors around the world. Selecting 12 sailors suffering from scurvy, Lind divided them into six pairs. Each pair received a different treatment: cider; sulfuric acid; vinegar; seawater; a concoction of nutmeg, garlic and mustard; and two oranges and a lemon. In less than a week, the pair who had received oranges and lemons were back on active duty, while the others languished. Given that sulphuric acid was the British Navy’s main treatment for scurvy, this was a crucial finding.

The trial provided robust evidence for the powers of citrus because it created a credible counterfactual. The sailors didn’t choose their treatments, nor were they assigned based on the severity of their ailment. Instead, they were randomly allocated, making it likely that difference in their recovery were due to the treatment rather than other characteristics.

Lind’s randomised trial, one of the first in history, has attained legendary status. Yet because 1747 was so long ago, it is easy to imagine that the methods he used are no longer applicable. After all, Lind’s research was conducted at a time before electricity, cars and trains, an era when slavery was rampant and education was reserved for the elite. Surely, some argue, ideas from such an age have been superseded today.

In place of randomised trials, some put their faith in ‘big data’. Between large-scale surveys and extensive administrative datasets, the world is awash in data as never before. Each day, hundreds of exabytes of data are produced. Big data has improved the accuracy of weather forecasts, permitted researchers to study social interactions across racial and ethnic lines, enabled the analysis of income mobility at a fine geographic scale and much more…(More)”

Policy for responsible use of AI in government

Curated on Posted on by Stefaan Verhulst

Policy by the Australian Government: “The Policy for the responsible use of AI in government ensures that government plays a leadership role in embracing AI for the benefit of Australians while ensuring its safe, ethical and responsible use, in line with community expectations. The policy:

  • provides a unified approach for government to engage with AI confidently, safely and responsibly, and realise its benefits
  • aims to strengthen public trust in government’s use of AI by providing enhanced transparency, governance and risk assurance
  • aims to embed a forward leaning, adaptive approach for government’s use of AI that is designed to evolve and develop over time…(More)”.

Policy fit for the future: the Australian Government Futures primer

Curated on Posted on by Stefaan Verhulst

Primer by Will Hartigan and Arthur Horobin: “Futures is a systematic exploration of probable, possible and preferable future developments to inform present-day policy, strategy and decision-making. It uses multiple plausible scenarios of the future to anticipate and make sense of disruptive change. It is also known as strategic foresight...

This primer provides an overview of Futures methodologies and their practical application to policy development and advice. It is a first step for policy teams and officers interested in Futures: providing you with a range of flexible tools, ideas and advice you can adapt to your own policy challenges and environments.

This primer was developed by the Policy Projects and Taskforce Office in the Department of Prime Minister and Cabinet. We have drawn on expertise from inside and outside of government –including through our project partners, the Futures Hub at the National Security College in the Australian National University. 

This primer has been written by policy officers, for policy officers –with a focus on practical and tested approaches that can support you to create policy fit for the future…(More)”.