Framework for Governance of Indigenous Data (GID)

Curated on Posted on by Stefaan Verhulst

Framework by The National Indigenous Australians Agency (NIAA): “Australian Public Service agencies now have a single Framework for working with Indigenous data.

The National Indigenous Australians Agency will collaborate across the Australian Public Service to implement the Framework for Governance of Indigenous Data in 2024.

Commonwealth agencies are expected to develop a seven-year implementation plan, guided by four principles:

  1. Partner with Aboriginal and Torres Strait Islander people
  2. Build data-related capabilities
  3. Provide knowledge of data assets
  4. Build an inclusive data system

The Framework represents the culmination of over 18 months of co-design effort between the Australian Government and Aboriginal and Torres Strait Islander partners. While we know we have some way to go, the Framework serves as a significant step forward to improve the collection, use and disclosure of data, to better serve Aboriginal and Torres Strait Islander priorities.

The Framework places Aboriginal and Torres Strait Islander peoples at its core. Recognising the importance of authentic engagement, it emphasises the need for First Nations communities to have a say in decisions affecting them, including the use of data in government policy-making.

Acknowledging data’s significance in self-determination, the Framework provides a stepping stone towards greater awareness and acceptance by Australian Government agencies of the principles of Indigenous Data Sovereignty.

It offers practical guidance on implementing key aspects of data governance aligned with both Indigenous Data Sovereignty principles and the objectives of the Australian Government…(More)”.

Now we are all measuring impact — but is anything changing?

Curated on Posted on by Stefaan Verhulst

Article by Griffith Centre for Systems Innovation: “…Increasingly the landscape of Impact Measurement is crowded, dynamic and contains a diversity of frameworks and approaches — which can mean we end up feeling like we’re looking at alphabet soup.

As we’ve traversed this landscape we’ve tried to make sense of it in various ways, and have begun to explore a matrix to represent the constellation of frameworks, approaches and models we’ve encountered in the process. As shown below, the matrix has two axes:

The horizontal axis provides us with a “time” delineation. Dividing the left and right sides between retrospective (ex post) and prospective (ex-ante) approaches to measuring impact.

More specifically the retrospective quadrants include approaches/frameworks/models that ask about events in the past: What impact did we have? While the prospective quadrants include approaches that ask about the possible future: What impact will we have?

The vertical axis provides us with a “purpose” delineation. Dividing the upper and lower parts between Impact Measurement + Management and Evaluation

The top-level quadrants, Impact Measurement + Management, focus on methods that count quantifiable data (i.e. time, dollars, widgets). These frameworks tend to measure outputs from activities/interventions. They tend to ask the question what happened or what could happen and rely significantly on quantitative data.

The bottom-level Evaluation quadrants include a range of approaches that look at a broader range of questions beyond counting. They include questions like: what changed and why? What was or might the interrelationships between changes be? They tend to draw on a mixture of quantitative and qualitative data to create a more cohesive understanding of changes that occurred, are occurring or could occur.

A word of warning: As with all frameworks, this matrix is a “construct” — a way for us to engage in sense-making and to critically discuss how impact measurement is being undertaken in our current context. We are sharing this as a starting point for a broader discussion. We welcome feedback, reflections, and challenges around how we have represented different approaches — we are not seeking a ‘true representation’, but rather, a starting point for dialogue about how all the methods that now abound are connected, entangled and constructed…(More)”

Can Artificial Intelligence Bring Deliberation to the Masses?

Curated on Posted on by Stefaan Verhulst

Chapter by Hélène Landemore: “A core problem in deliberative democracy is the tension between two seemingly equally important conditions of democratic legitimacy: deliberation, on the one hand, and mass participation, on the other. Might artificial intelligence help bring quality deliberation to the masses? The answer is a qualified yes. The chapter first examines the conundrum in deliberative democracy around the trade-off between deliberation and mass participation by returning to the seminal debate between Joshua Cohen and Jürgen Habermas. It then turns to an analysis of the 2019 French Great National Debate, a low-tech attempt to involve millions of French citizens in a two-month-long structured exercise of collective deliberation. Building on the shortcomings of this process, the chapter then considers two different visions for an algorithm-powered form of mass deliberation—Mass Online Deliberation (MOD), on the one hand, and Many Rotating Mini-publics (MRMs), on the other—theorizing various ways artificial intelligence could play a role in them. To the extent that artificial intelligence makes the possibility of either vision more likely to come to fruition, it carries with it the promise of deliberation at the very large scale….(More)”

Embracing the Social in Social Science

Curated on Posted on by Stefaan Verhulst

Article by Jay Lloyd: “In a world where science is inextricably intermixed with society, the social sciences are essential to building trust in the scientific enterprise.

To begin thinking about why all the sciences should embrace the social in social science, I would like to start with cupcakes.

In my research, context is a recurring theme, so let me give you some context for cupcakes as metaphor. A few months ago, when I was asked to respond to an article in this magazine, I wrote: “In the production of science, social scientists can often feel like sprinkles on a cupcake: not essential. Social science is not the egg, the flour, or the sugar. Sprinkles are neither in the batter, nor do they see the oven. Sprinkles are a late addition. No matter the stylistic or aesthetic impact, they never alter the substance of the ‘cake’ in the cupcake.”

In writing these sentences, I was, and still am, hopeful that all kinds of future scientific research will make social science a key component of the scientific “batter” and bake social scientific knowledge, skill, and expertise into twenty-first-century scientific “cupcakes.”

But there are tensions and power differentials in the ways interdisciplinary science can be done. Most importantly, the formation of questions itself is a site of power. The questions we as a society ask science to address both reflect and create the values and power dynamics of social systems, whether the scientific disciplines recognize this influence or not. And some of those knowledge systems do not embrace the importance of insights from the social sciences because many institutions of science work hard to insulate the practice of science from the contingencies of society.

Moving forward, how do we, as researchers, develop questions that not only welcome intellectual variety within the sciences but also embrace the diversity represented in societies? As science continues to more powerfully blend, overlap, and intermix with society, embracing what social science can bring to the entire scientific enterprise is necessary. In order to accomplish these important goals, social concerns must be a key ingredient of the whole cupcake—not an afterthought, or decoration, but among the first thoughts…(More)”

Artificial Intelligence Opportunities for State and Local Departments Of Transportation

Curated on Posted on by Stefaan Verhulst

Report by the National Academies of Sciences, Engineering, and Medicine: “Artificial intelligence (AI) has revolutionized various areas in departments of transportation (DOTs), such as traffic management and optimization. Through predictive analytics and real-time data processing, AI systems show promise in alleviating congestion, reducing travel times, and enhancing overall safety by alerting drivers to potential hazards. AI-driven simulations are also used for testing and improving transportation systems, saving time and resources that would otherwise be needed for physical tests…(More)”.

A Generation of AI Guinea Pigs

Curated on Posted on by Stefaan Verhulst

Article by Caroline Mimbs Nyce: “This spring, the Los Angeles Unified School District—the second-largest public school district in the United States—introduced students and parents to a new “educational friend” named Ed. A learning platform that includes a chatbot represented by a small illustration of a smiling sun, Ed is being tested in 100 schools within the district and is accessible at all hours through a website. It can answer questions about a child’s courses, grades, and attendance, and point users to optional activities.

As Superintendent Alberto M. Carvalho put it to me, “AI is here to stay. If you don’t master it, it will master you.” Carvalho says he wants to empower teachers and students to learn to use AI safely. Rather than “keep these assets permanently locked away,” the district has opted to “sensitize our students and the adults around them to the benefits, but also the challenges, the risks.” Ed is just one manifestation of that philosophy; the school district also has a mandatory Digital Citizenship in the Age of AI course for students ages 13 and up.

Ed is, according to three first graders I spoke with this week at Alta Loma Elementary School, very good. They especially like it when Ed awards them gold stars for completing exercises. But even as they use the program, they don’t quite understand it. When I asked them if they know what AI is, they demurred. One asked me if it was a supersmart robot…(More)”.

Multi-disciplinary Perspectives on Citizen Science—Synthesizing Five Paradigms of Citizen Involvement

Curated on Posted on by Stefaan Verhulst

Paper by Susanne Beck, Dilek Fraisl, Marion Poetz and Henry Sauermann: “Research on Open Innovation in Science (OIS) investigates how open and collaborative practices influence the scientific and societal impact of research. Since 2019, the OIS Research Conference has brought together scholars and practitioners from diverse backgrounds to discuss OIS research and case examples. In this meeting report, we describe four session formats that have allowed our multi-disciplinary community to have productive discussions around opportunities and challenges related to citizen involvement in research. However, these sessions also highlight the need for a better understanding of the underlying rationales of citizen involvement in an increasingly diverse project landscape. Building on the discussions at the 2023 and prior editions of the conference, we outline a conceptual framework of five crowd paradigms and present an associated tool that can aid in understanding how citizen involvement in particular projects can help advance science. We illustrate this tool using cases presented at the 2023 conference, and discuss how it can facilitate discussions at future conferences as well as guide future research and practice in citizen science…(More)”.

Cryptographers Discover a New Foundation for Quantum Secrecy

Curated on Posted on by Stefaan Verhulst

Article by Ben Brubaker: “…Say you want to send a private message, cast a secret vote or sign a document securely. If you do any of these tasks on a computer, you’re relying on encryption to keep your data safe. That encryption needs to withstand attacks from codebreakers with their own computers, so modern encryption methods rely on assumptions about what mathematical problems are hard for computers to solve.

But as cryptographers laid the mathematical foundations for this approach to information security in the 1980s, a few researchers discovered that computational hardness wasn’t the only way to safeguard secrets. Quantum theory, originally developed to understand the physics of atoms, turned out to have deep connections to information and cryptography. Researchers found ways to base the security of a few specific cryptographic tasks directly on the laws of physics. But these tasks were strange outliers — for all others, there seemed to be no alternative to the classical computational approach.

By the end of the millennium, quantum cryptography researchers thought that was the end of the story. But in just the past few years, the field has undergone another seismic shift.

“There’s been this rearrangement of what we believe is possible with quantum cryptography,” said Henry Yuen, a quantum information theorist at Columbia University.

In a string of recent papers, researchers have shown that most cryptographic tasks could still be accomplished securely even in hypothetical worlds where practically all computation is easy. All that matters is the difficulty of a special computational problem about quantum theory itself.

“The assumptions you need can be way, way, way weaker,” said Fermi Ma, a quantum cryptographer at the Simons Institute for the Theory of Computing in Berkeley, California. “This is giving us new insights into computational hardness itself.”…(More)”.

Governing with Artificial Intelligence

Curated on Posted on by Stefaan Verhulst

OECD Report: “OECD countries are increasingly investing in better understanding the potential value of using Artificial Intelligence (AI) to improve public governance. The use of AI by the public sector can increase productivity, responsiveness of public services, and strengthen the accountability of governments. However, governments must also mitigate potential risks, building an enabling environment for trustworthy AI. This policy paper outlines the key trends and policy challenges in the development, use, and deployment of AI in and by the public sector. First, it discusses the potential benefits and specific risks associated with AI use in the public sector. Second, it looks at how AI in the public sector can be used to improve productivity, responsiveness, and accountability. Third, it provides an overview of the key policy issues and presents examples of how countries are addressing them across the OECD…(More)”.

World-first data storage infrastructure solution built by Iwi Māori, for Iwi Māori

Curated on Posted on by Stefaan Verhulst

Media release: “Te Kāhui Raraunga Charitable Trust (TKR) is on a mission to provide a data storage solution like no other in the pursuit of mana motuhake when it comes to data and the digital future. The concept of the network’s purpose is encapsulated in its name, Te Pā Tūwatawata.

And after six months of testing, the pilot phase has proven so successful, TKR expects Te Pā Tūwatawata to go live in early 2025.

The kaupapa involves the development of a distributed storage network to enable iwi, hapū and whānau Māori to collect, store, protect, access and control their own data.

Unlike other data storage solutions here and around the world, the servers used to connect the network will be based at the heart of where the data comes from – on marae, inside Māori organisations, or at other relevant iwi locations.

Three locations have been in the testing phase since late 2023, with the final network set to open with eight locations around the motu.

TKR Chairman, Rāhui Papa says the project is not only a world-first, but significantly embraces core concepts like kotahitanga – through sharing and scaling; and rangatiratanga – by giving iwi and hapū the power to control and make decisions over their own data.

“Iwi Māori Data sovereignty is at the heart of everything we do at TKR. As the world becomes more and more digital, we must adapt and be prepared to create our own infrastructure and empower our people with the know-how and skills to use it,” says Mr Papa.

Kirikowhai Mikaere, Lead Technician for the Data ILG and Te Kāhui Raraunga says traditionally, data centres are located in big warehouses, completely isolated from the source of the data and the people and whenua who have connection to it.

“With this kaupapa, we’re housing the data where it belongs, under the safe protection of the people that it means the most to. Additionally, with Te Pā Tūwatawata being located on-shore and owned by us, it meets the principles of Iwi Māori Data Sovereignty at the highest levels,” says Ms Mikaere…(More)”.