Protecting Policy Space for Indigenous Data Sovereignty Under International Digital Trade Law

Curated on Posted on by Stefaan Verhulst

Paper by Andrew D. Mitchell and Theo Samlidis: “The impact of economic agreements on Indigenous peoples’ broader rights and interests has been subject to ongoing scrutiny. Technological developments and an increasing emphasis on Indigenous sovereignty within the digital domain have given rise to a global Indigenous data sovereignty movement, surfacing concerns about how international economic law impacts Indigenous peoples’ sovereignty over their data. This Article examines the policy space certain governments have reserved under international economic agreements to introduce measures for protecting Indigenous data or digital sovereignty (IDS). We argue that treaty countries have secured, under recent international digital trade chapters and agreements, the benefits of a comprehensive economic treaty and sufficient regulatory autonomy to protect Indigenous data sovereignty…(More)”

UN adopts Chinese resolution with US support on closing the gap in access to artificial intelligence

Curated on Posted on by Stefaan Verhulst

Article by Edith Lederer: “The U.N. General Assembly adopted a Chinese-sponsored resolution with U.S. support urging wealthy developed nations to close the widening gap with poorer developing countries and ensure that they have equal opportunities to use and benefit from artificial intelligence.

The resolution approved Monday follows the March 21 adoption of the first U.N. resolution on artificial intelligence spearheaded by the United States and co-sponsored by 123 countries including China. It gave global support to the international effort to ensure that AI is “safe, secure and trustworthy” and that all nations can take advantage of it.

Adoption of the two nonbinding resolutions shows that the United States and China, rivals in many areas, are both determined to be key players in shaping the future of the powerful new technology — and have been cooperating on the first important international steps.

The adoption of both resolutions by consensus by the 193-member General Assembly shows widespread global support for their leadership on the issue.

Fu Cong, China’s U.N. ambassador, told reporters Monday that the two resolutions are complementary, with the U.S. measure being “more general” and the just-adopted one focusing on “capacity building.”

He called the Chinese resolution, which had more than 140 sponsors, “great and far-reaching,” and said, “We’re very appreciative of the positive role that the U.S. has played in this whole process.”

Nate Evans, spokesperson for the U.S. mission to the United Nations, said Tuesday that the Chinese-sponsored resolution “was negotiated so it would further the vision and approach the U.S. set out in March.”

“We worked diligently and in good faith with developing and developed countries to strengthen the text, ensuring it reaffirms safe, secure, and trustworthy AI that respects human rights, commits to digital inclusion, and advances sustainable development,” Evans said.

Fu said that AI technology is advancing extremely fast and the issue has been discussed at very senior levels, including by the U.S. and Chinese leaders.

“We do look forward to intensifying our cooperation with the United States and for that matter with all countries in the world on this issue, which … will have far-reaching implications in all dimensions,” he said…(More)”.

AI for social good: Improving lives and protecting the planet

Curated on Posted on by Stefaan Verhulst

McKinsey Report: “…Challenges in scaling AI for social-good initiatives are persistent and tough. Seventy-two percent of the respondents to our expert survey observed that most efforts to deploy AI for social good to date have focused on research and innovation rather than adoption and scaling. Fifty-five percent of grants for AI research and deployment across the SDGs are $250,000 or smaller, which is consistent with a focus on targeted research or smaller-scale deployment, rather than large-scale expansion. Aside from funding, the biggest barriers to scaling AI continue to be data availability, accessibility, and quality; AI talent availability and accessibility; organizational receptiveness; and change management. More on these topics can be found in the full report.

While overcoming these challenges, organizations should also be aware of strategies to address the range of risks, including inaccurate outputs, biases embedded in the underlying training data, the potential for large-scale misinformation, and malicious influence on politics and personal well-being. As we have noted in multiple recent articles, AI tools and techniques can be misused, even if the tools were originally designed for social good. Experts identified the top risks as impaired fairness, malicious use, and privacy and security concerns, followed by explainability (Exhibit 2). Respondents from not-for-profits expressed relatively more concern about misinformation, talent issues such as job displacement, and effects of AI on economic stability compared with their counterparts at for-profits, who were more often concerned with IP infringement…(More)”

The Potential of Artificial Intelligence for the SDGs and Official Statistics

Curated on Posted on by Stefaan Verhulst

Report by Paris21: “Artificial Intelligence (AI) and its impact on people’s lives is growing rapidly. AI is already leading to significant developments from healthcare to education, which can contribute to the efficient monitoring and achievement of the Sustainable Development Goals (SDGs), a call to action to address the world’s greatest challenges. AI is also raising concerns because, if not addressed carefully, its risks may outweigh its benefits. As a result, AI is garnering increasing attention from National Statistical Offices (NSOs) and the official statistics community as they are challenged to produce more, comprehensive, timely, and highquality data for decision-making with limited resources in a rapidly changing world of data and technologies and in light of complex and converging global issues from pandemics to climate change. This paper has been prepared as an input to the “Data and AI for Sustainable Development: Building a Smarter Future” Conference, organized in partnership with The Partnership in Statistics for Development in the 21st Century (PARIS21), the World Bank and the International Monetary Fund (IMF). Building on case studies that examine the use of AI by NSOs, the paper presents the benefits and risks of AI with a focus on NSO operations related to sustainable development. The objective is to spark discussions and to initiate a dialogue around how AI can be leveraged to inform decisions and take action to better monitor and achieve sustainable development, while mitigating its risks…(More)”.

AI for Good: Applications in Sustainability, Humanitarian Action, and Health

Curated on Posted on by Stefaan Verhulst

Book by Juan M. Lavista Ferres and William B. Weeks: “…an insightful and fascinating discussion of how one of the world’s most recognizable software companies is tacking intractable social problems with the power of artificial intelligence (AI). In the book, you’ll learn about how climate change, illness and disease, and challenges to fundamental human rights are all being fought using replicable methods and reusable AI code.

The authors also provide:

  • Easy-to-follow, non-technical explanations of what AI is and how it works
  • Examinations of how healthcare is being improved, climate change is being addressed, and humanitarian aid is being facilitated around the world with AI
  • Discussions of the future of AI in the realm of social benefit organizations and efforts

An essential guide to impactful social change with artificial intelligence, AI for Good is a must-read resource for technical and non-technical professionals interested in AI’s social potential, as well as policymakers, regulators, NGO professionals, and, and non-profit volunteers…(More)”.

Predicting IMF-Supported Programs: A Machine Learning Approach

Curated on Posted on by Stefaan Verhulst

Paper by Tsendsuren Batsuuri, Shan He, Ruofei Hu, Jonathan Leslie and Flora Lutz: “This study applies state-of-the-art machine learning (ML) techniques to forecast IMF-supported programs, analyzes the ML prediction results relative to traditional econometric approaches, explores non-linear relationships among predictors indicative of IMF-supported programs, and evaluates model robustness with regard to different feature sets and time periods. ML models consistently outperform traditional methods in out-of-sample prediction of new IMF-supported arrangements with key predictors that align well with the literature and show consensus across different algorithms. The analysis underscores the importance of incorporating a variety of external, fiscal, real, and financial features as well as institutional factors like membership in regional financing arrangements. The findings also highlight the varying influence of data processing choices such as feature selection, sampling techniques, and missing data imputation on the performance of different ML models and therefore indicate the usefulness of a flexible, algorithm-tailored approach. Additionally, the results reveal that models that are most effective in near and medium-term predictions may tend to underperform over the long term, thus illustrating the need for regular updates or more stable – albeit potentially near-term suboptimal – models when frequent updates are impractical…(More)”.

Responsible Data Re-use in Developing Countries: Social Licence through Public Engagement

Curated on Posted on by Stefaan Verhulst

Report by Stefaan Verhulst, Laura Sandor, Natalia Mejia Pardo, Elena Murray and Peter Addo: “The datafication era has transformed the technological landscape, digitizing multiple areas of human life and offering opportunities for societal progress through the re-use of digital data. Developing countries stand to benefit from datafication but are faced with challenges like insufficient data quality and limited infrastructure. One of the primary obstacles to unlocking data re-use lies in agency asymmetries—disparities in decision-making authority among stakeholders—which fuel public distrust. Existing consent frameworks amplify the challenge, as they are individual-focused, lack information, and fail to address the nuances of data re-use. To address these limitations, a Social License for re-use becomes imperative—a community-focused approach that fosters responsible data practices and benefits all stakeholders. This shift is crucial for establishing trust and collaboration, and bridging the gap between institutions, governments, and citizens…(More)”.

Breaking the Gridlock

Curated on Posted on by Stefaan Verhulst

UNDP Human Development Report 2024: “We can do better than this. Better than runaway climate change and pandemics. Better than a spate of unconstitutional transfers of power amid a rising, globalizing tide of populism. Better than cascading human rights violations and unconscionable massacres of people in their homes and civic venues, in hospitals, schools and shelters.

We must do better than a world always on the brink, a socioecological house of cards. We owe it to ourselves, to each other, to our children and their children.

We have so much going for us.

We know what the global challenges are and who will be most affected by them. And we know there will surely be more that we cannot anticipate today.

We know which choices offer better opportunities for peace, shared prosperity and sustainability, better ways to navigate interacting layers of uncertainty and interlinked planetary surprises.

We enjoy unprecedented wealth know-how and technology—unimaginable to our ancestors—that with more equitable distribution and use could power bold and necessary choices for peace and for sustainable, inclusive human development on which peace depends…

In short, why are we so stuck? And how do we get unstuck without resorting myopically to violence or isolationism? These questions motivate the 2023–2024 Human Development Report.

Sharp questions belie their complexity; issues with power disparities at their core often defy easy explanation. Magic bullets entice but mislead—siren songs peddled by sloganeering that exploits group-based grievances. Slick solutions and simple recipes poison our willingness to do the hard work of overcoming polarization.

Geopolitical quagmires abound, driven by shifting power dynamics among states and by national gazes yanked inward by inequalities, insecurity and polarization, all recurring themes in this and recent Human Development Reports. Yet we need not sit on our hands simply because great power competition is heating up while countries underrepresented in global governance seek a greater say in matters of global import. Recall that global cooperation on smallpox eradication and protection of the ozone layer, among other important issues such as nuclear nonproliferation, happened over the course of the Cold War…(More)”.

Scaling Up Development Impact

Curated on Posted on by Stefaan Verhulst

Book by Isabel Guerrero with Siddhant Gokhale and Jossie Fahsbender: “Today, nearly one billion people lack electricity, over three billion lack clean water, and 750 million lack basic literacy skills. Many of these challenges could be solved with existing solutions, and technology enables us to reach the last mile like never before. Yet, few solutions attain the necessary scale to match the size of these challenges. Scaling Up Development Impact offers an analytical framework, a set of practical tools, and adaptive evaluation techniques to accompany the scaling process. It presents rich organizational experiences that showcase real-world journeys toward increased impact…(More)”.

Data Must Speak: Positive Deviance Research

Curated on Posted on by Stefaan Verhulst

Report by UNICEF: “Despite the global learning crisis, even in the most difficult contexts, there are some “positive deviant” schools that outperform others in terms of learning, gender equality, and retention. Since 2019, in line with UNICEF’s Foundational Literacy and Numeracy Programme, Data Must Speak (DMS) research identifies these positive deviant schools, explores which behaviours and practices make them outperform others, and investigates how these could be implemented in lower performing schools in similar contexts. DMS research uses a sequential, participatory, mixed-methods approach to improve uptake, replicability, and sustainability. The research is being undertaken in 14 countries across Africa, Asia, and Latin America…(More)”.

The 5 Stages of Data Must Speak Research