Article by Madalsa Singh: “Census data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. With the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential privacy) and post-processing 2020 census data to reduce the risk of identification of individual respondents. Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. White Americans have lowest variability, followed by Latinos, Asian, and Black Americans. DP underestimates pollution disparities for SO2 and PM2.5 while overestimates the pollution disparities for PM10…(More)”.
An Action Plan Towards a “New Deal on Data” in Africa
Blog by Charlie Martial Ngounou, Hannah Chafetz, Sampriti Saxena, Adrienne Schmoeker, Stefaan G. Verhulst, & Andrew J. Zahuranec: “To help accelerate responsible data use across the African data ecosystem, AfroLeadership with the support of The GovLab hosted two Open Data Action Labs in March and April 2023 focused on advancing open data policy across Africa. The Labs brought together domain experts across the African data ecosystem to build upon the African Union’s Data Policy Framework and develop an instrument to help realize Agenda 2063.
The Labs included discussions about the current state of open data policy and what could be involved in a “New Deal on Data” across the African continent. Specifically, the Labs explored how open data across African countries and communities could become more:
- Purpose-led: how to strengthen the value proposition of and incentives for open data and data re-use, and become purpose-led?
- Practice-led: how to accelerate the implementation of open data and data re-use policies, moving from policy to practice?
- People-led: how to trigger engagement, collaboration and coordination with communities and stakeholders toward advancing data rights, community interests, and diversity of needs and capacities?
Following the Labs, the organizing team conducted a brainstorming session to synthesize the insights gathered and develop an action plan towards a “New Deal on Data” for Africa. Below we provide a summary of our action plan. The action plan includes four vehicles that could make progress towards becoming purpose-, practice-, and people-led. These include:
- A “New Deal” Observatory: An online resource that takes stock of the the current state of open data policies, barriers to implementation, and use cases from the local to continental levels
- A Community-Led Platform: A solutions platform that helps advance data stewardship across African countries and communities
- “New Deal” Investment: Supporting the development of locally sourced solutions and nuanced technologies tailored to the African context
- Responsible Data Stewardship Framework: A framework that open data stewards can use to support their existing efforts when looking to encourage or implement grassroots policies…(More)”
Governing the Unknown
Article by Kaushik Basu: “Technology is changing the world faster than policymakers can devise new ways to cope with it. As a result, societies are becoming polarized, inequality is rising, and authoritarian regimes and corporations are doctoring reality and undermining democracy.
For ordinary people, there is ample reason to be “a little bit scared,” as OpenAI CEO Sam Altman recently put it. Major advances in artificial intelligence raise concerns about education, work, warfare, and other risks that could destabilize civilization long before climate change does. To his credit, Altman is urging lawmakers to regulate his industry.
In confronting this challenge, we must keep two concerns in mind. The first is the need for speed. If we take too long, we may find ourselves closing the barn door after the horse has bolted. That is what happened with the 1968 Nuclear Non-Proliferation Treaty: It came 23 years too late. If we had managed to establish some minimal rules after World War II, the NPT’s ultimate goal of nuclear disarmament might have been achievable.
The other concern involves deep uncertainty. This is such a new world that even those working on AI do not know where their inventions will ultimately take us. A law enacted with the best intentions can still backfire. When America’s founders drafted the Second Amendment conferring the “right to keep and bear arms,” they could not have known how firearms technology would change in the future, thereby changing the very meaning of the word “arms.” Nor did they foresee how their descendants would fail to realize this even after seeing the change.
But uncertainty does not justify fatalism. Policymakers can still effectively govern the unknown as long as they keep certain broad considerations in mind. For example, one idea that came up during a recent Senate hearing was to create a licensing system whereby only select corporations would be permitted to work on AI.
This approach comes with some obvious risks of its own. Licensing can often be a step toward cronyism, so we would also need new laws to deter politicians from abusing the system. Moreover, slowing your country’s AI development with additional checks does not mean that others will adopt similar measures. In the worst case, you may find yourself facing adversaries wielding precisely the kind of malevolent tools that you eschewed. That is why AI is best regulated multilaterally, even if that is a tall order in today’s world…(More)”.
Filling Africa’s Data Gap
Article by Jendayi Frazer and Peter Blair Henry: “Every few years, the U.S. government launches a new initiative to boost economic growth in Africa. In bold letters and with bolder promises, the White House announces that public-private partnerships hold the key to growth on the continent. It pledges to make these partnerships a cornerstone of its Africa policy, but time and again it fails to deliver.
A decade after U.S. President Barack Obama rolled out Power Africa—his attempt to solve Africa’s energy crisis by mobilizing private capital—half of the continent’s sub-Saharan population remains without access to electricity. In 2018, the Trump administration proclaimed that its Prosper Africa initiative would counter China’s debt-trap diplomacy and “expand African access to business finance.” Five years on, Chad, Ethiopia, Ghana, and Zambia are in financial distress and pleading for debt relief from Beijing and other creditors. Yet the Biden administration is once more touting the potential of public-private investment in Africa, organizing high-profile visits and holding leadership summits to prove that this time, the United States is “all in” on the continent.
There is a reason these efforts have yielded so little: goodwill tours, clever slogans, and a portfolio of G-7 pet projects in Africa do not amount to a sound investment pitch. Potential investors, public and private, need to know which projects in which countries are economically and financially worthwhile. Above all, that requires current and comprehensive data on the expected returns that investment in infrastructure in the developing world can yield. At present, investors lack this information, so they pass. If the United States wants to “build back better” in Africa—to expand access to business finance and encourage countries on the continent to choose sustainable and high-quality foreign investment over predatory lending from China and Russia—it needs to give investors access to better data…(More)”.
Yes, No, Maybe? Legal & Ethical Considerations for Informed Consent in Data Sharing and Integration
Report by Deja Kemp, Amy Hawn Nelson, & Della Jenkins: “Data sharing and integration are increasingly commonplace at every level of government, as cross-program and cross-sector data provide valuable insights to inform resource allocation, guide program implementation, and evaluate policies. Data sharing, while routine, is not without risks, and clear legal frameworks for data sharing are essential to mitigate those risks, protect privacy, and guide responsible data use. In some cases, federal privacy laws offer clear consent requirements and outline explicit exceptions where consent is not required to share data. In other cases, the law is unclear or silent regarding whether consent is needed for data sharing. Importantly, consent can present both ethical and logistical challenges, particularly when integrating cross-sector data. This brief will frame out key concepts related to consent; explore major federal laws governing the sharing of administrative data, including individually identifiable information; and examine important ethical implications of consent, particularly in cases when the law is silent or unclear. Finally, this brief will outline the foundational role of strong governance and consent frameworks in ensuring ethical data use and offer technical alternatives to consent that may be appropriate for certain data uses….(More)”.
Model evaluation for extreme risks
Paper by Toby Shevlane et al: “Current approaches to building general-purpose AI systems tend to produce systems with both beneficial and harmful capabilities. Further progress in AI development could lead to capabilities that pose extreme risks, such as offensive cyber capabilities or strong manipulation skills. We explain why model evaluation is critical for addressing extreme risks. Developers must be able to identify dangerous capabilities (through “dangerous capability evaluations”) and the propensity of models to apply their capabilities for harm (through “alignment evaluations”). These evaluations will become critical for keeping policymakers and other stakeholders informed, and for making responsible decisions about model training, deployment, and security.
Figure 1 | The theory of change for model evaluations for extreme risk. Evaluations for dangerous capabilities and alignment inform risk assessments, and are in turn embedded into important governance processes…(More)”.
How to decode modern conflicts with cutting-edge technologies
Blog by Mykola Blyzniuk: “In modern warfare, new technologies are increasingly being used to manipulate information and perceptions on the battlefield. This includes the use of deep fakes, or the malicious use of ICT (Information and Communication Technologies).
Likewise, emerging tech can be instrumental in documenting human rights violations, tracking the movement of troops and weapons, monitoring public sentiments and the effects of conflict on civilians and exposing propaganda and disinformation.
The dual use of new technologies in modern warfare highlights the need for further investigation. Here are two examples how the can be used to advance politial analysis and situational awareness…
The world of Natural Language Processing (NLP) technology took a leap with a recent study on the Russia-Ukraine conflict by Uddagiri Sirisha and Bolem Sai Chandana of the School of Computer Science and Engineering at Vellore Institute of Technology Andhra Pradesh ( VIT-AP) University in Amaravathi Andhra Pradesh, India.
The researchers developed a novel artificial intelligence model to analyze whether a piece of text is positive, negative or neutral in tone. This new model referred to as “ABSA-based ROBERTa-LSTM”, looks at not just the overall sentiment of a piece of text but also the sentiment towards specific aspects or entities mentioned in the text. The study took a pre-processed dataset of 484,221 tweets collected during April — May 2022 related to the Russia-Ukraine conflict and applied the model, resulting in a sentiment analysis accuracy of 94.7%, outperforming current techniques….(More)”.
Imagining AI: How the World Sees Intelligent Machines
Book edited by Stephen Cave and Kanta Dihal: “AI is now a global phenomenon. Yet Hollywood narratives dominate perceptions of AI in the English-speaking West and beyond, and much of the technology itself is shaped by a disproportionately white, male, US-based elite. However, different cultures have been imagining intelligent machines since long before we could build them, in visions that vary greatly across religious, philosophical, literary and cinematic traditions. This book aims to spotlight these alternative visions.
Imagining AI draws attention to the range and variety of visions of a future with intelligent machines and their potential significance for the research, regulation, and implementation of AI. The book is structured geographically, with each chapter presenting insights into how a specific region or culture imagines intelligent machines. The contributors, leading experts from academia and the arts, explore how the encounters between local narratives, digital technologies, and mainstream Western narratives create new imaginaries and insights in different contexts across the globe. The narratives they analyse range from ancient philosophy to contemporary science fiction, and visual art to policy discourse.
The book sheds new light on some of the most important themes in AI ethics, from the differences between Chinese and American visions of AI, to digital neo-colonialism. It is an essential work for anyone wishing to understand how different cultural contexts interplay with the most significant technology of our time…(More)”.
WHO Launches Global Infectious Disease Surveillance Network
Article by Shania Kennedy: “The World Health Organization (WHO) launched the International Pathogen Surveillance Network (IPSN), a public health network to prevent and detect infectious disease threats before they become epidemics or pandemics.
IPSN will rely on insights generated from pathogen genomics, which helps analyze the genetic material of viruses, bacteria, and other disease-causing micro-organisms to determine how they spread and how infectious or deadly they may be.
Using these data, researchers can identify and track diseases to improve outbreak prevention, response, and treatments.
“The goal of this new network is ambitious, but it can also play a vital role in health security: to give every country access to pathogen genomic sequencing and analytics as part of its public health system,” said WHO Director-General Tedros Adhanom Ghebreyesus, PhD, in the press release. “As was so clearly demonstrated to us during the COVID-19 pandemic, the world is stronger when it stands together to fight shared health threats.”
Genomics capacity worldwide was scaled up during the pandemic, but the press release indicates that many countries still lack effective tools and systems for public health data collection and analysis. This lack of resources and funding could slow the development of a strong global health surveillance infrastructure, which IPSN aims to help address.
The network will bring together experts in genomics and data analytics to optimize routine disease surveillance, including for COVID-19. According to the press release, pathogen genomics-based analyses of the SARS-COV-2 virus helped speed the development of effective vaccines and the identification of more transmissible virus variants…(More)”.
Generative Artificial Intelligence and Data Privacy: A Primer
Report by Congressional Research Service: “Since the public release of Open AI’s ChatGPT, Google’s Bard, and other similar systems, some Members of Congress have expressed interest in the risks associated with “generative artificial intelligence (AI).” Although exact definitions vary, generative AI is a type of AI that can generate new content—such as text, images, and videos—through learning patterns from pre-existing data.
It is a broad term that may include various technologies and techniques from AI and machine learning (ML). Generative AI models have received significant attention and scrutiny due to their potential harms, such as risks involving privacy, misinformation, copyright, and non-consensual sexual imagery. This report focuses on privacy issues and relevant policy considerations for Congress. Some policymakers and stakeholders have raised privacy concerns about how individual data may be used to develop and deploy generative models. These concerns are not new or unique to generative AI, but the scale, scope, and capacity of such technologies may present new privacy challenges for Congress…(More)”.