The New Knowledge


Book by Blayne Haggart and Natasha Tusikov: “From the global geopolitical arena to the smart city, control over knowledge—particularly over data and intellectual property—has become a key battleground for the exercise of economic and political power. For companies and governments alike, control over knowledge—what scholar Susan Strange calls the knowledge structure—has become a goal unto itself.

The rising dominance of the knowledge structure is leading to a massive redistribution of power, including from individuals to companies and states. Strong intellectual property rights have concentrated economic benefits in a smaller number of hands, while the “internet of things” is reshaping basic notions of property, ownership, and control. In the scramble to create and control data and intellectual property, governments and companies alike are engaging in ever-more surveillance.

The New Knowledge is a guide to and analysis of these changes, and of the emerging phenomenon of the knowledge-driven society. It highlights how the pursuit of the control over knowledge has become its own ideology, with its own set of experts drawn from those with the ability to collect and manipulate digital data. Haggart and Tusikov propose a workable path forward—knowledge decommodification—to ensure that our new knowledge is not treated simply as a commodity to be bought and sold, but as a way to meet the needs of the individuals and communities that create this knowledge in the first place…(More)”.

Climate change may kill data sovereignty


Article by Trisha Ray: “Data centres are the linchpin of a nation’s technological progress, serving as the nerve centers that power the information age. The need for robust and reliable data centre infrastructure cuts across the UN Sustainable Development Goals (SDGs), serving as an essential foundation for e-government, innovation and entrepreneurship, decent work, and economic growth. It comes as no surprise then that data sovereignty has gained traction over the past decade, particularly in the Global South. However, climate change threatens the very infrastructure that underpins the digital future, and its impact on data centres is a multifaceted challenge, with rising temperatures, extreme weather events, and changing environmental conditions posing significant threats to their reliability and sustainability, even as developing countries begin rolling out ambitious strategies and incentives to attract data centres…(More)”.

Data Science for Social Impact in Higher Education:  First Steps


Data.org playbook: “… was designed to help you expand opportunities for social impact data science learning. As you browse, you will see a range of these opportunities including courses, modules for other courses, research and internship opportunities, and a variety of events and activities. The playbook also offers lessons learned to guide you through your process. Additionally, the Playbook includes profiles of students who have engaged in data science for social impact, guidance for engaging partners, and additional resources relating to evaluation and courses. We hope that this playbook will inspire and support your efforts to bring social impact data science to your institutions…

As you look at the range of ways you might bring data science for social impact to your students, remember that the intention is not for you to replicate what is here, but rather adapt them to your local contexts and conditions. You might draw pieces from several activities and combine them to create a customized strategy that works for you. Consider the assets you have around you and how you might be able to leverage them. At the same time, imagine how some of the lessons learned might reflect barriers you might face, as well. Most importantly, know that it is possible for you to create data science for social impact at your institution to bring benefit to your students and society…(More)”.

Medical AI could be ‘dangerous’ for poorer nations, WHO warns


Article by David Adam: “The introduction of health-care technologies based on artificial intelligence (AI) could be “dangerous” for people in lower-income countries, the World Health Organization (WHO) has warned.

The organization, which today issued a report describing new guidelines on large multi-modal models (LMMs), says it is essential that uses of the developing technology are not shaped only by technology companies and those in wealthy countries. If models aren’t trained on data from people in under-resourced places, those populations might be poorly served by the algorithms, the agency says.

“The very last thing that we want to see happen as part of this leap forward with technology is the propagation or amplification of inequities and biases in the social fabric of countries around the world,” Alain Labrique, the WHO’s director for digital health and innovation, said at a media briefing today.

The WHO issued its first guidelines on AI in health care in 2021. But the organization was prompted to update them less than three years later by the rise in the power and availability of LMMs. Also called generative AI, these models, including the one that powers the popular ChatGPT chatbot, process and produce text, videos and images…(More)”.

Facial Recognition: Current Capabilities, Future Prospects, and Governance


A National Academies of Sciences, Engineering, and Medicine study: “Facial recognition technology is increasingly used for identity verification and identification, from aiding law enforcement investigations to identifying potential security threats at large venues. However, advances in this technology have outpaced laws and regulations, raising significant concerns related to equity, privacy, and civil liberties.

This report explores the current capabilities, future possibilities, and necessary governance for facial recognition technology. Facial Recognition Technology discusses legal, societal, and ethical implications of the technology, and recommends ways that federal agencies and others developing and deploying the technology can mitigate potential harms and enact more comprehensive safeguards…(More)”.

People Have a Right to Climate Data


Article by Justin S. Mankin: “As a climate scientist documenting the multi-trillion-dollar price tag of the climate disasters shocking economies and destroying lives, I sometimes field requests from strategic consultantsfinancial investment analysts and reinsurers looking for climate data, analysis and computer code.

Often, they want to chat about my findings or have me draw out the implications for their businesses, like the time a risk analyst from BlackRock, the world’s largest asset manager, asked me to help with research on what the current El Niño, a cyclical climate pattern, means for financial markets.

These requests make sense: People and companies want to adapt to the climate risks they face from global warming. But these inquiries are also part of the wider commodification of climate science. Venture capitalists are injecting hundreds of millions of dollars into climate intelligence as they build out a rapidly growing business of climate analytics — the data, risk models, tailored analyses and insights people and institutions need to understand and respond to climate risks.

I point companies to our freely available data and code at the Dartmouth Climate Modeling and Impacts Group, which I run, but turn down additional requests for customized assessments. I regard climate information as a public good and fear contributing to a world in which information about the unfolding risks of droughts, floods, wildfires, extreme heat and rising seas are hidden behind paywalls. People and companies who can afford private risk assessments will rent, buy and establish homes and businesses in safer places than the billions of others who can’t, compounding disadvantage and leaving the most vulnerable among us exposed.

Despite this, global consultants, climate and agricultural technology start-ups, insurance companies and major financial firms are all racing to meet the ballooning demand for information about climate dangers and how to prepare for them. While a lot of this information is public, it is often voluminous, technical and not particularly useful for people trying to evaluate their personal exposure. Private risk assessments fill that gap — but at a premium. The climate risk analytics market is expected to grow to more than $4 billion globally by 2027.

I don’t mean to suggest that the private sector should not be involved in furnishing climate information. That’s not realistic. But I worry that an overreliance on the private sector to provide climate adaptation information will hollow out publicly provided climate risk science, and that means we all will pay: the well-off with money, the poor with lives…(More)”.

A tale of two cities: one real, one virtual


Joy Lo Dico in the Financial Times: “In recent years, digital city-building has become a legitimate part of urban planning. Barcelona, Cambridge and Helsinki are among a number of European cities exploring how copies of themselves could prove useful in making their built environments sharper, faster, cleaner and greener.

What exists in real life is being rendered a second time in the digital space: creating a library of the past, an eagle’s-eye view of the present and, potentially, a vision of the future.

One of the most striking projects has been happening in Ukraine, where technology company Skeiron has, since 2022, been mapping the country’s monuments, under threat from bombing.

The project #SaveUkrainianHeritage has recorded 60 buildings, from the St Sofia Cathedral in Kyiv and the Chernivtsi National University — both Unesco world heritage sites — to wooden churches across the country, something Skeiron’s co-founder Yurii Prepodobnyi mentions with pride. There are thousands of them. “Some are only 20 or 30 square metres,” he says. “But Ukrainian churches keep Ukrainian identity.”

With laser measurements, drone photography and photogrammetry — the art of stitching photographs together — Prepodobnyi and his team can produce highly detailed 3D models.

They have even managed to recreate the exterior of the Mariupol drama theatre, destroyed in the early days of the Ukraine war, after calling for photographs and drone footage.

Another project, in Pompeii, has been using similar digital techniques to capture the evolution of excavations into a 3D model. The Pompeii I. 14 Project, led by Tulane University and Indiana State University, takes the process of excavating buildings within one block of Pompeii, Insula 14, and turns it into a digital representation. Using laser measurements, iPad Pros, a consumer drone and handheld cameras, a space can be measured to within a couple of millimetres. What is relayed back along the stream is a visual record of how a room changes over thousands of years, as the debris, volcanic eruption and layers of life that went before are revealed…(More)”.

Privacy-Enhancing and Privacy-Preserving Technologies: Understanding the Role of PETs and PPTs in the Digital Age


Paper by the Centre for Information Policy Leadership: “The paper explores how organizations are approaching privacy-enhancing technologies (“PETs”) and how PETs can advance data protection principles, and provides examples of how specific types of PETs work. It also explores potential challenges to the use of PETs and possible solutions to those challenges.

CIPL emphasizes the enormous potential inherent in these technologies to mitigate privacy risks and support innovation, and recommends a number of steps to foster further development and adoption of PETs. In particular, CIPL calls for policymakers and regulators to incentivize the use of PETs through clearer guidance on key legal concepts that impact the use of PETs, and by adopting a pragmatic approach to the application of these concepts.

CIPL’s recommendations towards wider adoption are as follows:

  • Issue regulatory guidance and incentives regarding PETs: Official regulatory guidance addressing PETs in the context of specific legal obligations or concepts (such as anonymization) will incentivize greater investment in PETs.
  • Increase education and awareness about PETs: PET developers and providers need to show tangible evidence of the value of PETs and help policymakers, regulators and organizations understand how such technologies can facilitate responsible data use.
  • Develop industry standards for PETs: Industry standards would help facilitate interoperability for the use of PETs across jurisdictions and help codify best practices to support technical reliability to foster trust in these technologies.
  • Recognize PETs as a demonstrable element of accountability: PETs complement robust data privacy management programs and should be recognized as an element of organizational accountability…(More)”.

Testing the Assumptions of the Data Revolution


Report by TRENDS: “Ten years have passed since the release of A World that Counts and the formal adoption of the Sustainable Development Goals (SDGs). This seems an appropriate time for national governments and the global data community to reflect on where progress has been made so far. 

This report supports this objective in three ways: it evaluates the assumptions that underpin A World that Counts’ core hypothesis that the data revolution would lead to better outcomes across the 17 SDGs, it summarizes where and how we have made progress, and it identifies knowledge gaps related to each assumption. These knowledge gaps will serve as the foundation for the next phase of the SDSN TReNDS research program, guiding our exploration of emerging data-driven paradigms and their implications for the SDGs. By analyzing these assumptions, we can consider how SDSN TReNDs and other development actors might adapt their activities to a new set of circumstances in the final six years of the SDG commitments.

Given that the 2030 Agenda established a 15-year timeframe for SDG attainment, it is to be expected that some of A World that Counts’ key assumptions would fall short or require recalibration along the way. Unforeseen events such as the COVID-19 pandemic would inevitably shift global attention and priorities away from the targets set out in the SDG framework, at least temporarily…(More)”.

Tackling Today’s Data Dichotomy: Unveiling the Paradox of Abundant Supply and Restricted Access in the Quest for Social Equity


Article by Stefaan Verhulst: “…One of the ironies of this moment, however, is that an era of unprecedented supply is simultaneously an era of constricted access to data. Much of the data we generate is privately “owned,” hidden away in private or public sector silos, or otherwise inaccessible to those who are most likely to benefit from it or generate valuable insights. These restrictions on access are grafted onto existing socioeconomic inequalities, driven by broader patterns of exclusion and marginalization, and also exacerbating them. Critically, restricted or unequal access to data does not only harm individuals: it causes untold public harm by limiting the potential of data to address social ills. It also limits attempts to improve the output of AI both in terms of bias and trustworthiness.

In this paper, we outline two potential approaches that could help address—or at least mitigate—the harms: social licensing and a greater role for data stewards. While not comprehensive solutions, we believe that these represent two of the most promising avenues to introduce greater efficiencies into how data is used (and reused), and thus lead to more targeted, responsive, and responsible policymaking…(page 22-25)”.