OECD Report: “As data become an important resource for the global economy, it is important to strengthen trust to facilitate data sharing domestically and across borders. Significant momentum for related policies in the G7, and G20, has gone hand in hand with a wide range of – often complementary – national and international initiatives and the development of technological and organisational measures. Advancing a common understanding and dialogue among G7 countries and beyond is crucial to support coordinated and coherent progress in policy and regulatory approaches that leverage the full potential of data for global economic and social prosperity. This report takes stock of key policies and initiatives on cross-border data flows to inform and support G7 countries’ engagement on this policy agenda…(More)”.
Collective Intelligence in Action – Using Machine Data and Insights to Improve UNDP Sensemaking
UNDP Report: “At its heart, sensemaking is a strategic process designed to extract insights from current projects to generate actionable intelligence for UNDP Country Offices (CO) and other stakeholders. Also, the approach has the potential to increase coherency amongst portfolios of projects, surface common patterns, identify connections, gaps and future perspectives, and determine strategic actions to accelerate the impact of their work.
By adopting a data-driven approach and looking into structured and semi-structured data from https://open.undp.org/ as well as unstructured data from Open UNDP, project documents and annual progress reports of selected projects, this endeavor aims to extract useful insights for the CO colleagues to better understand where their portfolio is working and identify entry points for breaking silos between teams and spurring collaboration. It is designed to help improve Sensemaking, support better strategy and improve management decisions…(More)”.
Global healthcare fairness: We should be sharing more, not less, data
Paper by Kenneth P. Seastedt et al: “The availability of large, deidentified health datasets has enabled significant innovation in using machine learning (ML) to better understand patients and their diseases. However, questions remain regarding the true privacy of this data, patient control over their data, and how we regulate data sharing in a way that does not encumber progress or further potentiate biases for underrepresented populations. After reviewing the literature on potential reidentifications of patients in publicly available datasets, we argue that the cost—measured in terms of access to future medical innovations and clinical software—of slowing ML progress is too great to limit sharing data through large publicly available databases for concerns of imperfect data anonymization. This cost is especially great for developing countries where the barriers preventing inclusion in such databases will continue to rise, further excluding these populations and increasing existing biases that favor high-income countries. Preventing artificial intelligence’s progress towards precision medicine and sliding back to clinical practice dogma may pose a larger threat than concerns of potential patient reidentification within publicly available datasets. While the risk to patient privacy should be minimized, we believe this risk will never be zero, and society has to determine an acceptable risk threshold below which data sharing can occur—for the benefit of a global medical knowledge system….(More)”.
New Horizons in Digital Anthropology
Report by UNESCO and the LiiV Center: “Digitisation, social networks, artificial intelligence, and the metaverse are changing what it means to be human. Humans and technology are now in a dynamic and reciprocal relationship. However, while society has invested trillions in building and tracking digital platforms and personal data, we’ve invested a shockingly small amount in understanding the values, social dynamics, identities, and biases of digital communities.
We can’t address transformations in one without understanding the impacts on the other. Handling growing global challenges such as the spread of misinformation, the rise of social and political polarisation, the mental health crisis, the expansion of digital surveillance, and growing digital inequalities depends on our ability to gain deeper insights into the relationship between people and digital technologies, and to see and understand people, cultures and communities online. The world depends heavily on economics and data science when it comes to understanding digital impacts, but these sciences alone don’t tell the whole story. Economic models are built for scale but struggle with depth. Furthermore, experience shows us that over-reliance on one-dimensional approaches magnifies social biases and ethical blind spots.
Digital Anthropology focuses on this intersection between technology and humans, examining the quantitative and qualitative, using big data and thick data, the virtual and real. While innovation in digital anthropology has started, the field needs more investment and global awareness of its unique and untapped potential to humanise decision-making for leaders across the public and private sectors.
This publication, developed in partnership between UNESCO and the LiiV Center, maps the landscape of innovation in digital anthropology as an approach to ensure a better understanding of how human communities and societies interact and are shaped by technologies and, knowing this, how policies can be rendered more ethical and inclusive.
Briefly, the research found that innovation in digital anthropology is in a state of transition and is perceived differently across sectors and regions. In the span of just a couple of decades, innovation has come from doing anthropology digitally and doing the digital anthropologically, two movements that give life to space where creation happens within the blurry lines among disciplines, fuelled by increasingly fluid movement between academia and the private sector.
The innovation space in-between these trends seem to be where the most exciting and forward-thinking digital innovations are occurring, like novel blended algorithms or computational and techno-anthropology, and opens opportunities to educate a new breed of digitally and anthropologically skilled professionals…(More)”.
Investment Case: Multiplying Progress Through Data Ecosystems
Report by Dalberg: “Data and data ecosystems enable decision makers to improve lives and livelihoods by better understanding the world around them and acting in more effective and targeted ways. In a time of growing crises and shrinking budgets, it is imperative that every dollar is spent in the most efficient and equitable way. Data ecosystems provide decision makers with the information needed to assess and predict challenges, identify and customize solutions, and monitor and evaluate real-time progress. Together, this enables decisions that are more collaborative, effective, efficient, equitable, timely, and transparent. And this is only getting easier—ongoing advances in our ability to harness and apply data are creating opportunities to better target resources and create even more transformative impact…(More)”.
Eliminate data asymmetries to democratize data use
Article by Rahul Matthan: “Anyone who possesses a large enough store of data can reasonably expect to glean powerful insights from it. These insights are more often than not used to enhance advertising revenues or ensure greater customer stickiness. In other instances, they’ve been subverted to alter our political preferences and manipulate us into taking decisions we otherwise may not have.
The ability to generate insights places those who have access to these data sets at a distinct advantage over those whose data is contained within them. It allows the former to benefit from the data in ways that the latter may not even have thought possible when they consented to provide it. Given how easily these insights can be used to harm those to whom it pertains, there is a need to mitigate the effects of this data asymmetry.
Privacy law attempts to do this by providing data principals with tools they can use to exert control over their personal data. It requires data collectors to obtain informed consent from data principals before collecting their data and forbids them from using it for any purpose other than that which has been previously notified. This is why, even if that consent has been obtained, data fiduciaries cannot collect more data than is absolutely necessary to achieve the stated purpose and are only allowed to retain that data for as long as is necessary to fulfil the stated purpose.
In India, we’ve gone one step further and built techno-legal solutions to help reduce this data asymmetry. The Data Empowerment and Protection Architecture (DEPA) framework makes it possible to extract data from the silos in which they reside and transfer it on the instructions of the data principal to other entities, which can then use it to provide other services to the data principal. This data micro-portability dilutes the historical advantage that incumbents enjoy on account of collecting data over the entire duration of their customer engagement. It eliminates data asymmetries by establishing the infrastructure that creates a competitive market for data-based services, allowing data principals to choose from a range of options as to how their data could be used for their benefit by service providers.
This, however, is not the only type of asymmetry we have to deal with in this age of big data. In a recent article, Stefaan Verhulst of GovLab at New York University pointed out that it is no longer enough to possess large stores of data—you need to know how to effectively extract value from it. Many businesses might have vast stores of data that they have accumulated over the years they have been in operation, but very few of them are able to effectively extract useful signals from that noisy data.
Without the know-how to translate data into actionable information, merely owning a large data set is of little value.
Unlike data asymmetries, which can be mitigated by making data more widely available, information asymmetries can only be addressed by radically democratizing the techniques and know-how that are necessary for extracting value from data. This know-how is largely proprietary and hard to access even in a fully competitive market. What’s more, in many instances, the computation power required far exceeds the capacity of entities for whom data analysis is not the main purpose of their business…(More)”.
Data and displacement: Ethical and practical issues in data-driven humanitarian assistance for IDPs
Blog by Vicki Squire: “Ten years since the so-called “data revolution” (Pearn et al, 2022), the rise of “innovation” and the proliferation of “data solutions” has rendered the assessment of changing data practices within the humanitarian sector ever more urgent. New data acquisition modalities have provoked a range of controversies across multiple contexts and sites (e.g. Human Rights Watch, 2021, 2022a, 2022b). Moreover, a range of concerns have been raised about data sharing (e.g. Fast, 2022) and the inequities embedded within humanitarian data (e.g. Data Values, 2022).
With this in mind, the Data and Displacement project set out to explore the practical and ethical implications of data-driven humanitarian assistance in two contexts characterised by high levels of internal displacement: north-eastern Nigeria and South Sudan. Our interdisciplinary research team includes academics from each of the regions under analysis, as well as practitioners from the International Organization for Migration. From the start, the research was designed to centre the lived experiences of Internally Displaced Persons (IDPs), while also shedding light on the production and use of humanitarian data from multiple perspectives.
We conducted primary research during 2021-2022. Our research combines dataset analysis and visualisation techniques with a thematic analysis of 174 semi-structured qualitative interviews. In total we interviewed 182 people: 42 international data experts, donors, and humanitarian practitioners from a range of governmental and non-governmental organisations; 40 stakeholders and practitioners working with IDPs across north-eastern Nigeria and South Sudan (20 in each region); and 100 IDPs in camp-like settings (50 in each region). Our findings point to a disconnect between international humanitarian standards and practices on the ground, the need to revisit existing ethical guidelines such informed consent, and the importance of investing in data literacies…(More)”.
A Philosophy for Future Generations
Book by Tiziana Andina: “If societies, like institutions, are built to endure, then the bond that exists between generations must be considered. Constructing a framework to establish a philosophy of future generations, Tiziana Andina explores the factors that make it possible for a society to reproduce over time.
Andina’s study of the diachronic structure of societies considers the never-ending passage of generations, as each new generation comes to form a part of the new social fabric and political model.
Her model draws on the anthropologies offered by classical political philosophies such as Hobbes and Machiavelli and the philosophies of power as discussed by Nietzsche. She confronts the ethics and function of this fundamental relationship, examines the role of transgenerationality in the formation and endurance of Western democracies and recognizes an often overlooked problem: each new generation must form part of social and political arrangements designed for them by the generations that came before…(More)”.
Inclusive Imaginaries: Catalysing Forward-looking Policy Making through Civic Imagination
UNDP Report: “Today’s complex challenges- including climate change, global health, and international security, among others – are pushing development actors to re-think and re-imagine traditional ways of working and decision-making. Transforming traditional approaches to navigating complexity would support what development thinker Sam Pitroda’s calls a ‘third vision’ demands a mindset rooted in creativity, innovation, and courage in order to one transcend national interests and takes into account global issues.
Inclusive Imaginaries is an approach that utilises collective reflection and imagination to engage with citizens, towards building more just, equitable and inclusive futures. It seeks to infuse imagination as a key process to support gathering of community perspectives rooted in lived experience and local culture, towards developing more contextual visions for policy and programme development…(More)”.
‘Dark data’ is killing the planet – we need digital decarbonisation
Article by Tom Jackson and Ian R. Hodgkinson: “More than half of the digital data firms generate is collected, processed and stored for single-use purposes. Often, it is never re-used. This could be your multiple near-identical images held on Google Photos or iCloud, a business’s outdated spreadsheets that will never be used again, or data from internet of things sensors that have no purpose.
This “dark data” is anchored to the real world by the energy it requires. Even data that is stored and never used again takes up space on servers – typically huge banks of computers in warehouses. Those computers and those warehouses all use lots of electricity.
This is a significant energy cost that is hidden in most organisations. Maintaining an effective organisational memory is a challenge, but at what cost to the environment?
In the drive towards net zero many organisations are trying to reduce their carbon footprints. Guidance has generally centred on reducing traditional sources of carbon production, through mechanisms such as carbon offsetting via third parties (planting trees to make up for emissions from using petrol, for instance).
While most climate change activists are focused on limiting emissions from the automotive, aviation and energy industries, the processing of digital data is already comparable to these sectors and is still growing. In 2020, digitisation was purported to generate 4% of global greenhouse gas emissions. Production of digital data is increasing fast – this year the world is expected to generate 97 zettabytes (that is: 97 trillion gigabytes) of data. By 2025, it could almost double to 181 zettabytes. It is therefore surprising that little policy attention has been placed on reducing the digital carbon footprint of organisations…(More)”.