Stefaan G. Verhulst & Sampriti Saxena at Data & Policy: “Data has rapidly emerged as an invaluable asset in societies and economies, leading to growing demands for innovative and transformative data practices. One such practice that has received considerable attention is data reuse. Data reuse is at the forefront of an emerging “third wave of open data” (Verhulst et al., 2020). Data reuse takes place when data collected for one purpose is used subsequently for an alternative purpose, typically with the justification that such secondary use has potential positive social impact (Choo et al., 2021). Since data is considered a non-rivalrous good, it can be used an infinite number of times, each use potentially bringing new insights and solutions to public problems (OECD, 2021). Data reuse can also lead to lower project costs and more sustainable outcomes for a variety of data-enabled initiatives across sectors.
A social license, or social license to operate, captures multiple stakeholders’ acceptance of standard practices and procedures (Kenton, 2021). Stakeholders, in this context, could refer to both the public and private sector, civil society, and perhaps most importantly, the public at large. Although the term originated in the context of extractive industries, it is now applied to a much broader range of businesses including technologies like artificial intelligence (Candelon et al., 2022). As data becomes more commonly compared to exploitative practices like mining, it is only apt that we apply the concept of social licenses to the data ecosystem as well (Aitken et al., 2020).
Before exploring how to achieve social licenses for data reuse, it is important to understand the many factors that affect social licenses….(More)”.
Article by Kriss Deiglmeier: “In 2011, I was co-teaching a course on Corporate Social Innovation at the Stanford Graduate School of Business, when our syllabus nearly went astray. A paper appeared in Harvard Business Review (HBR), titled “Creating Shared Value,” by Michael E. Porter and Mark R. Kramer. The students’ excitement was palpable: This could transform capitalism, enabling Adam Smith’s “invisible hand” to bend the arc of history toward not just efficiency and profit, but toward social impact…
History shows that the promise of shared value hasn’t exactly been realized. In the past decade, most indexes of inequality, health, and climate change have gotten worse, not better. The gap in wealth equality has widened – the combined worth of the top 1% in the United States increased from 29% of all wealth in 2011 to 32.3% in 2021 and the bottom 50% increased their share from 0.4% to 2.6% of overall wealth; everyone in between saw their share of wealth decline. The federal minimum wage has remained stagnant at $7.25 per hour while the US dollar has seen a cumulative price increase of 27.81%…
That said, data is by no means the only – or even primary – obstacle to achieving shared value, but the role of data is a key aspect that needs to change. In a shared value construct, data is used primarily for profit and not the societal benefit at the speed and scale required.
Unfortunately, the technology transformation has resulted in an emerging data divide. While data strategies have benefited the commercial sector, the public sector and nonprofits lag in education, tools, resources, and talent to use data in finding and scaling solutions. The result is the disparity between the expanding use of data to create commercial value, and the comparatively weak use of data to solve social and environmental challenges…
Data is part of our future and is being used by corporations to drive success, as they should. Bringing data into the shared value framework is about ensuring that other entities and organizations also have the access and tools to harness data for solving social and environmental challenges as well….
Business has the opportunity to help solve the data divide through a shared value framework by bringing talent, product and resources to bear beyond corporate boundaries to help solve our social and environmental challenges. To succeed, it’s essential to re-envision the shared value framework to ensure data is at the core to collectively solve these challenges for everyone. This will require a strong commitment to collaboration between business, government and NGOs – and it will undoubtedly require a dedication to increasing data literacy at all levels of education….(More)”.
Blog by Uma Kalkar, Marine Ragnet, and Stefaan Verhulst: “In 2020, there were an estimated 281 million migrants, accounting for 3.6% of the global population. Migrants move for a variety of reasons: some are forced to flee from unsafe situations caused by conflict or climate change, others voluntarily move in search of new opportunities. People on the move bring along a wealth of new data. This information creates new opportunities for data collection, use, and reuse across the migration process and by a variety of public, private, and humanitarian sectors. Increased access and use of data for migration need to be accompanied by increased agency and the empowerment of the data subjects — a concept called “digital self-determination” (DSD).
Although DSD is a relatively new concept, its roots stem from philosophy, psychology and human rights jurisprudence. Broadly speaking, DSD affirms that a person’s data is an extension of themselves in cyberspace, and we therefore need to consider how to provide a certain level of autonomy and agency to individuals or communities over their digital self. The first studio sought to deconstruct this concept within the context of migration and migrants. Below we list some of the main takeaways from the studio discussions.
Takeaway #1: DSD is in essence about the power asymmetries between migrants, states, and relevant organizations. Specifically, conversations around DSD centered around “power” and “control” — there is an asymmetry between the migrant and the state or organization they interact with to move within and across borders. These imbalances center around agency (a lack of autonomy over data collection, data consciousness, and data use); choice (in who, how, and where data are used, a lack of transparency over these decisions, and power and control issues faced when seeking to access national or social rights); and participation (who gets to formulate questions and access the data?).
Studio participants brought up how structural requirements force migrants to be open about their data; noted the opacity around how data is sourced from migrants; and raised concerns about agency, data literacy, and advocacy across the migrant process.
The various hierarchies of power, and how it relates to DSD for migrants, highlighted the discrepancies in power between migrants, the state, private companies, and even NGOs.
Information architecture and information asymmetries are some of the central aspects to consider to achieve DSD, suggesting that DSD may relate directly to who is telling the story during a crisis and who has the power to add insights to the narratives being developed. A responsible DSD framework will hinge on the voices of migrants.
The right to “data consciousness” was also raised to ensure that vulnerable individuals and groups are aware of when, where, and how data are collected, processed, and stored. Nurturing this awareness helps breed agency around personal data.
Representation of power asymmetries faced by migrants in achieving their DSD.
Takeaway #2: There is a need to understand the dual meaning of DSD.
Takeaway #3: There is a need to engage migrants in needs and expectations.…
Takeaway #4: A taxonomy of DSD for the various migration-related steps can support creating effective tools to protect migrants along their journey...
Takeaway #5: DSD can be achieved through policy, technology, and process innovations.…
Takeaway #6: DSD opportunities need to be determined across the data life cycle….(More)”.
WEF Blog: “New technologies, such as artificial intelligence, internet of things and the metaverse, demand data as the foundational resource for solving systemic challenges, from pandemic response to climate change. Yet despite an abundance of both supply and demand, the evolution from data to insight still presents many challenges.
On the one hand, data often remains siloed within territorial boundaries and corporate environments and is unavailable to benefit people, society and the planet. On the other, the type of governance needed to assure proper oversight, transparency and accountability by those using data is still being understood.
As the data universe expands, it becomes exponentially more complex, requiring solutions that integrate political, economic, social, environmental, technological and, most importantly, human aspects…
Through its partnership with the City of Helsinki, the Forum has convened a global community of technologists, anthropologists and policy and data experts to develop data policy that serves the general public and meets their expectations…(More)”.
Blog by USAID: “In order for us all to work better together, foreign assistance data — how and where the U.S. government invests our foreign assistance dollars — must be easily, readily, and freely available to the public, media, and our international partners.
To uphold these core values of transparency and openness, USAID and the U.S. Department of State jointly re-launched ForeignAssistance.gov.
This one-stop-shop helps the American taxpayer and other stakeholders understand the depth and breadth of the U.S. Government’s work in international development and humanitarian assistance, so that how much we invest and where and when we invest it is easier to access, use, and understand.
The new ForeignAssistance.gov provides a wealth of global information (above) as well as specific details for countries (below).
The new, consolidated ForeignAssistance.gov is a visual, interactive website that advances transparency by publishing U.S. foreign assistance budget and financial data that is usable, accurate, and timely. The site empowers users to explore U.S. foreign assistance data through visualizations, while also providing the flexibility for users to create custom queries, download data, and conduct analyses by country, sector, or agency…(More)”.
Blog by Eric Jensen and Mark Reed: “Managing data isn’t exciting and it can feel like a hassle to deposit data at the end of a project, when you want to focus on publishing your findings.
We analysed case studies from the UK Research Excellence Framework (REF) exercise in 2014 to show how data analysis and curation can generate benefits for policy and practice, and sought to understand the pathways through which data typically leads to impact. In this series of blog posts we will unpack this research and show you how you can manage your data for impact.
The most prevalent type of research data-driven impact was benefits for professional practice (45% UK; 44% Australia).
This category of impact includes changing the ways professionals operate and improving the quality of products or services through better methods, technologies, and responses to issues through better understanding. It also includes changing organisational culture and improving workplace productivity or outcomes.
Government impacts were the next most prevalent category identified in this research (21% UK; 20% Australia).
These impacts include the introduction of new policies and changes to existing policies, as well as
reducing the cost to deliver government services
enhancing the effectiveness or efficiency of government services and operations
more efficient government planning
Other relatively common types of research data-driven impacts were economic impact (13% UK; 14% Australia) and public health impacts (10% UK; 8% Australia)…(More)”.
Blog by the “Democratic Progress” Task force: “There appears to be distrust between citizens and governing officials at all levels, from local municipalities to regional and even national governments. The rapid transformation brought about by digital technologies, from the way we work to where we work, is instilling anxiety and uncertainty in the minds of our population. The fact is that the “business models” and way of doing business has shifted for all, whether you are in government, corporate, and even academia.
Despite their best efforts to innovate and embrace this transformation, the operational systems and processes in place are inefficient and ineffective in doing so, resulting in the digital divide. This divide just increases fear and uncertainty, leading to governments relying on populist views to garner votes, further polarizing rather than uniting nations.
New democratic forms and institutions, in general, can help liberal democracies overcome the challenges highlighted. We will need to build more collaborations, partnerships, and dialogues with a range of stakeholders (SDG17 SDG16 SDG8) so that we may consider more viewpoints on a number of levels and embrace this transition collectively.
This is where the potential of digital ecosystems (communities), which are primarily represented by coworking spaces, creative hubs, and youth centres, are critical platforms for enabling this shift becomes important. The creation of an enabling environment in which diverse stakeholders (government, corporate, academia, and civil society) can collaborate to accelerate social tech entrepreneurs and digital technologies while holding open and inclusive dialogues about social challenges, cultural, and democratic experiences would be a key focus for this.
The Conference on the Future of Europe has taken a significant step in this direction; now we must bring together and elevate the voices of our citizens and digital ecosystem players to ensure that we create an inclusive and enabling environment that embraces citizens’ needs in the digital transformation and closes the digital divide. The goal of these platforms is to facilitate true contact between citizens and decision-makers, which will aid in the resolution of social issues and the restoration of confidence in our society…(More)”
Article by Nicholas Davis: “Although technology regulation is evolving rapidly in today’s world, such regulation remains greatly fragmented across national and regional divides. Agile governance can potentially solve this fragmentation by promoting nimbler, more fluid, and more adaptive approaches to regulation.
Take data protection, for example. The EU’s General Data Protection Regulation (GDPR), which was first proposed in 2012 and came into effect in 2018, is essentially an international privacy law for data protection. Any organization that processes any personal data from any EU citizen is covered.
Article by Geoff Mulgan: “In the first months of the pandemic there was evidence of a strong desire for transformational change in many countries. People wanted to use the crisis to deal with the big unresolved problems of climate change inequality and much more, encouraged, for example, by the very obvious truth that the most essential jobs were often amongst the lowest paid and lowest status. That everyone was affected by the pandemic seemed likely to fuel a more collective spirit, a recognition of how much our lives are intertwined with those of millions of strangers.
Now much of that energy has gone. People are exhausted, expectations have fallen and a return to normality looks acceptable, however inadequate that normality might have been. War in Ukraine has reminded us just how easily the world can go into retreat and that basic values remain under threat. My hope, though, is that as the pandemic fades from view we will return to our shared need for radical imagination about the future, and the transformations ahead.
I have long believed that we have a major problem with imagination: that we can more easily imagine ecological apocalypse or technological advances than improvements in how our society works: better options for health, welfare or neighbourhoods a generation or two from now.
Some of the reasons for this problem are objective. The majority of people no longer expect their children to be better off than them. They have good reasons for their pessimism: stagnant incomes for much of the population, particularly since the financial crisis. But the causes of this pessimism also lie with institutions – our universities have become better at commenting on or analysing the present than designing the future. Our political parties have largely given up on long-term thinking, while our social movements are generally better at arguing against things than proposing. Amazingly, there are now no media outlets that promote new ideas: magazines and newspapers focus instead on commentary.
One symptom of this is how much public debate, even in its progressive forms, is dominated by quite old ideas. Take, for example, the circular economy. The main ideas were first proposed in the 1980s. They guided many projects (including ones I worked on) in the 1990s, got the backing of the Chinese Communist party nearly twenty years ago, and were then ably evangelized by people like Ellen McArthur. Yet they’re still not wholly mainstream…(More)”.
Essay by Bhaskar Chakravorti: “The pandemic could have been the moment when AI made good on its promising potential. There was an unprecedented convergence of the need for fast, evidence-based decisions and large-scale problem-solving with datasets spilling out of every country in the world. Instead, AI failed in myriad, specific ways that underscore where this technology is still weak: Bad datasets, embedded bias and discrimination, susceptibility to human error, and a complex, uneven global context all caused critical failures. But, these failures also offer lessons on how we can make AI better: 1) we need to find new ways to assemble comprehensive datasets and merge data from multiple sources, 2) there needs to be more diversity in data sources, 3) incentives must be aligned to ensure greater cooperation across teams and systems, and 4) we need international rules for sharing data…(More)”.
