Paper by Jamie Hancock et al: “There are calls for greater data sharing to address human rights issues. Advocates claim this will provide an evidence-base to increase transparency, improve accountability, enhance decision-making, identify abuses, and offer remedies for rights violations. However, these well-intentioned efforts have been found to sometimes enable harms against the people they seek to protect. This paper shows issues relating to fairness, accountability, or transparency (FAccT) in and around data sharing can produce such ‘ironic’ consequences. It does so using an empirical case study: efforts to tackle modern slavery and human trafficking in the UK. We draw on a qualitative analysis of expert interviews, workshops, ecosystem mapping exercises, and a desk-based review. The findings show how, in the UK, a large ecosystem of data providers, hubs, and users emerged to process and exchange data from across the country. We identify how issues including legal uncertainties, non-transparent sharing procedures, and limited accountability regarding downstream uses of data may undermine efforts to tackle modern slavery and place victims of abuses at risk of further harms. Our findings help explain why data sharing activities can have negative consequences for human rights, even within human rights initiatives. Moreover, our analysis offers a window into how FAccT principles for technology relate to the human rights implications of data sharing. Finally, we discuss why these tensions may be echoed in other areas where data sharing is pursued for human rights concerns, identifying common features which may lead to similar results, especially where sensitive data is shared to achieve social goods or policy objectives…(More)”.
The revolution shall not be automated: On the political possibilities of activism through data & AI
Article by Isadora Cruxên: “Every other day now, there are headlines about some kind of artificial intelligence (AI) revolution that is taking place. If you read the news or check social media regularly, you have probably come across these too: flashy pieces either trumpeting or warning against AI’s transformative potential. Some headlines promise that AI will fundamentally change how we work and learn or help us tackle critical challenges such as biodiversity conservation and climate change. Others question its intelligence, point to its embedded biases, and draw attention to its extractive labour record and high environmental costs.
Scrolling through these headlines, it is easy to feel like the ‘AI revolution’ is happening to us — or perhaps blowing past us at speed — while we are enticed to take the backseat and let AI-powered chat-boxes like ChatGPT do the work. But the reality is that we need to take the driver’s seat.
If we want to leverage this technology to advance social justice and confront the intersecting socio-ecological challenges before us, we need to stop simply wondering what the AI revolution will do to us and start thinking collectively about how we can produce data and AI models differently. As Mimi Ọnụọha and Mother Cyborg put it in A People’s Guide to AI, “the path to a fair future starts with the humans behind the machines, not the machines themselves.”
Sure, this might seem easier said than done. Most AI research and development is being driven by big tech corporations and start-ups. As Lauren Klein and Catherine D’Ignazio discuss in “Data Feminism for AI” (see “Further reading” at the end for all works cited), the results are models, tools, and platforms that are opaque to users, and that cater to the tech ambitions and profit motives of private actors, with broader societal needs and concerns becoming afterthoughts. There is excellent critical work that explores the extractive practices and unequal power relations that underpin AI production, including its relationship to processes of datafication, colonial data epistemologies, and surveillance capitalism (to link but a few). Interrogating, illuminating, and challenging these dynamics is paramount if we are to take the driver’s seat and find alternative paths…(More)”.
Blueprints for Learning
Report by the Data Foundation: “The Foundations for Evidence-Based Policymaking Act of 2018 (Evidence Act) required the creation of learning agendas for the largest federal agencies. These agendas outline how agencies will identify and answer priority questions through data and evidence-building activities. The Data Foundation undertook an analysis of the agendas to understand how they were developed and plans for implementation as part of the 5-Year milestone of the Evidence Act.
The analysis reveals both progress and areas for improvement in the development and use of learning agendas. All but one large agency produced a publicly-available learning agenda, demonstrating a significant initial effort. However, several challenges were identified:
- Limited detail on execution and use: Many learning agendas lacked specifics on how the identified priority questions would be addressed or how the evidence generated would be used.
- Variation in quality: Agencies diverged in the comprehensiveness and clarity of their agendas, with some providing more detailed plans than others.
- Resource constraints: The analysis suggests that a lack of dedicated resources may be hindering some agencies’ capacity to fully implement their learning agendas…(More)”.
Societal interaction plans—A tool for enhancing societal engagement of strategic research in Finland
Paper by Kirsi Pulkkinen, Timo Aarrevaara, Mikko Rask, and Markku Mattila: “…we investigate the practices and capacities that define successful societal interaction of research groups with stakeholders in mutually beneficial processes. We studied the Finnish Strategic Research Council’s (SRC) first funded projects through a dynamic governance lens. The aim of the paper is to explore how the societal interaction was designed and commenced at the onset of the projects in order to understand the logic through which the consortia expected broad impacts to occur. The Finnish SRC introduced a societal interaction plan (SIP) approach, which requires research consortia to consider societal interaction alongside research activities in a way that exceeds conventional research plans. Hence, the first SRC projects’ SIPs and the implemented activities and working logics discussed in the interviews provide a window into exploring how active societal interaction reflects the call for dynamic, sustainable practices and new capabilities to better link research to societal development. We found that the capacities of dynamic governance were implemented by integrating societal interaction into research, in particular through a ‘drizzling’ approach. In these emerging practices SIP designs function as platforms for the formation of communities of experts, rather than traditional project management models or mere communication tools. The research groups utilized the benefits of pooling academic knowledge and skills with other types of expertise for mutual gain. They embraced the limits of expertise and reached out to societal partners to truly broker knowledge, and exchange and develop capacities and perspectives to solve grand societal challenges…(More)”.
Why the future of democracy could depend on your group chats
Article by Nathan Schneider: “I became newly worried about the state of democracy when, a few years ago, my mother was elected president of her neighborhood garden club.
Her election wasn’t my worry – far from it. At the time, I was trying to resolve a conflict on a large email group I had created. Someone, inevitably, was being a jerk on the internet. I had the power to remove them, but did I have the right? I realized that the garden club had in its bylaws something I had never seen in nearly all the online communities I had been part of: basic procedures to hold people with power accountable to everyone else.
The internet has yet to catch up to my mother’s garden club.
When Alexis de Tocqueville toured the United States in the early 1830s, he made an observation that social scientists have seen over and over since: Democracy at the state and national levels depends on everyday organizations like that garden club. He called them “schools” for practicing the “general theory of association.” As members of small democracies, people were learning to be citizens of a democratic country.
How many people experience those kinds of schools today?
People interact online more than offline nowadays. Rather than practicing democracy, people most likely find themselves getting suspended from a Facebook group they rely on with no reason given or option to appeal. Or a group of friends join a chat together, but only one of them has the ability to change its settings. Or people see posts from Elon Musk inserted into their mentions on X, which he owns. All of these situations are examples of what I call “implicit feudalism.”…(More)”.
Inclusive by default: strategies for more inclusive participation
Article by Luiza Jardim and Maria Lucien: “…The systemic challenges that marginalised groups face are pressing and require action. The global average age of parliamentarians is 53, highlighting a gap in youth representation. Young people already face challenges like poverty, lack of education, unemployment and multiple forms of discrimination. Additionally, some participatory formats are often unappealing to young people and pose a challenge for engaging them. Gender equity research highlights the underrepresentation of women at all levels of decision-making and governance. Despite recent improvements, gender parity in governance worldwide is still decades or even centuries away. Meanwhile, ongoing global conflicts in Ukraine, Sudan, Gaza and elsewhere, as well as the impacts of a changing climate, have driven the recent increase in the number of forcibly displaced people to more than 100 million. The engagement of these individuals in decision-making can vary greatly depending on their specific circumstances and the nature of their displacement.
Participatory and deliberative democracy can have transformative impacts on historically marginalised communities but only if they are intentionally included in program design and implementation. To start with, it’s possible to reduce the barriers to participation, such as the cost and time of transport to the participation venue, or burdens imposed by social and cultural roles in society, like childcare. During the process, mindful and attentive facilitation can help balance power dynamics and encourage participation from traditionally excluded people. This is further strengthened if the facilitation team includes and trains members of priority communities in facilitation and session planning…(More)”.
Liberated Public Services: A new vision for citizens, professionals and policy makers
Report by Demos: “The crisis in public services is visible to everyone in Britain today. Waiting lists, crumbling buildings, exhausted professionals. This is affecting our wellbeing, our health and our economy. It’s increasingly clear that Britain cannot get back on the right track without a public services renewal. The aim of Demos’ Future Public Services Taskforce is to help deliver that renewal.
In this paper, the second paper of the Taskforce, we introduce a new vision for public services, which we call liberated public services. This includes public services being liberated from New Public Management across four domains:
- Citizens are liberated to bring their whole selves to services and seen as a resource to be worked with,
not a problem to be fixed. - Professionals are liberated from tight specifications defined from the centre.
- Communities are liberated to partner with public services, whether formally or informally.
- Policy makers in central government – ministers, advisors and civil servants – are liberated from day-today micromanagement of services and providers to a broader, strategic role supporting learning and best
practice.
Liberating public services will require the central state to think less about imposing a view from Whitehall and instead ask itself: how can it provide the conditions for public service renewal across the country?..(More)”.
Are We Ready for the Next Pandemic? Navigating the First and Last Mile Challenges in Data Utilization
Blog by Stefaan Verhulst, Daniela Paolotti, Ciro Cattuto and Alessandro Vespignani:
“Public health officials from around the world are gathering this week in Geneva for a weeklong meeting of the 77th World Health Assembly. A key question they are examining is: Are we ready for the next pandemic? As we have written elsewhere, regarding access to and re-use of data, particularly non-traditional data, for pandemic preparedness and response: we are not. Below, we list ten recommendations to advance access to and reuse of non-traditional data for pandemics, drawing on input from a high-level workshop, held in Brussels, within the context of the ESCAPE program…(More)”
As
close.city
About: “Proximity governs how we live, work, and socialize. Close is an interactive travel time map for people who want to be near the amenities that matter most to them. Close builds on two core principles:
- Different people will prioritize being near different amenities
- A neighborhood is only as accessible as its most distant important amenity
When you select multiple amenities in Close, the map shows the travel time to the furthest of those amenities. You can set your preferred travel mode to get to each amenity. Walking + Public Transit, Biking or Combined. Close is currently in public beta, with more features and destination types coming over the next few months. The reliability of destinations will continually improve as new data sources and user feedback are incorporated. Close is built and maintained by Henry Spatial Analysis. You can stay up-to-date on the latest improvements to Close by subscribing to the newsletter. How to use Close – Close includes travel time information for cities across the United States. To view a different location, select the search icon on the top left of the screen and enter a city or county name. To access map details, including a link to this About page, click the menu icon in the top left corner of the map…(More)”
Will we run out of data? Limits of LLM scaling based on human-generated data
Paper by Pablo Villalobos: We investigate the potential constraints on LLM scaling posed by the availability of public human-generated text data. We forecast the growing demand for training data based on current trends and estimate the total stock of public human text data. Our findings indicate that if current LLM development trends continue, models will be trained on datasets roughly equal in size to the available stock of public human text data between 2026 and 2032, or slightly earlier if models are overtrained. We explore how progress in language modeling can continue when human-generated text datasets cannot be scaled any further. We argue that synthetic data generation, transfer learning from data-rich domains, and data efficiency improvements might support further progress…(More)”.