Paper by Adrian Smith & Pedro Prieto Martín: “Digital platforms for urban democracy are analyzed in Madrid and Barcelona. These platforms permit citizens to debate urban issues with other citizens; to propose developments, plans, and policies for city authorities; and to influence how city budgets are spent. Contrasting with neoliberal assumptions about Smart Citizenship, the technopolitics discourse underpinning these developments recognizes that the technologies facilitating participation have themselves to be developed democratically. That is, technopolitical platforms are built and operate as open, commons-based processes for learning, reflection, and adaptation. These features prove vital to platform implementation consistent with aspirations for citizen engagement and activism….(More)”.
Democratic Innovation in Times of Crisis: Exploring Changes in Social and Political Trust
Paper by Martin Karlsson, Joachim Åström and Magnus Adenskog: “The Estonian Citizens’ Assembly (ECA) was initiated in late 2012 as a direct consequence of a legitimacy crisis of Estonian political parties and representative institutions. The spark igniting this crisis was the unraveling of a scheme of illegal party financing. The response from governmental institutions took the form of a democratic innovation involving public crowd‐sourcing and deliberative mini‐publics. This study reports on a survey among the participants in the online crowd‐sourcing process of the ECA (n = 847). The study examines how this democratic innovation influenced participants’ social and political trust as well as the impact of participants’ predispositions and level of satisfaction with the ECA on changes in trust. We find that participants that had positive predispositions and who were satisfied with the ECA were more likely to gain trust. Furthermore, we also find that the participants, in general, became more distrustful of political institutions, while their participation fostered increased social trust. This outcome differs from the intentions of the Estonian institutions which organized the ECA and sheds new light on the role of democratic innovations in the context of legitimacy crises. This is an important step forward in the scholarly understanding of the relationship between democratic innovation and trust….(More)”.
What privacy preserving techniques make possible: for transport authorities
Blog by Georgina Bourke: “The Mayor of London listed cycling and walking as key population health indicators in the London Health Inequalities Strategy. The pandemic has only amplified the need for people to use cycling as a safer and healthier mode of transport. Yet as the majority of cyclists are white, Black communities are less likely to get the health benefits that cycling provides. Groups like Transport for London (TfL) should monitor how different communities cycle and who is excluded. Organisations like the London Office of Technology and Innovation (LOTI) could help boroughs procure privacy preserving technology to help their efforts.
But at the moment, it’s difficult for public organisations to access mobility data held by private companies. One reason is because mobility data is sensitive. Even if you remove identifiers like name and address, there’s still a risk you can reidentify someone by linking different data sets together. This means you could track how an individual moved around a city. I wrote more about the privacy risks with mobility data in a previous blog post. The industry’s awareness of privacy issues in using and sharing mobility data is rising. In the case of Los Angeles Department of Transport’s Mobility Data Specification (LADOT), Uber is concerned about sharing anonymised data because of the privacy risk. Both organisations are now involved in a legal battle to see which has the rights to the data. This might have been avoided if Uber had applied privacy preserving techniques….
Privacy preserving techniques can help mobility providers share important insights with authorities without compromising peoples’ privacy.
Instead of requiring access to all customer trip data, authorities could ask specific questions like, where are the least popular places to cycle? If mobility providers apply techniques like randomised response, an individual’s identity is obscured by the noise added to the data. This means it’s highly unlikely that someone could be reidentified later on. And because this technique requires authorities to ask very specific questions – for randomised response to work, the answer has to be binary, ie Yes or No – authorities will also be practicing data minimisation by default.
It’s easy to imagine transport authorities like TfL combining privacy preserved mobility data from multiple mobility providers to compare insights and measure service provision. They could cross reference the privacy preserved bike trip data with demographic data in the local area to learn how different communities cycle. The first step to addressing inequality is being able to measure it….(More)”.
A Time for More Democracy Not Less
Graham Smith at Involve: “As part of the “A democratic response to COVID-19” project, we have been scanning print and social media to get a sense of how arguments for participation and deliberation are resonating in public debates….
Researchers from the Institute for Development Studies point to learning from previous pandemics. Drawing from their experience of working on the ebola epidemic in West Africa, they argue that pandemics are not just technical problems to be solved, but are social in character. They call for more deliberation and participation to ensure that decisions reflect not only the diversity of expert opinion, but also respond to the experiential knowledge of the most vulnerable….
A number of these proposals call for citizens’ assemblies, perhaps to the detriment of other participatory and deliberative processes. The Carnegie Trust offers a broader agenda, reminding us of the pressing contemporary significance of their pre-COVID-19 calls for co-design and co-production.
The Nuffield Council offers some simple guidance to government about how to act:
- Show us (the public) what it is doing and thinking across the range of issues of concern
- Set out the ethical considerations that inform(ed) its judgements
- Explain how it has arrived at decisions (including taking advice from e.g. SAGE, MEAG), and not that it is just ‘following the science’
- Invite a broad range of perspectives into the room, including wider public representation
- Think ahead – consult and engage other civic interests
We have found only a small number of examples of specific initiatives taking a participatory or deliberative approach to bringing in a broader range of voices in response to the pandemic. Our Covid Voices is gathering written statements of the experience of COVID-19 from those with health conditions or disabilities. The thinktank Demos is running a ‘People’s Commission’, inviting stories of lockdown life. It is not only reflections or stories. The Scottish Government invited ideas on how to tackle the virus, receiving and synthesising 4,000 suggestions. The West Midlands Combined Authority has established a citizens’ panel to guide its recovery work. The UK Citizens’ Assembly (and the French Convention) produced recommendations on how commitments to reach net zero carbon emissions need to be central to a post-COVID-19 recovery. We are sure that these examples only touch the surface of activity and that there will be many more initiatives that we are yet to hear about.
Of course, in one area, citizens have already taken matters into their own hands, with the huge growth in mutual-aid groups to ensure people’s emergency needs are met. The New Local Government Network has considered how public authorities could best support and work with such groups, and Danny Kruger MP was invited by the Prime Minister to investigate how to build on this community-level response.
The call for a more participatory and deliberative approach to governance needs to be more than a niche concern. As the Financial Times recognises, we need a “new civic contract” between government and the people….(More)”.
Creating a digital commons
Report by the IPPR (UK): ” There are, today, almost no parts of life that are untouched by the presence of data. Virtually every action we take produces some form of digital trail – our phones track our locations, our browsers track searches, our social network apps log our friends and family – even when we are only dimly aware of it.
It is the combination of this near-ubiquitous gathering of data with fast processing that has generated the economic and social transformation of the last few years – one that, if current developments in artificial intelligence (AI) continue, is only likely to accelerate. Combined with data-enabled technology, from the internet of things to 3D printing, we are potentially on the cusp of a radically different economy and society.
As the world emerges from the first phase of the pandemic, the demands for a socially just and sustainable recovery have grown. The data economy can and should be an essential part of that reconstruction, from the efficient management of energy systems to providing greater flexibility in working time. However, without effective public policy, and democratic oversight and management, the danger is that the tendencies in the data economy that we have already seen towards monopoly and opacity – reinforced, so far, by the crisis – will continue to dominate. It is essential, then, that planning for a fairer, more sustainable economy in the future build in active public policy for data…
This report focusses closely on data as the fundamental building block of the emerging economy, and argues that its use, management, ownership, and control as critical to shaping the future…(More)”.
Data for Policy: Junk-Food Diet or Technological Frontier?
Blog by Ed Humpherson at Data & Policy: “At the Office for Statistics Regulation, thinking about these questions is our day job. We set the standards for Government statistics and data through our Code of Practice for Statistics. And we review how Government departments are living up to these standards when they publish data and statistics. We routinely look at Government statistics are used in public debate.
Based on this, I would propose four factors that ensure that new data sources and tools serve the public good. They do so when:
- When data quality is properly tested and understood:
As my colleague Penny Babb wrote recently in a blog: “‘Don’t trust the data. If you’ve found something interesting, something has probably gone wrong!”. People who work routinely with data develop a sort of innate scepticism, which Penny’s blog captures neatly. Understanding the limitations of both the data, and the inferences you make about the data, are the starting point for any appropriate role for data and policy. Accepting results and insights from new data at face value is a mistake. Much better to test the quality, explore the risks of mistakes, and only then to share findings and conclusions.
2. When the risks of misleadingness are considered:
At OSR, we have an approach to misleadingness that focuses on whether a misuse of data might lead a listener to a wrong conclusion. In fact, by “wrong” we don’t mean in some absolute sense of objective truth; more that if they received the data presented in a different and more faithful way, they would change their mind. Here’s a really simple example: someone might hear that, of two neighbouring countries, one has a much lower fatality rate, when comparing deaths to positive tests for Covid-19. …
3. When the data fill gaps
Data gaps come in several forms. One gap, highlighted by the interest in real-time economic indicators, is timing. Economic statistics don’t really tell us what’s going on right now. Figures like GDP, trade and inflation tells us about some point in the (admittedly quite) recent past. This is the attraction of the real-time economic indicators, which the Bank of England have drawn on in their decisions during the pandemic. They give policymakers a much more real-time feel by filling in this timing gap.
Other gaps are not about time but about coverage….
4. When the data are available
Perhaps the most important thing for data and policy is to democratise the notion of who the data are for. Data (and policy itself) are not just for decision-making elites. They are a tool to help people make sense of their world, what is going on in their community, helping frame and guide the choices they make.
For this reason, I often instinctively recoil at narratives of data that focus on the usefulness of data to decision-makers. Of course, we are all decision-makers of one kind or another, and data can help us all. But I always suspect that the “data for decision-makers” narrative harbours an assumption that decisions are made by senior, central, expert people, who make decisions on behalf of society; people who are, in the words of the musical Hamilton, in the room where it happens. It’s this implication that I find uncomfortable.
That’s why, during the pandemic, our work at the Office for Statistics Regulation has repeatedly argued that data should be made available. We have published a statement that any management information referred to by a decision maker should be published clearly and openly. We call this equality of access.
We fight for equality of access. We have secured the publication of lots of data — on positive Covid-19 cases in England’s Local Authorities, on Covid-19 in prisons, on antibody testing in Scotland…. and several others.
Data and policy are a powerful mix. They offer huge benefits to society in terms of defining, understanding and solving problems, and thereby in improving lives. We should be pleased that the coming together of data and policy is being sped-up by the pandemic.
But to secure these benefits, we need to focus on four things: quality, misleadingness, gaps, and public availability….(More)”
Public perceptions on data sharing: key insights from the UK and the USA
Paper by Saira Ghafur, Jackie Van Dael, Melanie Leis and Ara Darzi, and Aziz Sheikh: “Data science and artificial intelligence (AI) have the potential to transform the delivery of health care. Health care as a sector, with all of the longitudinal data it holds on patients across their lifetimes, is positioned to take advantage of what data science and AI have to offer. The current COVID-19 pandemic has shown the benefits of sharing data globally to permit a data-driven response through rapid data collection, analysis, modelling, and timely reporting.
Despite its obvious advantages, data sharing is a controversial subject, with researchers and members of the public justifiably concerned about how and why health data are shared. The most common concern is privacy; even when data are (pseudo-)anonymised, there remains a risk that a malicious hacker could, using only a few datapoints, re-identify individuals. For many, it is often unclear whether the risks of data sharing outweigh the benefits.
A series of surveys over recent years indicate that the public holds a range of views about data sharing. Over the past few years, there have been several important data breaches and cyberattacks. This has resulted in patients and the public questioning the safety of their data, including the prospect or risk of their health data being shared with unauthorised third parties.
We surveyed people across the UK and the USA to examine public attitude towards data sharing, data access, and the use of AI in health care. These two countries were chosen as comparators as both are high-income countries that have had substantial national investments in health information technology (IT) with established track records of using data to support health-care planning, delivery, and research. The UK and USA, however, have sharply contrasting models of health-care delivery, making it interesting to observe if these differences affect public attitudes.
Willingness to share anonymised personal health information varied across receiving bodies (figure). The more commercial the purpose of the receiving institution (eg, for an insurance or tech company), the less often respondents were willing to share their anonymised personal health information in both the UK and the USA. Older respondents (≥35 years) in both countries were generally less likely to trust any organisation with their anonymised personal health information than younger respondents (<35 years)…
Despite the benefits of big data and technology in health care, our findings suggest that the rapid development of novel technologies has been received with concern. Growing commodification of patient data has increased awareness of the risks involved in data sharing. There is a need for public standards that secure regulation and transparency of data use and sharing and support patient understanding of how data are used and for what purposes….(More)”.
20’s the limit: How to encourage speed reductions
Report by The Wales Centre for Public Policy: “This report has been prepared to support the Welsh Government’s plan to introduce a 20mph national default speed limit in 2022. It aims to address two main questions: 1) What specific behavioural interventions might be implemented to promote driver compliance with 20mph speed limits in residential areas; and 2) are there particular demographics, community characteristics or other features that should form the basis of a segmentation approach?
The reasons for speeding are complex, but many behaviour change
techniques have been successfully applied to road safety, including some which use behavioural insights or “nudges”.
Drivers can be segmented into three types: defiers (a small minority),
conformers (the majority) and champions (a minority). Conformers are law abiding citizens who respect social norms – getting this group to comply can achieve a tipping point.
Other sectors have shown that providing information is only effective if part of a wider package of measures and that people are most open to
change at times of disruption or learning (e.g. learner drivers)….(More)”.
Rethinking citizen engagement for an inclusive energy transition
Urban Futures Studio: “In July 2020, we published our new essay ‘What, How and Who? Designing inclusive interactions in the energy transition’ (Bronsvoort, Hoffman and Hajer, 2020). In this essay, we argue that how the interactions between citizens and governments are shaped and enacted, has a large influence on who gets involved and to what extend people feel heard. To apply this approach to cases, we distinguish between three dimensions of interaction:
- What (the defined object or issue at hand)
- How (the setting and staging of the interaction)
- Who (the target groups and protagonists of the process)
Focusing on the issue of form, we argue that processes for interaction between citizens and governments should be designed in a way that is more future oriented, organized over the long term, in closer proximity to citizens and with attention to the powerful role of ‘in-betweeners’ and ‘in-between’ places such as community houses, where people can meet to deliberate on the wide range of possible futures for their neighbourhood.
Towards a multiplicity of future visions for sustainable cities
The energy transition has major consequences for the way we live, work, move and consume. For such complex transitions, governments need to engage and collaborate with citizens and other stakeholders. Their engagement enriches existing visions on future neighbourhoods, inform local policies and stimulate change. But how do you shape and organize such a participatory process? While governments use a wide range of public participation methods, many researchers have emphasized the limitations of many of these conventional methods with regard to the inclusion of diverse groups of citizens and in bridging discrepancies between government approaches and people’s lived experiences.
Rethinking citizen engagement for an inclusive energy transition
To help rethink citizen engagement, the Urban Futures Studio investigates existing and new approaches to citizen engagement and how they are practised by governments and societal actors. Following our essay research, our next project on citizen engagement includes a study on its relation to experimentation as a novel mode of governance. The goal of this research is to show insights into how citizen engagement manifests itself in the context of experimental governance on the neighbourhood level. By investigating the interactions between citizens, governments and other stakeholders in different types of participatory projects, we aim to gain a better understanding of how citizens are engaged and included in energy transition experiments and how we can improve its level of inclusion.
We use a relational approach of citizen engagement, by which we view participatory processes as collective practices that both shape and are shaped by their ‘matter of concern’, their public and their setting and staging. This view places emphasis on the form and conditions under which the interaction takes place. For example, the initiative of Places of Hope showed that engagement can be organised in diverse ways and can create new collectives….(More)”.
Four Principles for Integrating AI & Good Governance
Oxford Commission on AI and Good Governance: “Many governments, public agencies and institutions already employ AI in providing public services, the distribution of resources and the delivery of governance goods. In the public sector, AI-enabled governance may afford new efficiencies that have the potential to transform a wide array of public service tasks.
But short-sighted design and use of AI can create new problems, entrench existing inequalities, and calcify and ultimately undermine government organizations.
Frameworks for the procurement and implementation of AI in public service have widely remained undeveloped. Frequently, existing regulations and national laws are no longer fit for purpose to ensure
good behaviour (of either AI or private suppliers) and are ill-equipped to provide guidance on the democratic use of AI.
As technology evolves rapidly, we need rules to guide the use of AI in ways that safeguard democratic values. Under what conditions can AI be put into service for good governance?
We offer a framework for integrating AI with good governance. We believe that with dedicated attention and evidence-based policy research, it should be possible to overcome the combined technical and organizational challenges of successfully integrating AI with good governance. Doing so requires working towards:
Inclusive Design: issues around discrimination and bias of AI in relation to inadequate data sets, exclusion of minorities and under-represented
groups, and the lack of diversity in design.
Informed Procurement: issues around the acquisition and development in relation to due diligence, design and usability specifications and the assessment of risks and benefits.
Purposeful Implementation: issues around the use of AI in relation to interoperability, training needs for public servants, and integration with decision-making processes.
Persistent Accountability: issues around the accountability and transparency of AI in relation to ‘black box’ algorithms, the interpretability and explainability of systems, monitoring and auditing…(More)”