Why Predictive Algorithms are So Risky for Public Sector Bodies


Paper by Madeleine Waller and Paul Waller: “This paper collates multidisciplinary perspectives on the use of predictive analytics in government services. It moves away from the hyped narratives of “AI” or “digital”, and the broad usage of the notion of “ethics”, to focus on highlighting the possible risks of the use of prediction algorithms in public administration. Guidelines for AI use in public bodies are currently available, however there is little evidence these are being followed or that they are being written into new mandatory regulations. The use of algorithms is not just an issue of whether they are fair and safe to use, but whether they abide with the law and whether they actually work.

Particularly in public services, there are many things to consider before implementing predictive analytics algorithms, as flawed use in this context can lead to harmful consequences for citizens, individually and collectively, and public sector workers. All stages of the implementation process of algorithms are discussed, from the specification of the problem and model design through to the context of their use and the outcomes.

Evidence is drawn from case studies of use in child welfare services, the US Justice System and UK public examination grading in 2020. The paper argues that the risks and drawbacks of such technological approaches need to be more comprehensively understood, and testing done in the operational setting, before implementing them. The paper concludes that while algorithms may be useful in some contexts and help to solve problems, it seems those relating to predicting real life have a long way to go to being safe and trusted for use. As “ethics” are located in time, place and social norms, the authors suggest that in the context of public administration, laws on human rights, statutory administrative functions, and data protection — all within the principles of the rule of law — provide the basis for appraising the use of algorithms, with maladministration being the primary concern rather than a breach of “ethics”….(More)”

Impact through Engagement: Co-production of administrative data research


Paper by Elizabeth Nelson and Frances Burns: “The Administrative Data Research Centre Northern Ireland (ADRC NI) is a research partnership between Queen’s University Belfast and Ulster University to facilitate access to linked administrative data for research purposes for public benefit and for evidence-based policy development. This requires a social licence extended by publics which is maintained by a robust approach to engagement and involvement.

Public engagement is central to the ADRC NI’s approach to research. Research impact is pursued and secured through robust engagement and co-production of research with publics and key stakeholders. This is done by focusing on data subjects (the cohort of people whose lives make up the datasets, placing value on experts by experience outside of academic knowledge, and working with public(s) as key data advocates, through project steering committees and targeted events with stakeholders. The work is led by a dedicated Public Engagement, Communications and Impact Manager.

While there are strengths and weaknesses to the ADRC NI approach, examples of successful partnerships and clear pathways to impact demonstrate its utility and ability to amplify the positive impact of administrative data research. Working with publics as data use becomes more ubiquitous in a post-COVID-19 world will become more critical. ADRC NI’s model is a potential way forward….(More)”.

See also Special Issue on Public Involvement and Engagement by the International Journal of Population Data Science.

Civic Technologies: Research, Practice and Open Challenges


Paper by Pablo Aragon, Adriana Alvarado Garcia, Christopher A. Le Dantec, Claudia Flores-Saviaga, and Jorge Saldivar: “Over the last years, civic technology projects have emerged around the world to advance open government and community action. Although Computer-Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI) communities have shown a growing interest in researching issues around civic technologies, yet most research still focuses on projects from the Global North. The goal of this workshop is, therefore, to advance CSCW research by raising awareness for the ongoing challenges and open questions around civic technology by bridging the gap between researchers and practitioners from different regions.

The workshop will be organized around three central topics: (1) discuss how the local context and infrastructure affect the design, implementation, adoption, and maintenance of civic technology; (2) identify key elements of the configuration of trust among government, citizenry, and local organizations and how these elements change depending on the sociopolitical context where community engagement takes place; (3) discover what methods and strategies are best suited for conducting research on civic technologies in different contexts. These core topics will be covered across sessions that will initiate in-depth discussions and, thereby, stimulate collaboration between the CSCW research community and practitioners of civic technologies from both Global North and South….(More)”.

Open government data, uncertainty and coronavirus: An infodemiological case study


Paper by Nikolaos Yiannakoulias, Catherine E. Slavik, Shelby L. Sturrock, J. Connor Darlington: “Governments around the world have made data on COVID-19 testing, case numbers, hospitalizations and deaths openly available, and a breadth of researchers, media sources and data scientists have curated and used these data to inform the public about the state of the coronavirus pandemic. However, it is unclear if all data being released convey anything useful beyond the reputational benefits of governments wishing to appear open and transparent. In this analysis we use Ontario, Canada as a case study to assess the value of publicly available SARS-CoV-2 positive case numbers. Using a combination of real data and simulations, we find that daily publicly available test results probably contain considerable error about individual risk (measured as proportion of tests that are positive, population based incidence and prevalence of active cases) and that short term variations are very unlikely to provide useful information for any plausible decision making on the part of individual citizens. Open government data can increase the transparency and accountability of government, however it is essential that all publication, use and re-use of these data highlight their weaknesses to ensure that the public is properly informed about the uncertainty associated with SARS-CoV-2 information….(More)”

Is the Coronavirus Catalyzing New Civic Collaborations for Open Government?


Paper by Abigail Bellows and Nada Zodhy: “From Africa to Latin America to Europe, the coronavirus pandemic has generated a surge in public demand for government transparency and accountability. To seize this window for reform, elite and grassroots civic actors concerned with open governance must overcome the cleavage that has long existed between them.

Thus far, the pandemic has catalyzed some new civic collaborations, but not at the scale or depth needed to seize that window. In general, civil society groups report feeling more isolated during the pandemic. In some places, the urgency of tackling open government issues during the pandemic has helped overcome that isolation by deepening partnerships among existing networks. But in other places, those partnerships have yet to take shape, and new alliances are less likely to form without the benefit of face-to-face interactions. Even the partnerships that have crystallized or deepened do not appear to be changing the fundamental roles of elite and grassroots civic actors. It is possible that this shift may happen over time. Or it may be that the pandemic alone is not enough to dislodge structural barriers to deeper cooperation.

The pandemic has dramatically changed the operations of elite and grassroots actors alike. The impact of those changes on collaboration between the two depends on preexisting levels of technological capacity. In places with limited connectivity, the pandemic has exacerbated the digital divide, adversely affecting grassroots actors. Meanwhile, in places with good connectivity, technology is enabling broader (though shallower) participation, laying the groundwork for more elite-grassroots collaboration.

Although many civil society groups are struggling financially during the pandemic, those effects are mitigated to some degree by continuing donor interest in the open government sector. This is encouraging, as coalition building requires dedicated, flexible resources.

Finally, it is a more dangerous time to be working on open government issues in general, and grassroots actors bear disproportionate risks in doing so. This underscores the need for more vertical alliances to mitigate civic space threats.

Moving forward, practitioners need to capitalize on public momentum around open governance by cultivating new elite-grassroots partnerships built on mutual respect. These partnerships will benefit from continued learning about which pandemic-era operational adaptations should be sustained (such as blended modes of in-person and online work) and how to mitigate the costs of doing so. Donors should drive timely investment toward coalition building in places where it is missing, alongside more direct support to grassroots actors…(More)”.

Armchair Survey Research: A Possible Post-COVID-19 Boon in Social Science


Paper by Samiul Hasan: “Post-COVID-19 technologies for higher education and corporate communication have opened-up wonderful opportunity for Online Survey Research. These technologies could be used for one-to-one interview, group interview, group questionnaire survey, online questionnaire survey, or even ‘focus group’ discussions. This new trend, which may aptly be called ‘armchair survey research’ may be the only or new trend in social science research. If that is the case, an obvious question might be what is ‘survey research’ and how is it going to be easier in the post-COVID-19 world? My intention is to offer some help to the promising researchers who have all quality and eagerness to undertake good social science research for publication, but no fund.

The text is divided into three main parts. Part one deals with “Science, Social Science and Research” to highlight some important points about the importance of ‘What’, ‘Why’, and ‘So what’ and ‘framing of a research question’ for a good research. Then the discussion moves to ‘reliability and validity’ in social science research including falsifiability, content validity, and construct validity. This part ends with discussions on concepts, constructs, and variables in a theoretical (conceptual) framework. The second part deals categorically with ‘survey research’ highlighting the use and features of interviews and questionnaire surveys. It deals primarily with the importance and use of nominal response or scale and ordinal response or scale as well as the essentials of question content and wording, and question sequencing. The last part deals with survey research in the post-COVID-19 period highlighting strategies for undertaking better online survey research, without any fund….(More)”.

The Case for Digital Activism: Refuting the Fallacies of Slacktivism


Paper by Nora Madison and Mathias Klang: “This paper argues for the importance and value of digital activism. We first outline the arguments against digitally mediated activism and then address the counter-arguments against its derogatory criticisms. The low threshold for participating in technologically mediated activism seems to irk its detractors. Indeed, the term used to downplay digital activism is slacktivism, a portmanteau of slacker and activism. The use of slacker is intended to stress the inaction, low effort, and laziness of the person and thereby question their dedication to the cause. In this work we argue that digital activism plays a vital role in the arsenal of the activist and needs to be studied on its own terms in order to be more fully understood….(More)”

Remaking the Commons: How Digital Tools Facilitate and Subvert the Common Good


Paper by Jessica Feldman:”This scoping paper considers how digital tools, such as ICTs and AI, have failed to contribute to the “common good” in any sustained or scalable way. This is attributed to a problem that is at once political-economic and technical.

Many digital tools’ business models are predicated on advertising: framing the user as an individual consumer-to-be-targeted, not as an organization, movement, or any sort of commons. At the level of infrastructure and hardware, the increased privatization and centralization of transmission and production leads to a dangerous bottlenecking of communication power, and to labor and production practices that are undemocratic and damaging to common resources.

These practices escalate collective action problems, pose a threat to democratic decision making, aggravate issues of economic and labor inequality, and harm the environment and health. At the same time, the growth of both AI and online community formation raise questions around the very definition of human subjectivity and modes of relationality. Based on an operational definition of the common good grounded in ethics of care, sustainability, and redistributive justice, suggestions are made for solutions and further research in the areas of participatory design, digital democracy, digital labor, and environmental sustainability….(More)”

Evaluating Identity Disclosure Risk in Fully Synthetic Health Data: Model Development and Validation


Paper by Khaled El Emam et al: “There has been growing interest in data synthesis for enabling the sharing of data for secondary analysis; however, there is a need for a comprehensive privacy risk model for fully synthetic data: If the generative models have been overfit, then it is possible to identify individuals from synthetic data and learn something new about them.

Objective: The purpose of this study is to develop and apply a methodology for evaluating the identity disclosure risks of fully synthetic data.

Methods: A full risk model is presented, which evaluates both identity disclosure and the ability of an adversary to learn something new if there is a match between a synthetic record and a real person. We term this “meaningful identity disclosure risk.” The model is applied on samples from the Washington State Hospital discharge database (2007) and the Canadian COVID-19 cases database. Both of these datasets were synthesized using a sequential decision tree process commonly used to synthesize health and social science data.

Results: The meaningful identity disclosure risk for both of these synthesized samples was below the commonly used 0.09 risk threshold (0.0198 and 0.0086, respectively), and 4 times and 5 times lower than the risk values for the original datasets, respectively.

Conclusions: We have presented a comprehensive identity disclosure risk model for fully synthetic data. The results for this synthesis method on 2 datasets demonstrate that synthesis can reduce meaningful identity disclosure risks considerably. The risk model can be applied in the future to evaluate the privacy of fully synthetic data….(More)”.

Algorithmic governance: A modes of governance approach


Article by Daria Gritsenko and Matthew Wood: “This article examines how modes of governance are reconfigured as a result of using algorithms in the governance process. We argue that deploying algorithmic systems creates a shift toward a special form of design‐based governance, with power exercised ex ante via choice architectures defined through protocols, requiring lower levels of commitment from governing actors. We use governance of three policy problems – speeding, disinformation, and social sharing – to illustrate what happens when algorithms are deployed to enable coordination in modes of hierarchical governance, self‐governance, and co‐governance. Our analysis shows that algorithms increase efficiency while decreasing the space for governing actors’ discretion. Furthermore, we compare the effects of algorithms in each of these cases and explore sources of convergence and divergence between the governance modes. We suggest design‐based governance modes that rely on algorithmic systems might be re‐conceptualized as algorithmic governance to account for the prevalence of algorithms and the significance of their effects….(More)”.