How data governance technologies can democratize data sharing for community well-being

Curated on Posted on by Stefaan Verhulst

Paper by Dan Wu, Stefaan Verhulst, Alex Pentland, Thiago Avila, Kelsey Finch, and Abhishek Gupta in Data & Policy (Cambridge University Press) focusing on “Data sharing efforts to allow underserved groups and organizations to overcome the concentration of power in our data landscape…

A few special organizations, due to their data monopolies and resources, are able to decide which problems to solve and how to solve them. But even though data sharing creates a counterbalancing democratizing force, it must nevertheless be approached cautiously. Underserved organizations and groups must navigate difficult barriers related to technological complexity and legal risk.

To examine what those common barriers are, one type of data sharing effort—data trusts—are examined, specifically the reports commenting on that effort. To address these practical issues, data governance technologies have a large role to play in democratizing data trusts safely and in a trustworthy manner. Yet technology is far from a silver bullet. It is dangerous to rely upon it. But technology that is no-code, flexible, and secure can help more responsibly operate data trusts. This type of technology helps innovators put relationships at the center of their efforts….(More)”.

Understanding crowdsourcing projects: A review on the key design elements of a crowdsourcing initiative

Curated on Posted on by Stefaan Verhulst

Paper by Rea Karachiwalla and Felix Pinkow: “Crowdsourcing has gained considerable traction over the past decade and has emerged as a powerful tool in the innovation process of organizations. Given its growing significance in practice, a profound understanding of the concept is crucial. The goal of this study is to develop a comprehensive understanding of designing crowdsourcing projects for innovation by identifying and analyzing critical design elements of crowdsourcing contests. Through synthesizing the principles of the social exchange theory and absorptive capacity, this study provides a novel conceptual configuration that accounts for both the attraction of solvers and the ability of the crowdsourcer to capture value from crowdsourcing contests. Therefore, this paper adopts a morphological approach to structure the four dimensions, namely, (i) task, (ii) crowd, (iii) platform and (iv) crowdsourcer, into a conceptual framework to present an integrated overview of the various crowdsourcing design options. The morphological analysis allows the possibility of identifying relevant interdependencies between design elements, based on the goals of the problem to be crowdsourced. In doing so, the paper aims to enrich the extant literature by providing a comprehensive overview of crowdsourcing and to serve as a blueprint for practitioners to make more informed decisions when designing and executing crowdsourcing projects….(More)”.

New knowledge environments. On the possibility of a citizen social science.

Curated on Posted on by Stefaan Verhulst

Article by Joseph Perelló: “Citizen science is in a process of consolidation, with a wide variety of practices and perspectives. Social sciences and humanities occupy a small space despite the obvious social dimension of citizen science. In this sense, citizen social science can enrich the concept of citizen science both because the research objective can also be of a social nature and because it provides greater reflection on the active participation of individuals, groups, or communities in research projects. Based on different experiences, this paper proposes that citizen social science should have the capacity to empower participants and provide them with skills to promote collective actions or public policies based on a co-created knowledge.

Citizen science is commonly recognised as the participation of the public in scientific research (Vohland et al., 2021). It has been promoted as a way to collect massive amounts of data and accelerate its processing, while also raising awareness and spreading knowledge and a better understanding of both scientific methods and the social relevance of results (Parrish et al., 2019). Some researchers support the idea of maintaining the generality and vagueness of the term citizen science (Auerbach et al., 2019), due to the youth of the discipline and the different ways it can be understood (Haklay et al., 2020). Such diversity can be considered positively, as a way to enrich citizen science and, more generally, as a catalyst for the emergence of trans-disciplinary and transformative science.

The sociologist Alan Irwin, one of the authors to whom we owe the concept, already said over 25 years ago: «Citizen Science evokes a science which assists the needs and concerns of citizens» (Irwin, 1995, p. xi). The book argues that citizens can create reliable knowledge. However, decades later, the number of contributions using the term citizen science in social sciences and humanities is scarce, smaller than the number of items published in environmental sciences or biology, which predominate in the field (Kullenberg & Kasperowski, 2016). Nevertheless, there is a growing consensus that social sciences and humanities are necessary for citizen science to reach maturity, both so that the object of study can also be of a social nature, and also so that these disciplines can provide a more elaborate reflection on participation in citizen science projects (Tauginienė et al., 2020)….(More)”.

How laws affect the perception of norms: empirical evidence from the lockdown

Curated on Posted on by Stefaan Verhulst

Paper by Roberto Galbiati, Emeric Henry, Nicolas Jacquemet, and Max Lobeck: “Laws not only affect behavior due to changes in material payoffs, but they may also change the perception individuals have of societal norms, either by shifting them directly or by providing information on these norms. Using detailed daily survey data and exploiting the introduction of lockdown measures in the UK in the context of the COVID-19 health crisis, we provide causal evidence that the law drastically changed the perception of the norms regarding social distancing behaviors. We show this effect of laws on perceived norms is mostly driven by an informational channel….(More)”.

Disrupting the Welfare State? Digitalisation and the Retrenchment of Public Sector Capacity

Curated on Posted on by Stefaan Verhulst

Paper by Rosie Collington: “Welfare state bureaucracies the world over have adopted far-reaching digitalisation reforms in recent years. From the deployment of AI in service management, to the ‘opening up’ of administrative datasets, digitalisation initiatives have uprooted established modes of public sector organisation and administration. And, as this paper suggests, they have also fundamentally transformed the political economy of the welfare state. Through a case study of Danish reforms between 2002 and 2019, the analysis finds that public sector digitalisation has entailed the transfer of responsibility for key infrastructure to private actors. Reforms in Denmark have not only been pursued in the name of public sector improvement and efficiency. A principal objective of public sector digitalisation has rather been the growth of Denmark’s nascent digital technology industries as part of the state’s wider export-led growth strategy, adopted in response to functional pressures on the welfare state model. The attempt to deliver fiscal stability in this way has, paradoxically, produced retrenchment of critical assets and capabilities. The paper’s findings hold important implications for states embarking on public sector digitalisation reforms, as well as possibilities for future research on how states can harness technological progress in the interests of citizens – without hollowing out in the process….(More)”.

Research directions in policy modeling: Insights from comparative analysis of recent projects

Curated on Posted on by Stefaan Verhulst

Paper by Alexander Ronzhyn and Maria A. Wimmer: “With the increased availability of data and the capacity to make sense of these data, computational approaches to analyze, model and simulate public policy evolved toward viable instruments to deliberate, plan, and evaluate them in different areas of application. Such examples include infrastructure, mobility, monetary, or austerity policies, policies on different aspects of societies (health, pandemic, skills, inclusion, etc.). Technological advances along with the evolution of theoretical models and frameworks open valuable opportunities, while at the same time, posing new challenges. The paper investigates the current state of research in the domain and aims at identifying the most pressing areas for future research. This is done through both literature research of policy modeling and the analysis of research and innovation projects that either focus on policy modeling or involve it as a significant component of the research design. In the paper, 16 recent projects involving the keyword policy modeling were analyzed. The majority of projects concern the application of policy modeling to a specific domain or area of interest, while several projects tackled the cross-cutting topics (risk and crisis management). The detailed analysis of the projects led to topics of future research in the domain of policy modeling. Most prominent future research topics in policy modeling include stakeholder involvement approaches, applicability of research results, handling complexity of models, integration of models from different modeling and simulation paradigms and approaches, visualization of simulation results, real-time data processing, and scalability. These aspects require further research to appropriately contribute to further advance the field….(More)”.

The Diffusion of Disruptive Technologies

Curated on Posted on by Stefaan Verhulst

Paper by Nicholas Bloom, Tarek Alexander Hassan, Aakash Kalyani, Josh Lerner & Ahmed Tahoun: “We identify novel technologies using textual analysis of patents, job postings, and earnings calls. Our approach enables us to identify and document the diffusion of 29 disruptive technologies across firms and labor markets in the U.S. Five stylized facts emerge from our data. First, the locations where technologies are developed that later disrupt businesses are geographically highly concentrated, even more so than overall patenting. Second, as the technologies mature and the number of new jobs related to them grows, they gradually spread across space. While initial hiring is concentrated in high-skilled jobs, over time the mean skill level in new positions associated with the technologies declines, broadening the types of jobs that adopt a given technology. At the same time, the geographic diffusion of low-skilled positions is significantly faster than higher-skilled ones, so that the locations where initial discoveries were made retain their leading positions among high-paying positions for decades. Finally, these technology hubs are more likely to arise in areas with universities and high skilled labor pools….(More)”

Transparency’s AI Problem

Curated on Posted on by Stefaan Verhulst

Paper by Hannah Bloch-Wehba: “A consensus seems to be emerging that algorithmic governance is too opaque and ought to be made more accountable and transparent. But algorithmic governance underscores the limited capacity of transparency law—the Freedom of Information Act and its state equivalents—to promote accountability. Drawing on the critical literature on “open government,” this Essay shows that algorithmic governance reflects and amplifies systemic weaknesses in the transparency regime, including privatization, secrecy, private sector cooptation, and reactive disclosure. These deficiencies highlight the urgent need to reorient transparency and accountability law toward meaningful public engagement in ongoing oversight. This shift requires rethinking FOIA’s core commitment to public disclosure of agency records, exploring instead alternative ways to empower the public and to shed light on decisionmaking. The Essay argues that new approaches to transparency and accountability for algorithmic governance should be independent of private vendors, and ought to adequately represent the interests of affected individuals and communities. These considerations, of vital importance for the oversight of automated systems, also hold broader lessons for efforts to recraft open government obligations in the public interest….(More)”

Manipulation As Theft

Curated on Posted on by Stefaan Verhulst

Paper by Cass Sunstein: “Should there be a right not to be manipulated? What kind of right? On Kantian grounds, manipulation, lies, and paternalistic coercion are moral wrongs, and for similar reasons; they deprive people of agency, insult their dignity, and fail to respect personal autonomy. On welfarist grounds, manipulation, lies, and paternalistic coercion share a different characteristic; they displace the choices of those whose lives are directly at stake, and who are likely to have epistemic advantages, with the choices of outsiders, who are likely to lack critical information. Kantians and welfarists should be prepared to endorse a (moral) right not to be manipulated, though on very different grounds.

The moral prohibition on manipulation, like the moral prohibition on lies, should run against officials and regulators, not only against private institutions. At the same time, the creation of a legal right not to be manipulated raises hard questions, in part because of definitional challenges; there is a serious risk of vagueness and a serious risk of overbreadth. (Lies, as such, are not against the law, and the same is true of unkindness, inconsiderateness, and even cruelty.) With welfarist considerations in mind, it is probably best to start by prohibiting particular practices, while emphasizing that they are forms of manipulation and may not count as fraud. The basic goal should be to build on the claim that in certain cases, manipulation is a form of theft; the law should forbid theft, whether it occurs through force, lies, or manipulation. Some manipulators are thieves….(More)”

The uncounted: politics of data in global health

Curated on Posted on by Stefaan Verhulst

Essay by Sara L M Davis: “Data is seductive in global health politics. It seduces donors with the promise of cost-effectiveness in making the right investments in people’s health and of ensuring they get results and performance from the state projects they fund. It seduces advocates of gender equality with its power to make gender differences in health outcomes and burdens visible. The seduction of data is that of the quick or technocratic fix to complex social and political problems. Are women disproportionately impacted by COVID-19? Get better data to find out the extent of the problem. Do you want to save as many lives as possible?…(More)”.