Paper by Joseph Donia and Jay Shaw: “Applications of artificial intelligence / machine learning (AI/ML) are dynamic and rapidly growing, and although multi-purpose, are particularly consequential in health care. One strategy for anticipating and addressing ethical challenges related to AI/ML for health care is co-design – or involvement of end users in design. Co-design has a diverse intellectual and practical history, however, and has been conceptualized in many different ways. Moreover, the unique features of AI/ML introduce challenges to co-design that are often underappreciated. This review summarizes the research literature on involvement in health care and design, and informed by critical data studies, examines the extent to which co-design as commonly conceptualized is capable of addressing the range of normative issues raised by AI/ML for health. We suggest that AI/ML technologies have amplified existing challenges related to co-design, and created entirely new challenges. We outline five co-design ‘myths and misconceptions’ related to AI/ML for health that form the basis for future research and practice. We conclude by suggesting that the normative strength of a co-design approach to AI/ML for health can be considered at three levels: technological, health care system, and societal. We also suggest research directions for a ‘new era’ of co-design capable of addressing these challenges….(More)”.
The Society of Algorithms
Paper by Jenna Burrell and Marion Fourcade: “The pairing of massive data sets with processes—or algorithms—written in computer code to sort through, organize, extract, or mine them has made inroads in almost every major social institution. This article proposes a reading of the scholarly literature concerned with the social implications of this transformation. First, we discuss the rise of a new occupational class, which we call the coding elite. This group has consolidated power through their technical control over the digital means of production and by extracting labor from a newly marginalized or unpaid workforce, the cybertariat. Second, we show that the implementation of techniques of mathematical optimization across domains as varied as education, medicine, credit and finance, and criminal justice has intensified the dominance of actuarial logics of decision-making, potentially transforming pathways to social reproduction and mobility but also generating a pushback by those so governed. Third, we explore how the same pervasive algorithmic intermediation in digital communication is transforming the way people interact, associate, and think. We conclude by cautioning against the wildest promises of artificial intelligence but acknowledging the increasingly tight coupling between algorithmic processes, social structures, and subjectivities….(More)”.
Data ownership revisited: clarifying data accountabilities in times of big data and analytics
Paper by Martin Fadler and Christine Legner: “Today, a myriad of data is generated via connected devices and digital applications. In order to benefit from these data, companies have to develop their capabilities related to big data and analytics (BDA). A critical factor that is often cited concerning the “soft” aspects of BDA is data ownership, i.e., clarifying the fundamental rights and responsibilities for data. IS research has investigated data ownership for operational systems and data warehouses, where the purpose of data processing is known. In the BDA context, defining accountabilities for data is more challenging because data are stored in data lakes and used for previously unknown purposes. Based on four case studies, we identify ownership principles and three distinct types: data, data platform, and data product ownership. Our research answers fundamental questions about how data management changes with BDA and lays the foundation for future research on data and analytics governance….(More)”.
Who will benefit from big data? Farmers’ perspective on willingness to share farm data
Paper by Airong Zhang et al : “Agricultural industries are facing a dual challenge of increasing production to meet the growing population with a disruptive changing climate and, at the same time, reducing its environmental impacts. Digital agriculture supported by big data technology has been regarded as a solution to address such challenges. However, realising the potential value promised by big data technology depends upon farm-level data generated by digital agriculture being aggregated at scale. Yet, there is limited understanding of farmers’ willingness to contribute agricultural data for analysis and how that willingness could be affected by their perceived beneficiary of the aggregated data.
The present study aimed to investigate farmers’ perspective on who would benefit the most from the aggregated agricultural data, and their willingness to share their input and output farm data with a range of agricultural sector stakeholders (i.e. other farmers, industry and government statistical organisations, technology businesses, and research institutions). To do this, we conducted a computer-assisted telephone interview with 880 Australian farmers from broadacre agricultural sectors. The results show that only 34 % of participants regarded farmers as the primary beneficiary of aggregated agricultural data, followed by agribusiness (35 %) and government (21 %) as the main beneficiary. The participants’ willingness to share data was mostly positive. However, the level of willingness fluctuated depending on who was perceived as the primary beneficiary and with which stakeholder the data would be shared. While participants reported concerns over aggregated farm data being misused and privacy of own farm data, perception of farmers being the primary beneficiary led to the lowest levels of concerns. The findings highlight that, to seize the opportunities of sustainable agriculture through applying big data technologies, significant value propositions for farmers need to be created to provide a reason for farmers to share data, and a higher level of trust between farmers and stakeholders, especially technology and service providers, needs to be established….(More)”.
The Place of Local Government Law in the Urban Digital Age
Paper by Beatriz Botero Arcila: “A central theme of local government law scholarship is how local government law shapes urban policymaking. Local government law is the body of law that establishes the formal authority of cities and, as such, it creates the limited legal framework in which municipalities operate. Consequently, it shapes the potential economic development strategies of cities. In the digital economy, the rise of digital technology firms that provide urban services and services for city governments promises to entice local innovation and business opportunities and represent important economic development opportunities. Nevertheless, the implementation and deployment of these technologies in cities have also become regulatory challenges for cities and have raised important concerns about their potential to increase urban inequality and corporate power while entrenching surveillance in the city-fabric.
However, the literature that warns on these risks rarely addresses how the legal system and, in particular local government law, shapes the form of these technologies and creates incentives for local governments and the companies themselves to adopt, regulate and design these technologies in particular ways. This Essay presents an analysis of how local government law participates in shaping the present form of the urban digital information economy….(More)”.
Systemic Mapping and Design Research: Towards Participatory Democratic Engagement
Paper by Juan de LaRosa, Stan Ruecker, Carolina Giraldo Nohora: “This article presents an argument to extend possibilities and discussions about the role of design in democratic participation. We ground this argument in case studies and observations of several grassroots experimental participatory design workshops run with the intention of producing spaces for community deliberation and a tangible transformation of these communities. These cases show how systemic mapping and prototyping are used to increase community understanding of how potential futures represent values systems that should correspond to the values the community would like to see in place. The methodologies used on these workshops are presented it here as an opportunity to question the role of design in democratic deliberation and policy making….(More)”.
Principled Data Access: Building Public-private Data Partnerships for Better Official Statistics
Paper by Claudia Biancotti, Oscar Borgogno and Giovanni Veronese: “Official statistics serve as an important compass for policymakers due to their quality, impartiality, and transparency. In the current post-pandemic environment of great uncertainty and widespread disinformation, they need to serve this purpose more than ever. The wealth of data produced by the digital society (e.g. from user activity on online platforms or from Internet-of-Things devices) could help official statisticians improve the salience, timeliness and depth of their output. This data, however, tends to be locked away within the private sector. We argue that this should change and we propose a set of principles under which the public and the private sector can form partnerships to leverage the potential of new-generation data in the public interest. The principles, compatible with a variety of legal frameworks, aim at establishing trust between data collectors, data subjects, and statistical authorities, while also ensuring the technical usability of the data and the sustainability of partnerships over time. They are driven by a logic of incentive compatibility and burden sharing….(More)”
Fair algorithms for selecting citizens’ assemblies
Flanigan et al in Nature: “Globally, there has been a recent surge in ‘citizens’ assemblies’1, which are a form of civic participation in which a panel of randomly selected constituents contributes to questions of policy. The random process for selecting this panel should satisfy two properties. First, it must produce a panel that is representative of the population. Second, in the spirit of democratic equality, individuals would ideally be selected to serve on this panel with equal probability. However, in practice these desiderata are in tension owing to differential participation rates across subpopulations Here we apply ideas from fair division to develop selection algorithms that satisfy the two desiderata simultaneously to the greatest possible extent: our selection algorithms choose representative panels while selecting individuals with probabilities as close to equal as mathematically possible, for many metrics of ‘closeness to equality’. Our implementation of one such algorithm has already been used to select more than 40 citizens’ assemblies around the world. As we demonstrate using data from ten citizens’ assemblies, adopting our algorithm over a benchmark representing the previous state of the art leads to substantially fairer selection probabilities. By contributing a fairer, more principled and deployable algorithm, our work puts the practice of sortition on firmer foundations. Moreover, our work establishes citizens’ assemblies as a domain in which insights from the field of fair division can lead to high-impact applications….(More)”
Using Satellite Imagery and Deep Learning to Evaluate the Impact of Anti-Poverty Programs
Paper by Luna Yue Huang, Solomon M. Hsiang & Marco Gonzalez-Navarro: “The rigorous evaluation of anti-poverty programs is key to the fight against global poverty. Traditional approaches rely heavily on repeated in-person field surveys to measure program effects. However, this is costly, time-consuming, and often logistically challenging. Here we provide the first evidence that we can conduct such program evaluations based solely on high-resolution satellite imagery and deep learning methods. Our application estimates changes in household welfare in a recent anti-poverty program in rural Kenya. Leveraging a large literature documenting a reliable relationship between housing quality and household wealth, we infer changes in household wealth based on satellite-derived changes in housing quality and obtain consistent results with the traditional field-survey based approach. Our approach generates inexpensive and timely insights on program effectiveness in international development programs…(More)”.
Safeguarding Public Values in Cooperation with Big Tech Companies: The Case of the Austrian Contact Tracing App Stopp Corona
Paper by Valerie Eveline: “In April 2020, at the beginning of the COVID-19 pandemic, the Austrian Red Cross announced it was encouraging a cooperation with Google and Apple’s Exposure Notification Framework to develop the so-called Stop Corona app – a contact tracing app which would support health personnel in monitoring the spread of the virus to prevent new infections (European Commission, 2020a). The involvement of Google and Apple to support combating a public health emergency fueled controversy over addressing profit-driven private interests at the expense of public values. Concerns have been raised about the dominant position of US based big tech companies in political decision concerning public values. This research investigates how public values are safeguarded in cooperation with big tech companies in the Austrian contact tracing app Stop Corona. Contact tracing apps manifest a bigger trend in literature, signifying power dynamics of big tech companies, governments, and civil society in relation to public values. The theoretical foundation of this research form prevailing concepts from Media and Communication Studies (MCS) and Science and Technology Studies (STS) about power dynamics such as the expansion of digital platforms and infrastructures, the political economy of big tech companies, dependencies, and digital platforms and infrastructure governance.
The cooperative responsibility framework guides the empirical investigation in four main steps. First steps identify key public values at stake and main stakeholders. After, public deliberations on advancing public values and the translation of public values based on the outcome of public deliberation are analyzed….(More)”.