Special Issue of Daedalus edited by James Manyika: “AI is transforming our relationships with technology and with others, our senses of self, as well as our approaches to health care, banking, democracy, and the courts. But while AI in its many forms has become ubiquitous and its benefits to society and the individual have grown, its impacts are varied. Concerns about its unintended effects and misuses have become paramount in conversations about the successful integration of AI in society. This volume explores the many facets of artificial intelligence: its technology, its potential futures, its effects on labor and the economy, its relationship with inequalities, its role in law and governance, its challenges to national security, and what it says about us as humans…(More)” See also https://aiethicscourse.org/
Rethinking gamified democracy as frictional: a comparative examination of the Decide Madrid and vTaiwan platforms
Paper by Yu-Shan Tseng: “Gamification in digital design harnesses game-like elements to create rewarding and competitive systems that encourage desirable user behaviour by influencing users’ bodily actions and emotions. Recently, gamification has been integrated into platforms built to fix democratic problems such as boredom and disengagement in political participation. This paper draws on an ethnographic study of two such platforms – Decide Madrid and vTaiwan – to problematise the universal, techno-deterministic account of digital democracy. I argue that gamified democracy is frictional by nature, a concept borrowed from cultural and social geographies. Incorporating gamification into interface design does not inherently enhance the user’s enjoyment, motivation and engagement through controlling their behaviours. ‘Friction’ in the user experience includes various emotional predicaments and tactical exploitation by more advanced users. Frictional systems in the sphere of digital democracy are neither positive nor negative per se. While they may threaten systemic inclusivity or hinder users’ abilities to organise and implement policy changes, friction can also provide new impetus to advance democratic practices…(More)”.
From “democratic erosion” to “a conversation among equals”
Paper by Roberto Gargarella: “In recent years, legal and political doctrinaires have been confusing the democratic crisis that is affecting most of our countries with a mere crisis of constitutionalism (i.e., a crisis in the way our system of “checks and balances” works). Expectedly, the result of this “diagnostic error” is that legal and political doctrinaires began to propose the wrong remedies for the democratic crisis. Usually, they began advocating for the “restoration” of the old system of “internal controls” or “checks and balances”, without paying attention to the democratic aspects of the crisis that would require, instead, the strengthening of “popular” controls and participatory mechanisms that favored the gradual emergence of a “conversation among equals”. In this work, I focus my attention on certain institutional alternatives – citizens’ assemblies and the like- that may help us overcome the present democratic crisis. In particular, I examine the recent practice of citizens’ assemblies and evaluate their functioning…(More)”.
Decoding human behavior with big data? Critical, constructive input from the decision sciences
Paper by Konstantinos V. Katsikopoulos and Marc C. Canellas: “Big data analytics employs algorithms to uncover people’s preferences and values, and support their decision making. A central assumption of big data analytics is that it can explain and predict human behavior. We investigate this assumption, aiming to enhance the knowledge basis for developing algorithmic standards in big data analytics. First, we argue that big data analytics is by design atheoretical and does not provide process-based explanations of human behavior; thus, it is unfit to support deliberation that is transparent and explainable. Second, we review evidence from interdisciplinary decision science, showing that the accuracy of complex algorithms used in big data analytics for predicting human behavior is not consistently higher than that of simple rules of thumb. Rather, it is lower in situations such as predicting election outcomes, criminal profiling, and granting bail. Big data algorithms can be considered as candidate models for explaining, predicting, and supporting human decision making when they match, in transparency and accuracy, simple, process-based, domain-grounded theories of human behavior. Big data analytics can be inspired by behavioral and cognitive theory….(More)”.
Making forest data fair and open
Paper by Renato A. F. de Lima : “It is a truth universally acknowledged that those in possession of time and good fortune must be in want of information. Nowhere is this more so than for tropical forests, which include the richest and most productive ecosystems on Earth. Information on tropical forest carbon and biodiversity, and how these are changing, is immensely valuable, and many different stakeholders wish to use data on tropical and subtropical forests. These include scientists, governments, nongovernmental organizations and commercial interests, such as those extracting timber or selling carbon credits. Another crucial, often-ignored group are the local communities for whom forest information may help to assert their rights and conserve or restore their forests.
A widespread view is that to lead to better public outcomes it is necessary and sufficient for forest data to be open and ‘Findable, Accessible, Interoperable, Reusable’ (FAIR). There is indeed a powerful case. Open data — those that anyone can use and share without restrictions — can encourage transparency and reproducibility, foster innovation and be used more widely, thus translating into a greater public good (for example, https://creativecommons.org). Open biological collections and genetic sequences such as GBIF or GenBank have enabled species discovery, and open Earth observation data helps people to understand and monitor deforestation (for example, Global Forest Watch). But the perspectives of those who actually make the forest measurements are much less recognized, meaning that open and FAIR data can be extremely unfair indeed. We argue here that forest data policies and practices must be fair in the correct, linguistic use of the term — just and equitable.
In a world in which forest data origination — measuring, monitoring and sustaining forest science — is secured by large, long-term capital investment (such as through space missions and some officially supported national forest inventories), making all data open makes perfect sense. But where data origination depends on insecure funding and precarious employment conditions, top-down calls to make these data open can be deeply problematic. Even when well-intentioned, such calls ignore the socioeconomic context of the places where the forest plots are located and how knowledge is created, entrenching the structural inequalities that characterize scientific research and collaboration among and within nations. A recent review found scant evidence for open data ever lessening such inequalities. Clearly, only a privileged part of the global community is currently able to exploit the potential of open forest data. Meanwhile, some local communities are de facto owners of their forests and associated knowledge, so making information open — for example, the location of valuable species — may carry risks to themselves and their forests….(More)”.
Co-designing algorithms for governance: Ensuring responsible and accountable algorithmic management of refugee camp supplies
Paper by Rianne Dekker et al: “There is increasing criticism on the use of big data and algorithms in public governance. Studies revealed that algorithms may reinforce existing biases and defy scrutiny by public officials using them and citizens subject to algorithmic decisions and services. In response, scholars have called for more algorithmic transparency and regulation. These are useful, but ex post solutions in which the development of algorithms remains a rather autonomous process. This paper argues that co-design of algorithms with relevant stakeholders from government and society is another means to achieve responsible and accountable algorithms that is largely overlooked in the literature. We present a case study of the development of an algorithmic tool to estimate the populations of refugee camps to manage the delivery of emergency supplies. This case study demonstrates how in different stages of development of the tool—data selection and pre-processing, training of the algorithm and post-processing and adoption—inclusion of knowledge from the field led to changes to the algorithm. Co-design supported responsibility of the algorithm in the selection of big data sources and in preventing reinforcement of biases. It contributed to accountability of the algorithm by making the estimations transparent and explicable to its users. They were able to use the tool for fitting purposes and used their discretion in the interpretation of the results. It is yet unclear whether this eventually led to better servicing of refugee camps…(More)”.
Intermediaries do matter: voluntary standards and the Right to Data Portability
Paper by Matteo Nebbiai: “This paper enlightens an understudied aspect of the application of the General Data Protection Regulation (GDPR) Right to Data Portability (RtDP), introducing a framework to analyse empirically the voluntary data portability standards adopted by various data controllers. The first section explains how the RtDP wording creates some “grey areas” that allow data controllers a broad interpretation of the right. Secondly, the paper shows why the regulatory initiatives affecting the interpretation of these “grey areas” can be framed as “regulatory standard-setting (RSS) schemes”, which are voluntary standards of behaviour settled either by private, public, or non-governmental actors. The empirical section reveals that in the EU, between 2000 and 2020, the number of such schemes increased every year and most of them were governed by private actors. Finally, the historical analysis highlights that the RtDP was introduced when many private-run RSS schemes were already operating, and no evidence suggests that the GDPR impacted significantly on their spread…(More)”.
Data-driven orientation and open innovation: the role of resilience in the (co-)development of social changes
Introduction to Special Issue by Orlando Troisi and Mara Grimaldi: “…Contemporary organizations that aim at exploiting the opportunities offered from Big data should reframe their processes through new technologies and analytics not only to gain competitive advantage but also to implement flexible governance and foster diffused decision-making (Visvizi et al., 2018; Polese et al., 2021).
In the last developments introduced in management research, new collaborative and open models are understood strategically according to a network view that considers the relationships with a broad set of stakeholders (from for-profit companies to users, non-profit and public institutions) as critical factors enabling well-being and innovation (Visvizi and Lytras, 2019a).
For this reason, open innovation (OI) (Chesbrough, 2003) is conceptualized to describe the way in which emergent models of innovation can enable the development of innovative insights thanks to the knowledge exchanged through a complex set of relationships enhanced by smart technologies.
Smart organizations based on OI models can be reread as smart communities, as technology-mediated networks that through the collaboration between people (Abbate et al., 2019) and the sharing of a set of norms, rules and values (Barile et al., 2017; Vargo et al., 2020) can improve well-being in different areas, from economy to environment and social inclusion (Appio et al., 2019; Kashef et al., 2021). The ability of communities to challenge environmental complexity through their constant evolution can help rereading the concept of resilience as the complex result of system’s adaptation, maintenance, change and disruption (Vargo et al., 2015). The investigation of the main resilient features (restructuring, adaptation, transformation) of smart communities can contribute to detect the transition from the emergence of innovation to the development of social changes.
Therefore, the goal of the current Special Issue is to advance new theoretical and empirical contributions that analysze how contemporary resilient data-driven organizations and communities can integrate technologies with human component (Bang et al., 2021) to reframe innovation emergence and foster the attainment of societal transformation. In this way, by using a collaborative approach, research can explore how organizations can develop innovation solutions to address relevant social issues thanks to the constant reshaping of culture and knowledge and to co-learning processes that can address the evolving community needs.
The exploration of the different ways to reframe organizational processes and policies thanks to human’s interactions mediated through technology can help the identification of how social, economic and health challenges (in COVID era but also in case of future crises) can be met through continuous transformation…(More)”
Can the use of minipublics backfire? Examining how policy adoption shapes the effect of minipublics on political support among the general public
Paper by Lisa van Dijk and Jonas Lefevere: “Academics and practitioners are increasingly interested in deliberative minipublics and whether these can address widespread dissatisfaction with contemporary politics. While optimism seems to prevail, there is also talk that the use of minipublics may backfire. When the government disregards a minipublic’s recommendations, this could lead to more dissatisfaction than not asking for its advice in the first place. Using an online survey experiment in Belgium (n = 3,102), we find that, compared to a representative decision-making process, a minipublic tends to bring about higher political support when its recommendations are fully adopted by the government, whereas it generates lower political support when its recommendations are not adopted. This study presents novel insights into whether and when the use of minipublics may alleviate or aggravate political dissatisfaction among the public at large….(More)”
City museums in the age of datafication: could museums be meaningful sites of data practice in smart cities?
Paper by Natalia Grincheva: “The article documents connections and synergies between city museums’ visions and programming as well as emerging smart city issues and dilemmas in a fast-paced urban environment marked with the processes of increasing digitalization and datafication. The research employs policy/document analysis and semi-structured interviews with smart city government representatives and museum professionals to investigating both smart city policy frameworks as well as city museum’s data-driven installations and activities in New York, London and Singapore. A comparative program analysis of the Singapore City Gallery, Museum of the City of New York and Museum of London identifies such sites of data practices as Data storytelling, interpretation and eco-curation. Discussing these sites as dedicated spaces of smart citizen engagement, the article reveals that city museums can either empower their visitors to consider their roles as active city co-makers or see them as passive recipients of the smart city transformations….(More)”.