Open Data Commons Licences (ODCL): Licensing personal and non personal data supporting the commons and privacy

Curated on Posted on by Stefaan Verhulst

Paper by Yaniv Benhamou and Melanie Dulong de Rosnay: “Data are often subject to a multitude of rights (e.g. original works or personal data posted on social media, or collected through captcha, subject to copyright, database and data protection) and voluntary shared through non standardized, non interoperable contractual terms. This leads to fragmented legal regimes and has become an even major challenge in the AI-era, for example when online platforms set their own Terms of Services (ToS), in business-to-consumer relationship (B2C).

This article proposes standard terms that may apply to all kind of data (including personal and mixed datasets subject to different legal regimes) based on the open data philosophy initially developed for Free and Open Source software and Creative Commons licenses for artistic and other copyrighted works. In a first part, we analyse how to extend open standard terms to all kinds of data (II). In a second part, we suggest to combine these open standard terms with collective governance instruments, in particular data trust, inspired by commons-based projects and by the centennial collective management of copyright (III). In a last part, after few concluding remarks (IV), we propose a template “Open Data Commons Licenses“ (ODCL) combining compulsory and optional elements to be selected by licensors, illustrated by pictograms and icons inspired by the bricks of Creative Commons licences and legal design techniques (V).

This proposal addresses the bargaining power imbalance and information asymmetry (by offering the licensor the ability to decide the terms), and conceptualises contract law differently. It reverses the current logic of contract: instead of letting companies (licensees) impose their own ToS to the users (licensors, being the copyright owner, data subject, data producer), licensors will reclaim the ability to set their own terms for access and use of data, by selecting standard terms. This should also allow the management of complex datasets, increase data sharing, and improve trust and control over the data. Like previous open licencing standards, the model is expected to lower the transaction costs by reducing the need to develop and read new complicated contractual terms. It can also spread the virality of open data to all data in an AI-era, if any input data under such terms used for AI training purposes propagates its conditions to all aggregated and output data. In other words, any data distributed under our ODCL template will turn all outcome into more or less open data and foster a data common ecosystem. Finally, instead of full openness, our model allows for restrictions outside of certain boundaries (e.g. authorized users and uses), in order to protect the commons and certain values. The model would require to be governed and monitored by a collective data trust…(More)”.

Populist Leaders and the Economy

Curated on Posted on by Stefaan Verhulst

Paper by Manuel Funke, Moritz Schularick and Christoph Trebesch: “Populism at the country level is at an all-time high, with more than 25 percent of nations currently governed by populists. How do economies perform under populist leaders? We build a new long-run cross-country database to study the macroeconomic history of populism. We identify 51 populist presidents and prime ministers from 1900 to 2020 and show that the economic cost of populism is high. After 15 years, GDP per capita is 10 percent lower compared to a plausible nonpopulist counterfactual. Economic disintegration, decreasing macroeconomic stability, and the erosion of institutions typically go hand in hand with populist rule…(More)”.

Steering Responsible AI: A Case for Algorithmic Pluralism

Curated on Posted on by Stefaan Verhulst

Paper by Stefaan G. Verhulst: “In this paper, I examine questions surrounding AI neutrality through the prism of existing literature and scholarship about mediation and media pluralism. Such traditions, I argue, provide a valuable theoretical framework for how we should approach the (likely) impending era of AI mediation. In particular, I suggest examining further the notion of algorithmic pluralism. Contrasting this notion to the dominant idea of algorithmic transparency, I seek to describe what algorithmic pluralism may be, and present both its opportunities and challenges. Implemented thoughtfully and responsibly, I argue, Algorithmic or AI pluralism has the potential to sustain the diversity, multiplicity, and inclusiveness that are so vital to democracy…(More)”.

Open data ecosystems: what models to co-create service innovations in smart cities?

Curated on Posted on by Stefaan Verhulst

Paper by Arthur Sarazin: “While smart cities are recently providing open data, how to organise the collective creation of data, knowledge and related products and services produced from this collective resource, still remains to be thought. This paper aims at gathering the literature review on open data ecosystems to tackle the following research question: what models can be imagined to stimulate the collective co-creation of services between smart cities’ stakeholders acting as providers and users of open data? Such issue is currently at stake in many municipalities such as Lisbon which decided to position itself as a platform (O’Reilly, 2010) in the local digital ecosystem. With the implementation of its City Operation Center (COI), Lisbon’s municipality provides an Information Infrastructure (Bowker et al., 2009) to many different types of actors such as telecom companies, municipalities, energy utilities or transport companies. Through this infrastructure, Lisbon encourages such actors to gather, integrate and release heterogeneous datasets and tries to orchestrate synergies among them so data-driven solution to urban problems can emerge (Carvalho and Vale, 2018). The remaining question being: what models for the municipalities such as Lisbon to lean on so as to drive this cutting-edge type of service innovation?…(More)”.

Governing the economics of the common good

Curated on Posted on by Stefaan Verhulst

Paper by Mariana Mazzucato: “To meet today’s grand challenges, economics requires an understanding of how common objectives may be collaboratively set and met. Tied to the assumption that the state can, at best, fix market failures and is always at risk of ‘capture’, economic theory has been unable to offer such a framework. To move beyond such limiting assumptions, the paper provides a renewed conception of the common good, going beyond the classic public good and commons approach, as a way of steering and shaping (rather than just fixing) the economy towards collective goals…(More)”.

AI and Democracy’s Digital Identity Crisis

Curated on Posted on by Stefaan Verhulst

Paper by Shrey Jain, Connor Spelliscy, Samuel Vance-Law and Scott Moore: “AI-enabled tools have become sophisticated enough to allow a small number of individuals to run disinformation campaigns of an unprecedented scale. Privacy-preserving identity attestations can drastically reduce instances of impersonation and make disinformation easy to identify and potentially hinder. By understanding how identity attestations are positioned across the spectrum of decentralization, we can gain a better understanding of the costs and benefits of various attestations. In this paper, we discuss attestation types, including governmental, biometric, federated, and web of trust-based, and include examples such as e-Estonia, China’s social credit system, Worldcoin, OAuth, X (formerly Twitter), Gitcoin Passport, and EAS. We believe that the most resilient systems create an identity that evolves and is connected to a network of similarly evolving identities that verify one another. In this type of system, each entity contributes its respective credibility to the attestation process, creating a larger, more comprehensive set of attestations. We believe these systems could be the best approach to authenticating identity and protecting against some of the threats to democracy that AI can pose in the hands of malicious actors. However, governments will likely attempt to mitigate these risks by implementing centralized identity authentication systems; these centralized systems could themselves pose risks to the democratic processes they are built to defend. We therefore recommend that policymakers support the development of standards-setting organizations for identity, provide legal clarity for builders of decentralized tooling, and fund research critical to effective identity authentication systems…(More)”.

Remote collaboration fuses fewer breakthrough ideas

Curated on Posted on by Stefaan Verhulst

Paper by Yiling Lin, Carl Benedikt Frey & Lingfei Wu: “Theories of innovation emphasize the role of social networks and teams as facilitators of breakthrough discoveries. Around the world, scientists and inventors are more plentiful and interconnected today than ever before. However, although there are more people making discoveries, and more ideas that can be reconfigured in new ways, research suggests that new ideas are getting harder to find—contradicting recombinant growth theory. Here we shed light on this apparent puzzle. Analysing 20 million research articles and 4 million patent applications from across the globe over the past half-century, we begin by documenting the rise of remote collaboration across cities, underlining the growing interconnectedness of scientists and inventors globally. We further show that across all fields, periods and team sizes, researchers in these remote teams are consistently less likely to make breakthrough discoveries relative to their on-site counterparts. Creating a dataset that allows us to explore the division of labour in knowledge production within teams and across space, we find that among distributed team members, collaboration centres on late-stage, technical tasks involving more codified knowledge. Yet they are less likely to join forces in conceptual tasks—such as conceiving new ideas and designing research—when knowledge is tacit. We conclude that despite striking improvements in digital technology in recent years, remote teams are less likely to integrate the knowledge of their members to produce new, disruptive ideas…(More)”.

Transmission Versus Truth, Imitation Versus Innovation: What Children Can Do That Large Language and Language-and-Vision Models Cannot (Yet)

Curated on Posted on by Stefaan Verhulst

Paper by Eunice Yiu, Eliza Kosoy, and Alison Gopnik: “Much discussion about large language models and language-and-vision models has focused on whether these models are intelligent agents. We present an alternative perspective. First, we argue that these artificial intelligence (AI) models are cultural technologies that enhance cultural transmission and are efficient and powerful imitation engines. Second, we explore what AI models can tell us about imitation and innovation by testing whether they can be used to discover new tools and novel causal structures and contrasting their responses with those of human children. Our work serves as a first step in determining which particular representations and competences, as well as which kinds of knowledge or skills, can be derived from particular learning techniques and data. In particular, we explore which kinds of cognitive capacities can be enabled by statistical analysis of large-scale linguistic data. Critically, our findings suggest that machines may need more than large-scale language and image data to allow the kinds of innovation that a small child can produce…(More)”.

Public Value of Data: B2G data-sharing Within the Data Ecosystem of Helsinki

Curated on Posted on by Stefaan Verhulst

Paper by Vera Djakonoff: “Datafication penetrates all levels of society. In order to harness public value from an expanding pool of private-produced data, there has been growing interest in facilitating business-to-government (B2G) data-sharing. This research examines the development of B2G data-sharing within the data ecosystem of the City of Helsinki. The research has identified expectations ecosystem actors have for B2G data-sharing and factors that influence the city’s ability to unlock public value from private-produced data.

The research context is smart cities, with a specific focus on the City of Helsinki. Smart cities are in an advantageous position to develop novel public-private collaborations. Helsinki, on the international stage, stands out as a pioneer in the realm of data-driven smart city development. For this research, nine data ecosystem actors representing the city and companies participated in semi-structured thematic interviews through which their perceptions and experiences were mapped.

The theoretical framework of this research draws from the public value management (PVM) approach in examining the smart city data ecosystem and alignment of diverse interests for a shared purpose. Additionally, the research transcends the examination of the interests in isolation and looks at how technological artefacts shape the social context and interests surrounding them. Here, the focus is on the properties of data as an artefact with anti-rival value-generation potential.

The findings of this research reveal that while ecosystem actors recognise that more value can be drawn from data through collaboration, this is not apparent at the level of individual initiatives and transactions. This research shows that the city’s commitment to and facilitation of a long-term shared sense of direction and purpose among ecosystem actors is central to developing B2G data-sharing for public value outcomes. Here, participatory experimentation is key, promoting an understanding of the value of data and rendering visible the diverse motivations and concerns of ecosystem actors, enabling learning for wise, data-driven development…(More)”.

The Oligopoly’s Shift to Open Access. How the Big Five Academic Publishers Profit from Article Processing Charges 

Curated on Posted on by Stefaan Verhulst

Paper by Leigh-Ann Butler et al: “This study aims to estimate the total amount of article processing charges (APCs) paid to publish open access (OA) in journals controlled by the five large commercial publishers Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley between 2015 and 2018. Using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets and historical fees retrieved via the Internet Archive Wayback Machine, we estimate that globally authors paid $1.06 billion in publication fees to these publishers from 2015–2018. Revenue from gold OA amounted to $612.5 million, while $448.3 million was obtained for publishing OA in hybrid journals. Among the five publishers, Springer-Nature made the most revenue from OA ($589.7 million), followed by Elsevier ($221.4 million), Wiley ($114.3 million), Taylor & Francis ($76.8 million) and Sage ($31.6 million). With Elsevier and Wiley making most of APC revenue from hybrid fees and others focusing on gold, different OA strategies could be observed between publishers…(More)”.This study aims to estimate the total amount of article processing charges (APCs) paid to publish open access (OA) in journals controlled by the five large commercial publishers Elsevier, Sage, Springer-Nature, Taylor & Francis and Wiley between 2015 and 2018. Using publication data from WoS, OA status from Unpaywall and annual APC prices from open datasets and historical fees retrieved via the Internet Archive Wayback Machine, we estimate that globally authors paid $1.06 billion in publication fees to these publishers from 2015–2018. Revenue from gold OA amounted to $612.5 million, while $448.3 million was obtained for publishing OA in hybrid journals. Among the five publishers, Springer-Nature made the most revenue from OA ($589.7 million), followed by Elsevier ($221.4 million), Wiley ($114.3 million), Taylor & Francis ($76.8 million) and Sage ($31.6 million). With Elsevier and Wiley making most of APC revenue from hybrid fees and others focusing on gold, different OA strategies could be observed between publishers.