What you don’t know can’t hurt you: this seems to be the current approach for responding to disinformation by public regulators across the world. Nobody is able to say with any degree of certainty what is actually going on. This is in no small part because, at present, public regulators don’t have the slightest idea how disinformation actually works in practice. We believe that there are very good reasons for the current state of affairs, which stem from a lack of verifiable data available to public institutions. If an election board or a media regulator wants to know what types of digital content are being shared in their jurisdiction, they have no effective mechanisms for finding this data or ensuring its veracity. While there are many other reasons why governments would want access to this kind of data, the phenomenon of disinformation provides a particularly salient example of the consequences of a lack of access to this data for ensuring free and fair elections and informed democratic participation. This chapter will provide an overview of the main aspects of the problems associated with basing public regulatory decisions on unverified data, before sketching out some ideas of what a solution might look like. In order to do this, the chapter develops the concept of auditing intermediaries. After discussing which problems the concept of auditing intermediaries is designed to solve, it then discusses some of the main challenges associated with access to data, potential misuse of intermediaries, and the general lack of standards for the provision of data by large online platforms. In conclusion, the chapter suggests that there is an urgent need for an auditing mechanism to ensure the accuracy of transparency data provided by large online platform providers about the content on their services. Transparency data that have been audited would be considered verified data in this context. Without such a transparency verification mechanism, existing public debate is based merely on a whim, and digital dominance is likely to only become more pronounced.
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By way of a case study on the regulatory role of owners and managers of brothels and rented rooms for prostitution, this study focuses on the strategies deployed by a municipality to govern these intermediaries. The analysis is based on a typology of responsibilization distinguishing between who the responsible should govern (themselves or others) and forms of power (repressive or facilitative). The regulator concomitantly renders these entrepreneurs responsible for their own possible criminal conduct (self-governing) and empowers them to keep out traffickers and pimps and to control sex-workers (others-governing). Moreover, the municipality applies both repressive and facilitative power. Although the responsibilization strategy succeeds in having entrepreneurs govern themselves, it also unintentionally undermines sex-workers’ independence and favors the largest entrepreneurs. Our study enriches the R(egulator)I(ntermediary)T(arget) model by showing how varied and contentious the interactions between regulators and involuntary intermediaries are and by demonstrating the power game that the responsibilization strategy entails
This qualitative study investigates the role of coworking spaces as innovation intermediaries, focusing on a specific case study in Amsterdam. We introduce a comprehensive framework that integrates five key coworking space units and delineates three primary innovation intermediary roles: facilitation, configuring, and brokering. Our research underscores the significance of both online and offline managerial interventions that stimulate social interaction, content configuration by staff and community members, active brokering through community managers, and formal/informal events. These strategic interventions collectively enhance information flows and knowledge exchange among entrepreneurs. This study contributes valuable insights into the mechanisms through which coworking spaces facilitate innovation intermediation in support of entrepreneurial endeavours.
The bio-transition will require mass mobilization of biomass for industrial feedstock, of which lignocellulose from agricultural residues is a promising sustainable source. Agricultural lignocellulosic residues (ALR) are available in varying densities across the EU and offer an opportunity to improve environmental outcomes in agriculture as well as in refining. While technologies are emerging, the future demands of industry for ALR are not understood, limiting the ability of biomass intermediaries to develop a supply chain. This project is a collaboration of Looop, BioGrowth Development (BD), and MNEXT, with the aim to quantify and characterize ALR in the EU and match it to expected demand from the refining industry. The spatial distribution of ALR, as well as the technical requirements of refineries, are critical components to developing a sustainable supply chain. Looop aspires to create circularity between ALRs and industry, and together with the biomass consulting experience of BD have approached MNEXT to leverage their knowledge of biorefinery applications. The focus of the project is to spatially model ALR availability across the EU and identify locations where mobilizing biomass for biorefining is most feasible according to technical, environmental, and logistical considerations. The one-year collaboration enables sufficient mapping, modeling, and exploration of parameters, with a focus on creating results applicable to a wide range of future scenarios. The project makes use of academic and industry knowledge to both create industry solutions and establish a starting point for further research.
In stedelijke regio’s wordt steeds meer verwacht van actieve bewoners en sociale ondernemers. Uit eerder onderzoek blijkt echter dat deze ‘stedelijke intermediairs’ vaak moeite hebben om zich aan te passen aan eisen uit de omgeving. Het lijkt dat maar een deel van hen in staat is om op een duurzame manier te wortelen in de wijk. We vragen ons af: Hoe zijn stedelijke intermediairs in staat om hun innovatieve praktijken door te ontwikkelen, ten einde tegemoet te komen aan omgevingseisen op de korte en lange termijn? Belangrijk bij deze vraag is hoe lokale overheden en andere partijen in de stad omgaan met innovatieve praktijken van intermediairs. Kortweg: Hoe kunnen omgevingspartijen aan het adaptieve vermogen van intermediairs bijgedragen? Dit onderzoeken we in Amsterdam, Utrecht, Den Haag, Leeuwarden en Zwolle. We zetten in op een longitudinaal perspectief door middel van: 1) 30 diepte-interviews met eerder onderzochte intermediairs; 2) Expertinterviews in de betrokken gemeenten om inzicht te krijgen in de ontwikkeling van de lokale governance context; 3) Living Lab bijeenkomsten waarin deze kennisontwikkeling binnen een netwerk van stedelijke experts en stakeholders wordt gedeeld. Deze analyse levert uiteindelijk een kennisnetwerk op van intermediairs, ambtenaren en wetenschappers waarin gekeken wordt naar de verduurzaming van stedelijke intermediairs en maatschappelijke initiatieven. De pop-up bouwt voort op (af)lopend SURF-onderzoek (smart-urban-intermediaries.com, april 2017 - september 2019).
Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
