A Behavioral Economics Approach to Digitalisation

Curated on Posted on by Stefaan Verhulst

Paper by Dirk Beerbaum and Julia M. Puaschunder: “A growing body of academic research in the field of behavioural economics, political science and psychology demonstrate how an invisible hand can nudge people’s decisions towards a preferred option. Contrary to the assumptions of the neoclassical economics, supporters of nudging argue that people have problems coping with a complex world, because of their limited knowledge and their restricted rationality. Technological improvement in the age of information has increased the possibilities to control the innocent social media users or penalise private investors and reap the benefits of their existence in hidden persuasion and discrimination. Nudging enables nudgers to plunder the simple uneducated and uninformed citizen and investor, who is neither aware of the nudging strategies nor able to oversee the tactics used by the nudgers (Puaschunder 2017a, b; 2018a, b).

The nudgers are thereby legally protected by democratically assigned positions they hold. The law of motion of the nudging societies holds an unequal concentration of power of those who have access to compiled data and coding rules, relevant for political power and influencing the investor’s decision usefulness (Puaschunder 2017a, b; 2018a, b). This paper takes as a case the “transparency technology XBRL (eXtensible Business Reporting Language)” (Sunstein 2013, 20), which should make data more accessible as well as usable for private investors. It is part of the choice architecture on regulation by governments (Sunstein 2013). However, XBRL is bounded to a taxonomy (Piechocki and Felden 2007).

Considering theoretical literature and field research, a representation issue (Beerbaum, Piechocki and Weber 2017) for principles-based accounting taxonomies exists, which intelligent machines applying Artificial Intelligence (AI) (Mwilu, Prat and Comyn-Wattiau 2015) nudge to facilitate decision usefulness. This paper conceptualizes ethical questions arising from the taxonomy engineering based on machine learning systems: Should the objective of the coding rule be to support or to influence human decision making or rational artificiality? This paper therefore advocates for a democratisation of information, education and transparency about nudges and coding rules (Puaschunder 2017a, b; 2018a, b)…(More)”.

Big data analytics to identify illegal construction waste dumping: A Hong Kong study

Curated on Posted on by Stefaan Verhulst

WeishengLu at Resources, Conservation and Recycling: “Illegal dumping, referring to the intentional and criminal abandonment of waste in unauthorized areas, has long plagued governments and environmental agencies worldwide. Despite the tremendous resources spent to combat it, the surreptitious nature of illegal dumping indicates the extreme difficulty in its identification. In 2006, the Construction Waste Disposal Charging Scheme (CWDCS) was implemented, regulating that all construction waste must be disposed of at government waste facilities if not otherwise properly reused or recycled.

While the CWDCS has significantly improved construction waste management in Hong Kong, it has also triggered illegal dumping problems. Inspired by the success of big data in combating urban crime, this paper aims to identify illegal dumping cases by mining a publicly available data set containing more than 9 million waste disposal records from 2011 to 2017. Using behavioral indicators and up-to-date big data analytics, possible drivers for illegal dumping (e.g., long queuing times) were identified. The analytical results also produced a list of 546 waste hauling trucks suspected of involvement in illegal dumping. This paper contributes to the understanding of illegal dumping behavior and joins the global research community in exploring the value of big data, particularly for combating urban crime. It also presents a three-step big data-enabled urban crime identification methodology comprising ‘Behavior characterization’, ‘Big data analytical model development’, and ‘Model training, calibration, and evaluation’….(More)”.

The Nail Finds a Hammer: Self-Sovereign Identity, Design Principles, and Property Rights in the Developing World

Curated on Posted on by Stefaan Verhulst

Report by Michael Graglia, Christopher Mellon and Tim Robustelli: “Our interest in identity systems was an inevitable outgrowth of our earlier work on blockchain-based1 land registries.2 Property registries, which at the simplest level are ledgers of who has which rights to which asset, require a very secure and reliable means of identifying both people and properties. In the course of investigating solutions to that problem, we began to appreciate the broader challenges of digital identity and its role in international development. And the more we learned about digital identity, the more convinced we became of the need for self-sovereign identity, or SSI. This model, and the underlying principles of identity which it incorporates, will be described in detail in this paper.

We believe that the great potential of SSI is that it can make identity in the digital world function more like identity in the physical world, in which every person has a unique and persistent identity which is represented to others by means of both their physical attributes and a collection of credentials attested to by various external sources of authority. These credentials are stored and controlled by the identity holder—typically in a wallet—and presented to different people for different reasons at the identity holder’s discretion. Crucially, the identity holder controls what information to present based on the environment, trust level, and type of interaction. Moreover, their fundamental identity persists even though the credentials by which it is represented may change over time.

The digital incarnation of this model has many benefits, including both greatly improved privacy and security, and the ability to create more trustworthy online spaces. Social media and news sites, for example, might limit participation to users with verified identities, excluding bots and impersonators.

The need for identification in the physical world varies based on location and social context. We expect to walk in relative anonymity down a busy city street, but will show a driver’s license to enter a bar, and both a driver’s license and a birth certificate to apply for a passport. There are different levels of ID and supporting documents required for each activity. But in each case, access to personal information is controlled by the user who may choose whether or not to share it.

Self-sovereign identity gives users complete control of their own identities and related personal data, which sits encrypted in distributed storage instead of being stored by a third party in a central database. In older, “federated identity” models, a single account—a Google account, for example—might be used to log in to a number of third-party sites, like news sites or social media platforms. But in this model a third party brokers all of these ID transactions, meaning that in exchange for the convenience of having to remember fewer passwords, the user must sacrifice a degree of privacy.

A real world equivalent would be having to ask the state to share a copy of your driver’s license with the bar every time you wanted to prove that you were over the age of 21. SSI, in contrast, gives the user a portable, digital credential (like a driver’s license or some other document that proves your age), the authenticity of which can be securely validated via cryptography without the recipient having to check with the authority that issued it. This means that while the credential can be used to access many different sites and services, there is no third-party broker to track the services to which the user is authenticating. Furthermore, cryptographic techniques called “zero-knowledge proofs” (ZKPs) can be used to prove possession of a credential without revealing the credential itself. This makes it possible, for example, for users to prove that they are over the age of 21 without having to share their actual birth dates, which are both sensitive information and irrelevant to a binary, yes-or-no ID transaction….(More)”.

Governing Open Data Platforms to Cultivate Innovation Ecosystems: The Case of the Government of Buenos Aires

Curated on Posted on by Stefaan Verhulst

Paper by Carla Bonina, Ben Eaton and Stefan Henningsson: “Open Government Data (OGD) is increasingly an object of research. Whilst referred to as a platform problem, few studies examine the phenomenon using platform concepts. One challenge governments face is to establish thriving OGD ecosystems through appropriate platform governance. The governance of innovating complements on the demand side of platforms, such as services using OGD datasets by entrepreneurs for citizen users, is well studied in platform literature. However, understanding of the supply side and how third parties can be governed to help innovate platform core architecture, such a ministries sourcing quality datasets for OGD platforms, is lacking. In our preliminary study of emergent OGD platforms in Latin America, we construct a model extending concepts of boundary resources from the demand side to the supply side to expand our understanding of platform governance. In addition to contributing to platform governance theories, we improve our understanding of OGD platform ecosystem cultivation….(More)”.

Beyond Open vs. Closed: Balancing Individual Privacy and Public Accountability in Data Sharing

Curated on Posted on by Stefaan Verhulst

Paper by Bill Howe et al: “Data too sensitive to be “open” for analysis and re-purposing typically remains “closed” as proprietary information. This dichotomy undermines efforts to make algorithmic systems more fair, transparent, and accountable. Access to proprietary data in particular is needed by government agencies to enforce policy, researchers to evaluate methods, and the public to hold agencies accountable; all of these needs must be met while preserving individual privacy and firm competitiveness. In this paper, we describe an integrated legaltechnical approach provided by a third-party public-private data trust designed to balance these competing interests.

Basic membership allows firms and agencies to enable low-risk access to data for compliance reporting and core methods research, while modular data sharing agreements support a wide array of projects and use cases. Unless specifically stated otherwise in an agreement, all data access is initially provided to end users through customized synthetic datasets that offer a) strong privacy guarantees, b) removal of signals that could expose competitive advantage for the data providers, and c) removal of biases that could reinforce discriminatory policies, all while maintaining empirically good fidelity to the original data. We find that the liberal use of synthetic data, in conjunction with strong legal protections over raw data, strikes a tunable balance between transparency, proprietorship, privacy, and research objectives; and that the legal-technical framework we describe can form the basis for organizational data trusts in a variety of contexts….(More)”.

An open-science crowdsourcing approach for producing community noise maps using smartphones

Curated on Posted on by Stefaan Verhulst

Judicaël Picaut at al at Building and Environment: “An alternative method is proposed for the assessment of the noise environment, on the basis of a crowdsourcing approach. For this purpose, a smartphone application and a spatial data infrastructure have been specifically developed in order to collect physical data (noise indicators, GPS positions, etc.) and perceptual data (pleasantness), without territorial limits, of the sound environment.

As the project is developed within an Open Science framework, all source codes, methodologies, tools and raw data are freely available, and if necessary, can be duplicated for any specific use. In particular, the collected data can be used by the scientific community, cities, associations, or any institution, which would like to develop new tools for the evaluation and representation of sound environments. In this paper, all the methodological and technical issues are detailed, and a first analysis of the collected data is proposed….(More)”.

The Inevitability of AI Law & Policy: Preparing Government for the Era of Autonomous Machines

Curated on Posted on by Stefaan Verhulst

Public Knowledge: “Today, we’re happy to announce our newest white paper, “The Inevitability of AI Law & Policy: Preparing Government for the Era of Autonomous Machines,” by Public Knowledge General Counsel Ryan Clough. The paper argues that the rapid and pervasive rise of artificial intelligence risks exploiting the most marginalized and vulnerable in our society. To mitigate these harms, Clough advocates for a new federal authority to help the U.S. government implement fair and equitable AI. Such an authority should provide the rest of the government with the expertise and experience needed to achieve five goals crucial to building ethical AI systems:

  • Boosting sector-specific regulators and confronting overarching policy challenges raised by AI;
  • Protecting public values in government procurement and implementation of AI;
  • Attracting AI practitioners to civil service, and building durable and centralized AI expertise within government;
  • Identifying major gaps in the laws and regulatory frameworks that govern AI; and
  • Coordinating strategies and priorities for international AI governance.

“Any individual can be misjudged and mistreated by artificial intelligence,” Clough explains, “but the record to date indicates that it is significantly more likely to happen to the less powerful, who also have less recourse to do anything about it.” The paper argues that a new federal authority is the best way to meet the profound and novel challenges AI poses for us all….(More)”.

Positive deviance, big data, and development: A systematic literature review

Curated on Posted on by Stefaan Verhulst

Paper by Basma Albanna and Richard Heeks: “Positive deviance is a growing approach in international development that identifies those within a population who are outperforming their peers in some way, eg, children in low‐income families who are well nourished when those around them are not. Analysing and then disseminating the behaviours and other factors underpinning positive deviance are demonstrably effective in delivering development results.

However, positive deviance faces a number of challenges that are restricting its diffusion. In this paper, using a systematic literature review, we analyse the current state of positive deviance and the potential for big data to address the challenges facing positive deviance. From this, we evaluate the promise of “big data‐based positive deviance”: This would analyse typical sources of big data in developing countries—mobile phone records, social media, remote sensing data, etc—to identify both positive deviants and the factors underpinning their superior performance.

While big data cannot solve all the challenges facing positive deviance as a development tool, they could reduce time, cost, and effort; identify positive deviants in new or better ways; and enable positive deviance to break out of its current preoccupation with public health into domains such as agriculture, education, and urban planning. In turn, positive deviance could provide a new and systematic basis for extracting real‐world development impacts from big data…(More)”.

Algorithmic Government: Automating Public Services and Supporting Civil Servants in using Data Science Technologies

Curated on Posted on by Stefaan Verhulst

Zeynep Engin and Philip Treleaven in the Computer Journal:  “The data science technologies of artificial intelligence (AI), Internet of Things (IoT), big data and behavioral/predictive analytics, and blockchain are poised to revolutionize government and create a new generation of GovTech start-ups. The impact from the ‘smartification’ of public services and the national infrastructure will be much more significant in comparison to any other sector given government’s function and importance to every institution and individual.

Potential GovTech systems include Chatbots and intelligent assistants for public engagement, Robo-advisors to support civil servants, real-time management of the national infrastructure using IoT and blockchain, automated compliance/regulation, public records securely stored in blockchain distributed ledgers, online judicial and dispute resolution systems, and laws/statutes encoded as blockchain smart contracts. Government is potentially the major ‘client’ and also ‘public champion’ for these new data technologies. This review paper uses our simple taxonomy of government services to provide an overview of data science automation being deployed by governments world-wide. The goal of this review paper is to encourage the Computer Science community to engage with government to develop these new systems to transform public services and support the work of civil servants….(More)”.

The Role of Management in Open Data Initiatives in Local Governments: Opening the Organizational Black Box

Curated on Posted on by Stefaan Verhulst

Paper by Mila Gasco-Hernandez and  Jose Ramon Gil-Garcia: “Previous studies have infrequently addressed the dynamic interactions among social, technical, and organizational variables in open government data initiatives. In addition, organization level models have neglected to explain the role of management in decision-making processes about technology and data. This article contributes to addressing this gap in the literature by analyzing the complex relationships between open government data characteristics and the organizations and institutions in which they are embedded.

We systematically compare the open data inception and implementation processes, as well as their main results, in three Spanish local governments (Gava and Rubi in Catalonia and Gijon in Asturias) by using a model that combines the technology enactment framework with some specific constructs and relationships from the process model of computing change. Our resulting model is able to identify and explain the significant role of management in shaping and mediating different interactions, but also acknowledges the importance of organizational level variables and the context in which the open data initiative is taking place…(More)”.