Nudging Citizens through Technology in Smart Cities

Curated on Posted on by Stefaan Verhulst

Sofia Ranchordas in the International Review of Law, Computers & Technology: “In the last decade, several smart cities throughout the world have started employing Internet of Things, big data, and algorithms to nudge citizens to save more water and energy, live healthily, use public transportation, and participate more actively in local affairs. Thus far, the potential and implications of data-driven nudges and behavioral insights in smart cities have remained an overlooked subject in the legal literature. Nevertheless, combining technology with behavioral insights may allow smart cities to nudge citizens more systematically and help these urban centers achieve their sustainability goals and promote civic engagement. For example, in Boston, real-time feedback on driving has increased road safety and in Eindhoven, light sensors have been used to successfully reduce nightlife crime and disturbance. While nudging tends to be well-intended, data-driven nudges raise a number of legal and ethical issues. This article offers a novel and interdisciplinary perspective on nudging which delves into the legal, ethical, and trust implications of collecting and processing large amounts of personal and impersonal data to influence citizens’ behavior in smart cities….(More)”.

Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice

Curated on Posted on by Stefaan Verhulst

Paper by Rashida Richardson, Jason Schultz, and Kate Crawford: “Law enforcement agencies are increasingly using algorithmic predictive policing systems to forecast criminal activity and allocate police resources. Yet in numerous jurisdictions, these systems are built on data produced within the context of flawed, racially fraught and sometimes unlawful practices (‘dirty policing’). This can include systemic data manipulation, falsifying police reports, unlawful use of force, planted evidence, and unconstitutional searches. These policing practices shape the environment and the methodology by which data is created, which leads to inaccuracies, skews, and forms of systemic bias embedded in the data (‘dirty data’). Predictive policing systems informed by such data cannot escape the legacy of unlawful or biased policing practices that they are built on. Nor do claims by predictive policing vendors that these systems provide greater objectivity, transparency, or accountability hold up. While some systems offer the ability to see the algorithms used and even occasionally access to the data itself, there is no evidence to suggest that vendors independently or adequately assess the impact that unlawful and bias policing practices have on their systems, or otherwise assess how broader societal biases may affect their systems.

In our research, we examine the implications of using dirty data with predictive policing, and look at jurisdictions that (1) have utilized predictive policing systems and (2) have done so while under government commission investigations or federal court monitored settlements, consent decrees, or memoranda of agreement stemming from corrupt, racially biased, or otherwise illegal policing practices. In particular, we examine the link between unlawful and biased police practices and the data used to train or implement these systems across thirteen case studies. We highlight three of these: (1) Chicago, an example of where dirty data was ingested directly into the city’s predictive system; (2) New Orleans, an example where the extensive evidence of dirty policing practices suggests an extremely high risk that dirty data was or will be used in any predictive policing application, and (3) Maricopa County where despite extensive evidence of dirty policing practices, lack of transparency and public accountability surrounding predictive policing inhibits the public from assessing the risks of dirty data within such systems. The implications of these findings have widespread ramifications for predictive policing writ large. Deploying predictive policing systems in jurisdictions with extensive histories of unlawful police practices presents elevated risks that dirty data will lead to flawed, biased, and unlawful predictions which in turn risk perpetuating additional harm via feedback loops throughout the criminal justice system. Thus, for any jurisdiction where police have been found to engage in such practices, the use of predictive policing in any context must be treated with skepticism and mechanisms for the public to examine and reject such systems are imperative….(More)”.

From Human Rights Aspirations to Enforceable Obligations by Non-State Actors in the Digital Age: The Example of Internet Governance and ICANN

Curated on Posted on by Stefaan Verhulst

Paper by Monika Zalnieriute: “As the global policy-making capacity and influence of non-state actors in the digital age is rapidly increasing, the protection of fundamental human rights by private actors becomes one of the most pressing issues in Global Governance. This article combines business and human rights and digital constitutionalism discourses and uses the changing institutional context of Internet Governance and Internet Corporation for Assigned Names and Numbers (‘ICANN’) as an example to argue that economic incentives act against the voluntary protection of human rights by informal actors and regulatory structures in the digital era. It further contends that the global policy-making role and increasing regulatory power of informal actors such as ICANN necessitates reframing of their legal duties by subjecting them to directly binding human rights obligations in international law.

The article argues that such reframing is particularly important in the information age for three reasons. Firstly, it is needed to rectify an imbalance between hard legal commercial obligations and human rights soft law. This imbalance is well reflected in ICANNs policies. Secondly, binding obligations would ensure that individuals whose human rights have been affected can access an effective remedy. This is not envisaged under the new ICANN Bylaw on human rights precisely because of the fuzziness around the nature of ICANN’s obligations to respect internationally recognized human rights in its policies. Finally, the article suggests that because private actors such as ICANN are themselves engaging in the balancing exercise around such rights, an explicit recognition of their human rights obligations is crucial for the future development of access to justice in the digital age….(More)”.

The Future of FOIA in an Open Government World: Implications of the Open Government Agenda for Freedom of Information Policy and Implementation

Curated on Posted on by Stefaan Verhulst

Paper by Daniel Berliner, Alex Ingrams and Suzanne J. Piotrowski: “July 4, 2016 marked the fiftieth anniversary of the 1966 Freedom of Information Act of the United States. Freedom of Information (FOI) has become a vital element of the American political process, become recognized as a core value of democracy, and helped to inspire similar laws and movements around the world. FOI has always faced myriad challenges, including resistance, evasion, and poor implementation and enforcement. Yet the last decade has brought a change of a very different form to the evolution of FOI policy—the emergence of another approach to transparency that is in some ways similar to FOI, and in other ways distinct: open government. The open government agenda, driven by technological developments and motivated by a broader conception of transparency, today rivals, or by some measures, even eclipses FOI in terms of political attention and momentum. What have been the consequences of these trends? How does the advent of new technologies and new agendas shape the transparency landscape?

The political and policy contexts for FOI have fundamentally shifted due to the rise of the open government reform agenda. FOI was at one point the primary tool used to promote governance transparency. FOI is now just one good governance tool in an increasingly crowded field of transparency policy areas. Focus is increasingly shifting toward technology-enabled open data reforms. While many open government reformers see these as positive developments, many traditional FOI proponents have raised concerns. With a few notable exceptions, the academic literature has been silent on this issue. We offer a systematic framework for understanding the potential consequences—both positive and negative—of the open government agenda for FOI policy and implementation….(More)”.

Assessing the Legitimacy of “Open” and “Closed” Data Partnerships for Sustainable Development

Curated on Posted on by Stefaan Verhulst

Paper by Andreas Rasche, Mette Morsing and Erik Wetter in Business and Society: “This article examines the legitimacy attached to different types of multi-stakeholder data partnerships occurring in the context of sustainable development. We develop a framework to assess the democratic legitimacy of two types of data partnerships: open data partnerships (where data and insights are mainly freely available) and closed data partnerships (where data and insights are mainly shared within a network of organizations). Our framework specifies criteria for assessing the legitimacy of relevant partnerships with regard to their input legitimacy as well as their output legitimacy. We demonstrate which particular characteristics of open and closed partnerships can be expected to influence an analysis of their input and output legitimacy….(More)”.

Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence

Curated on Posted on by Stefaan Verhulst

Paper by Huimin Xia et al in at Nature Medicine: “Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive electronic health record (EHR) data remains challenging. Here, we show that MLCs can query EHRs in a manner similar to the hypothetico-deductive reasoning used by physicians and unearth associations that previous statistical methods have not found. Our model applies an automated natural language processing system using deep learning techniques to extract clinically relevant information from EHRs. In total, 101.6 million data points from 1,362,559 pediatric patient visits presenting to a major referral center were analyzed to train and validate the framework.

Our model demonstrates high diagnostic accuracy across multiple organ systems and is comparable to experienced pediatricians in diagnosing common childhood diseases. Our study provides a proof of concept for implementing an AI-based system as a means to aid physicians in tackling large amounts of data, augmenting diagnostic evaluations, and to provide clinical decision support in cases of diagnostic uncertainty or complexity. Although this impact may be most evident in areas where healthcare providers are in relative shortage, the benefits of such an AI system are likely to be universal….(More)”.

Impact of a nudging intervention and factors associated with vegetable dish choice among European adolescents

Curated on Posted on by Stefaan Verhulst

Paper by Q. Dos Santos et al: “To test the impact of a nudge strategy (dish of the day strategy) and the factors associated with vegetable dish choice, upon food selection by European adolescents in a real foodservice setting.

A cross-sectional quasi-experimental study was implemented in restaurants in four European countries: Denmark, France, Italy and United Kingdom. In total, 360 individuals aged 12-19 years were allocated into control or intervention groups, and asked to select from meat-based, fish-based, or vegetable-based meals. All three dishes were identically presented in appearance (balls with similar size and weight) and with the same sauce (tomato sauce) and side dishes (pasta and salad). In the intervention condition, the vegetable-based option was presented as the “dish of the day” and numbers of dishes chosen by each group were compared using the Pearson chi-square test. Multivariate logistic regression analysis was run to assess associations between choice of vegetable-based dish and its potential associated factors (adherence to Mediterranean diet, food neophobia, attitudes towards nudging for vegetables, food choice questionnaire, human values scale, social norms and self-estimated health, country, gender and belonging to control or intervention groups). All analyses were run in SPSS 22.0.

The nudging strategy (dish of the day) did not show a difference on the choice of the vegetable-based option among adolescents tested (p = 0.80 for Denmark and France and p = 0.69 and p = 0.53 for Italy and UK, respectively). However, natural dimension of food choice questionnaire, social norms and attitudes towards vegetable nudging were all positively associated with the choice of the vegetable-based dish. Being male was negatively associated with choosing the vegetable-based dish.

The “dish of the day” strategy did not work under the study conditions. Choice of the vegetable-based dish was predicted by natural dimension, social norms, gender and attitudes towards vegetable nudging. An understanding of factors related to choosing vegetable based dishes is necessary for the development and implementation of public policy interventions aiming to increase the consumption of vegetables among adolescents….(More)”

Show me the Data! A Systematic Mapping on Open Government Data Visualization

Curated on Posted on by Stefaan Verhulst

Paper by André Eberhardt and Milene Selbach Silveira: “During the last years many government organizations have adopted Open Government Data policies to make their data publicly available. Although governments are having success on publishing their data, the availability of the datasets is not enough to people to make use of it due to lack of technical expertise such as programming skills and knowledge on data management. In this scenario, Visualization Techniques can be applied to Open Government Data in order to help to solve this problem.

In this sense, we analyzed previously published papers related to Open Government Data Visualization in order to provide an overview about how visualization techniques are being applied to Open Government Data and which are the most common challenges when dealing with it. A systematic mapping study was conducted to survey the papers that were published in this area. The study found 775 papers and, after applying all inclusion and exclusion criteria, 32 papers were selected. Among other results, we found that datasets related to transportation are the main ones being used and Map is the most used visualization technique. Finally, we report that data quality is the main challenge being reported by studies that applied visualization techniques to Open Government Data…(More)”.

Smart Contracts and Their Identity Crisis

Curated on Posted on by Stefaan Verhulst

Paper by Alvaro Gonzalez Rivas, Mariya Tsyganova and Eliza Mik: “Many expect Smart Contracts (SC’s) to disrupt the way contracts are done implying that SC have the potential to affect all commercial relationships. SC’s are automatization tools; therefore, proponents claim that SC’s can reduce transaction costs through disintermediation and risk reduction.

This is an over-simplification of the role of relationships, contract law, and risk. We believe there is a gap in the understanding of the capabilities of SC’s. With that in mind we seek to define an amorphous term and clarify the capabilities of SC’s, intending to facilitate future SC research. We’ve examined the legal, technical, and IS views from an academic and practitioner’s perspective. We conclude that SC’s have taken many forms, becoming a suitcase word for any sort of code stored on a blockchain, including the embodiment of contractual terms; and that the immutable nature of SC’s is a barrier to their adoption in uncertain and multi-contextual environments….(More)”.

Using Personal Informatics Data in Collaboration among People with Different Expertise

Curated on Posted on by Stefaan Verhulst

Dissertation by Chia-Fang Chung: “Many people collect and analyze data about themselves to improve their health and wellbeing. With the prevalence of smartphones and wearable sensors, people are able to collect detailed and complex data about their everyday behaviors, such as diet, exercise, and sleep. This everyday behavioral data can support individual health goals, help manage health conditions, and complement traditional medical examinations conducted in clinical visits. However, people often need support to interpret this self-tracked data. For example, many people share their data with health experts, hoping to use this data to support more personalized diagnosis and recommendations as well as to receive emotional support. However, when attempting to use this data in collaborations, people and their health experts often struggle to make sense of the data. My dissertation examines how to support collaborations between individuals and health experts using personal informatics data.

My research builds an empirical understanding of individual and collaboration goals around using personal informatics data, current practices of using this data to support collaboration, and challenges and expectations for integrating the use of this data into clinical workflows. These understandings help designers and researchers advance the design of personal informatics systems as well as the theoretical understandings of patient-provider collaboration.

Based on my formative work, I propose design and theoretical considerations regarding interactions between individuals and health experts mediated by personal informatics data. System designers and personal informatics researchers need to consider collaborations occurred throughout the personal tracking process. Patient-provider collaboration might influence individual decisions to track and to review, and systems supporting this collaboration need to consider individual and collaborative goals as well as support communication around these goals. Designers and researchers should also attend to individual privacy needs when personal informatics data is shared and used across different healthcare contexts. With these design guidelines in mind, I design and develop Foodprint, a photo-based food diary and visualization system. I also conduct field evaluations to understand the use of lightweight data collection and integration to support collaboration around personal informatics data. Findings from these field deployments indicate that photo-based visualizations allow both participants and health experts to easily understand eating patterns relevant to individual health goals. Participants and health experts can then focus on individual health goals and questions, exchange knowledge to support individualized diagnoses and recommendations, and develop actionable and feasible plans to accommodate individual routines….(More)”.