Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

Segmenting Publics

This research synthesis was commissioned by the National Co-ordinating Centre for Public Engagement (NCCPE) and the Economic and Social Research Council (ESRC) to examine audience segmentation methods and tools in the area of public engagement. It provides resources for assessing the ways in which segmentation tools might be used to enhance the various activities through which models of public engagement in higher education are implemented. Understanding the opinions, values, and motivations of members of the public is a crucial feature of successful engagement. Segmentation methods can offer potential resources to help understand the complex set of interests and attitudes that the public have towards higher education. Key findings: There exist a number of existing segmentations which address many of the areas of activity found in Universities and HEIs. These include segmentations which inform strategic planning of communications; segmentations which inform the design of collaborative engagement activities by museums, galleries, and libraries; and segmentations that are used to identify under-represented users and consumers. Segmentation is, on its own, only a tool, used in different ways in different contexts. The broader strategic rationale shaping the application and design of segmentation methods is a crucial factor in determining the utility of segmentation tools. Four issues emerged of particular importance: 1. Segmentation exercises are costly and technically complex. Undertaking segmentations therefore requires significant commitment of financial and professional resources by HEIs; the appropriate interpretation, analysis, and application of segmentation exercises also require high levels of professional capacity and expertise 2. Undertaking a segmentation exercise has implications for the internal organisational operations of HEIs, not only for how they engage with external publics and stakeholders 3. Segmentation tools are adopted to inform interventions of various sorts, and superficially to differentiate and sometime discriminate between how groups of people are addressed and engaged. 4. For HEIs, the ethical issues and reputational risks which have been identified in this Research Synthesis as endemic to the application of segmentation methods for public purposes are particularly relevant

Supplement to MTI Study on Selective Passenger Screening in the Mass Transit Rail Environment, MTI Report 09-05

This supplement updates and adds to MTIs 2007 report on Selective Screening of Rail Passengers (Jenkins and Butterworth MTI 07-06: Selective Screening of Rail Passengers). The report reviews current screening programs implemented (or planned) by nine transit agencies, identifying best practices. The authors also discuss why three other transit agencies decided not to implement passenger screening at this time. The supplement reconfirms earlier conclusions that selective screening is a viable security option, but that effective screening must be based on clear policies and carefully managed to avoid perceptions of racial or ethnic profiling, and that screening must have public support. The supplement also addresses new developments, such as vapor-wake detection canines, continuing challenges, and areas of debate. Those interested should also read MTI S-09-01 Rail Passenger Selective Screening Summit

Designing the Health-related Internet of Things: Ethical Principles and Guidelines

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may be rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols

The Chilling Effect of Governance-by-Data on Data Markets

Big data has become an important resource not only for commerce but also for governance. Governance-by-data seeks to take advantage of the bulk of data collected by private firms to make law enforcement more efficient. It can take many forms, including setting enforcement priorities, affecting methods of proof, and even changing the content of legal norms. For instance, car manufacturers can use real-time data on the driving habits of drivers to learn how their cars respond to different driving patterns. If shared with the government, the same data can be used to enforce speed limits or even to craft personalized speed limits for each driver. The sharing of data for the purpose of law enforcement raises obvious concerns for civil liberties. Indeed, over the past two decades, scholars have focused on the risks arising from such data sharing for privacy and freedom. So far, however, the literature has generally overlooked the implications of such dual use of data for data markets and data-driven innovation. In this Essay, we argue that governance-by-data may create chilling effects that could distort data collection and data-driven innovation. We challenge the assumptions that incentives to collect data are a given and that firms will continue to collect data notwithstanding governmental access to such data. We show that, in some instances, an inverse relationship exists between incentives for collecting data and sharing it for the purpose of governance. Moreover, the incentives of data subjects to allow the collection of data by private entities might also change, thereby potentially affecting the efficiency of data-driven markets and, subsequently, data-driven innovation. As a result, data markets might not provide sufficient and adequate data to support digital governance. This, in turn, might significantly affect welfare

Stops and Stares: Street Stops, Surveillance, and Race in the New Policing

The use of proactive tactics to disrupt criminal activities, such as Terry street stops and concentrated misdemeanor arrests, are essential to the “new policing.” This model applies complex metrics, strong management, and aggressive enforcement and surveillance to focus policing on high crime risk persons and places. The tactics endemic to the “new policing” gave rise in the 1990s to popular, legal, political and social science concerns about disparate treatment of minority groups in their everyday encounters with law enforcement. Empirical evidence showed that minorities were indeed stopped and arrested more frequently than similarly situated whites, even when controlling for local social and crime conditions. In this article, we examine racial disparities under a unique configuration of the street stop prong of the “new policing” – the inclusion of non-contact observations (or surveillances) in the field interrogation (or investigative stop) activity of Boston Police Department officers. We show that Boston Police officers focus significant portions of their field investigation activity in two areas: suspected and actual gang members, and the city’s high crime areas. Minority neighborhoods experience higher levels of field interrogation and surveillance activity net of crime and other social factors. Relative to white suspects, Black suspects are more likely to be observed, interrogated, and frisked or searched controlling for gang membership and prior arrest history. Moreover, relative to their black counterparts, white police officers conduct high numbers of field investigations and are more likely to frisk/search subjects of all races. We distinguish between preference-based and statistical discrimination by comparing stops by officer-suspect racial pairs. If officer activity is independent of officer race, we would infer that disproportionate stops of minorities reflect statistical discrimination. We show instead that officers seem more likely to investigate and frisk or search a minority suspect if officer and suspect race differ. We locate these results in the broader tensions of racial profiling that pose recurring social and constitutional concerns in the “new policing.”

In Things We Trust? Towards trustability in the Internet of Things

This essay discusses the main privacy, security and trustability issues with the Internet of Things