In May 2018, the new Dutch Intelligence and Security Services Act 2017 (Wet op de Inlichtingen- en veiligheidsdiensten, Wiv) will enter into force. It replaces the previous 2002 Act and incorporates many reforms to the information gathering powers of the two intelligence and security services as well as to the accountability and oversight mechanisms. Due to the technologyneutral approach, both the civil and the military intelligence services are now authorized to, for example, intercept communications in bulk, hack third parties, decrypt files, store DNA or use any other future innovative technology. Also, the national security legislation extends the possibilities for the indiscriminate collection of data, and for the processing, storage and analysis thereof. The process leading to the law includes substantial criticism from the various stakeholders involved. Upon publication of this report, an official consultative referendum is being organized on the new act. The aim of this policy brief is to provide an international audience with a comprehensive overview of the most relevant aspects of the act and its context. In addition, there is considerable focus on the checks and balances as well as the bottlenecks of the Dutch intelligence gathering reform. The selection of topics is based on the core issues addressed during the parliamentary debate and on the authors’ insights.
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By analysing intelligence-gathering reform legislation this article discusses access to justice for communications interception by the intelligence and security services. In the aftermath of the Snowden revelations, sophisticated oversight systems for bulk communications surveillance are being established across the globe. In the Netherlands prior judicial consent and a binding complaint procedure have been established. However, although checks and balances for targeted communications interference have been created, accountability mechanisms are less equipped to effectively remedy indiscriminate interference. Therefore, within the context of mass communications surveillance programs, access to justice for complainants remains a contentious issue.
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Het aantal banen neemt toe. Jaarlijks ontstaan er volgens CBS (2019) ongeveer 900 duizend vacatures. Deze keer is de verandering op de arbeidsmarkt niet het resultaat van één enkele factor, maar eerder een combinatie van vijf factoren: snelle technologische vooruitgang, diepgaande veranderingen in gezondheid en demografie, een groeiende economie, toenemende globalisering en belangrijke maatschappelijke veranderingen - die samen een groot deel van wat we als vanzelfsprekend beschouwen, fundamenteel transformeren (Gratton, 2011). Digitalisering en automatisering spelen een grote rol bij deze veranderingen. Er zijn optimistische voorspellingen dat nieuwe technologieën de arbeidsmarkt ten goede komen. Technologie verlaagt bijvoorbeeld de werkdruk. We zouden door technologie zelfs naar een kortere werkweek kunnen en nieuwe banen erbij krijgen, zodat niemand ongewild zonder werk komt te zitten (Ford, 2015; Giang, 2015; Mahdawi, 2017; MGI, 2017). Echter, de angst dat automatisering banen over gaat nemen en er een tekort aan werk gaat ontstaan, is ook een veelgehoorde zorg (Alexis, 2017; Ford, 2015; Giang, 2015; MGI, 2017; WRR. 2013).
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Artificial Intelligence systems are more and more being introduced into first response; however, this introduction needs to be done responsibly. While generic claims on what this entails already exist, more details are required to understand the exact nature of responsible application of AI within the first response domain. The context in which AI systems are applied largely determines the ethical, legal, and societal impact and how to deal with this impact responsibly. For that reason, we empirically investigate relevant human values that are affected by the introduction of a specific AI-based Decision Aid (AIDA), a decision support system under development for Fire Services in the Netherlands. We held 10 expert group sessions and discussed the impact of AIDA on different stakeholders. This paper presents the design and implementation of the study and, as we are still in process of analyzing the sessions in detail, summarizes preliminary insights and steps forward.
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Editorial on the Research Topic "Leveraging artificial intelligence and open science for toxicological risk assessment"
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With artificial intelligence (AI) systems entering our working and leisure environments with increasing adaptation and learning capabilities, new opportunities arise for developing hybrid (human-AI) intelligence (HI) systems, comprising new ways of collaboration. However, there is not yet a structured way of specifying design solutions of collaboration for hybrid intelligence (HI) systems and there is a lack of best practices shared across application domains. We address this gap by investigating the generalization of specific design solutions into design patterns that can be shared and applied in different contexts. We present a human-centered bottom-up approach for the specification of design solutions and their abstraction into team design patterns. We apply the proposed approach for 4 concrete HI use cases and show the successful extraction of team design patterns that are generalizable, providing re-usable design components across various domains. This work advances previous research on team design patterns and designing applications of HI systems.
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Fire fighters operate in a dangerous, dynamic, and complex environment. Artificial Intelligence (AI) systems can contribute to improve fire fighters’ situation awareness and decision-making. However, the introduction of AI systems needs to be done responsibly, taking (human) values into account, especially as the situation in which fire fighters operate is uncertain and decisions have a big impact. In this research, we investigate values that are affected by the introduction of AI systems for fire services by conducting several semi-structured focus group sessions with (operational) fire service personnel. The focus group outcomes are qualitatively analyzed and key values are identified and discussed. This research is a first step in an iterative process towards a generic framework of ethical aspects for the introduction of AI systems in first response, which will give insight into the relevant ethical aspects to take into account when developing AI systems for first responders.
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Smart home technologies are a large potential market for the construction and building services industry. This chapter discusses the topics consultants, installers, and suppliers of home automation systems encounter when working in the field. Improved communication skills and more flexible approaches to the design and installing of building services leads to many new opportunities for new products and services. There are a large number of requirements from the perspective of architectural design and building services engineering, which relate to the infrastructure that is needed for smart homes. An overview of these electrical engineering and ICT requirements is discussed. When working with clients, it is important to consider the additional set of rules of working in their homes. Clients may have additional needs in the field of home modifications that can also be addressed when doing retrofitting projects. An outline of steps to get stared and essential questions for professional care organization is given.
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Ambient intelligence technologies are a means to support ageing-in-place by monitoring clients in the home. In this study, monitoring is applied for the purpose of raising an alarm in an emergency situation, and thereby, providing an increased sense of safety and security. Apart from these technological solutions, there are numerous environmental interventions in the home environment that can support people to age-in-place. The aim of this study was to investigate the needs and motives, related to ageing-in-place, of the respondents receiving ambient intelligence technologies, and to investigate whether, and how, these technologies contributed to aspects of ageing-in-place. This paper presents the results of a qualitative study comprised of interviews and observations of technology and environmental interventions in the home environment among 18 community-dwelling older adults with a complex demand for care.
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The healthcare sector has been confronted with rapidly rising healthcare costs and a shortage of medical staff. At the same time, the field of Artificial Intelligence (AI) has emerged as a promising area of research, offering potential benefits for healthcare. Despite the potential of AI to support healthcare, its widespread implementation, especially in healthcare, remains limited. One possible factor contributing to that is the lack of trust in AI algorithms among healthcare professionals. Previous studies have indicated that explainability plays a crucial role in establishing trust in AI systems. This study aims to explore trust in AI and its connection to explainability in a medical setting. A rapid review was conducted to provide an overview of the existing knowledge and research on trust and explainability. Building upon these insights, a dashboard interface was developed to present the output of an AI-based decision-support tool along with explanatory information, with the aim of enhancing explainability of the AI for healthcare professionals. To investigate the impact of the dashboard and its explanations on healthcare professionals, an exploratory case study was conducted. The study encompassed an assessment of participants’ trust in the AI system, their perception of its explainability, as well as their evaluations of perceived ease of use and perceived usefulness. The initial findings from the case study indicate a positive correlation between perceived explainability and trust in the AI system. Our preliminary findings suggest that enhancing the explainability of AI systems could increase trust among healthcare professionals. This may contribute to an increased acceptance and adoption of AI in healthcare. However, a more elaborate experiment with the dashboard is essential.
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