Project objectives Radicalisation research leads to ethical and legal questions and issues. These issues need to be addressed in way that helps the project progress in ethically and legally acceptable manner. Description of Work The legal analysis in SAFIRE addressed questions such as which behavior associated with radicalisation is criminal behaviour. The ethical issues were addressed throughout the project in close cooperation between the ethicists and the researchers using a method called ethical parallel research. Results A legal analysis was made about criminal law and radicalisation. During the project lively discussions were held in the research team about ethical issues. An ethical justification for interventions in radicalisation processes has been written. With regard to research ethics: An indirect informed consent procedure for interviews with (former) radicals has been designed. Practical guidelines to prevent obtaining information that could lead to indirect identification of respondents were developed.
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This document presents the findings of a study into methods that can help counterterrorism professionals make decisions about ethical problems. The study was commissioned by the Research and Documentation Centre (Wetenschappelijk Onderzoeken Documentatiecentrum, WODC) of the Dutch Ministry of Security and Justice (Ministerie van Veiligheid en Justitie), on behalf of the National Coordinator for Counterterrorism and Security (Nationaal Coördinator Terrorismebestrijding en Veiligheid,NCTV). The research team at RAND Europe was complemented by applied ethics expert Anke van Gorp from the Research Centre for Social Innovation (Kenniscentrum Sociale Innovatie) at Hogeschool Utrecht. The study provides an inventory of methods to support ethical decision-making in counterterrorism, drawing on the experience of other public sectors – healthcare, social work, policing and intelligence – and multiple countries, primarily the Netherlands and the United Kingdom
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In het boek komen 40 experts aan het woord, die in duidelijke taal uitleggen wat AI is, en welke vragen, uitdagingen en kansen de technologie met zich meebrengt.
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In this chapter, we propose an ethical framework for serious game design, which we term the Ecosystem for Designing Games Ethically (EDGE).EDGE expands on Zagal’s categorization of ethical areas in game design by incorporating the different contexts of design and their use. In addition, we leverage these contexts to suggest four guidelines that support Ethical Stewardship in serious game design. We conclude by discussing a number of specific areas inwhich ethics plays a role in serious game design. These include games in (a) amilitary context, (b) the consideration of privacy issues, and (c) the evaluation ofgame design choices.
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People tend to be hesitant toward algorithmic tools, and this aversion potentially affects how innovations in artificial intelligence (AI) are effectively implemented. Explanatory mechanisms for aversion are based on individual or structural issues but often lack reflection on real-world contexts. Our study addresses this gap through a mixed-method approach, analyzing seven cases of AI deployment and their public reception on social media and in news articles. Using the Contextual Integrity framework, we argue that most often it is not the AI technology that is perceived as problematic, but that processes related to transparency, consent, and lack of influence by individuals raise aversion. Future research into aversion should acknowledge that technologies cannot be extricated from their contexts if they aim to understand public perceptions of AI innovation.
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Abstract for World Physiotherapy Congress 2021Title Ethical Considerations of Using Machine Learning for Decision Support in Occupational Physical Therapy: a narrative literature study and ethical deliberation. Authors Marianne W. M. C. Six Dijkstra1,4,7 · Egbert Siebrand2 · Steven Dorrestijn2 · Etto L. Salomons3 ·Michiel F. Reneman4 · Frits G. J. Oosterveld1 · Remko Soer1,5 · Douglas P. Gross6 · Hendrik J. Bieleman1 Presenter and contactName: Marianne W. M. C. Six DijkstraEmail: w.m.c.sixdijkstra@saxion.nlAdres: School of Health, Saxion University of Applied Sciences/AGZ, M.H. Tromplaan 28, 7500 KB, Enschede, The NetherlandsTel: +31(0)612379329 1 School of Health, Saxion University of AppliedSciences, Enschede, The Netherlands2 Research Group Ethics & Technology, Saxion Universityof Applied Sciences, Enschede, The Netherlands3 School of Ambient Intelligence, Saxion Universityof Applied Sciences, Enschede, The Netherlands4 Department of Rehabilitation Medicine, University MedicalCenter Groningen, University of Groningen, Groningen,The Netherlands5 University Medical Center Groningen, Pain Centre,University of Groningen, Groningen, The Netherlands6 Department of Physical Therapy, University of Alberta,Edmonton, Canada7 University of Groningen, Groningen, The Netherlands Funding This study was funded by Netherlands Organisation for Scientific Research (NWO) (023.011.076) and Saxion University of Applied Sciences in The Netherlands. The funding source had no involvementin study design, data collection, analysis or interpretation, in the writing of the report, or the decision to submit the article for publication.Ethical approvalThis study is part of a PhD project entitled “Development of a Decision Support System – Artificial Intelligence advices for Sustainable Employability”. The Ethics Board at the University Medical Center Groningen in The Netherlands decided that formal approval of the study was not necessary because all workers were subjected to care as usual only.AbstractBackground Computer algorithms and Machine Learning (ML) will be integrated into clinical decision support within physical therapy. This will change the interaction between therapists and their clients, with unknown consequences.Purpose The aim of this study was to explore ethical considerations and potential consequences of using ML based decision support tools (DSTs). We used an example in the context of occupational physical therapy.Methods We conducted an ethical deliberation. This was supported by a narrative literature review of publications about ML and DSTs in occupational health and by an assessment of the potential impact of ML-DSTs according to frameworks from medical ethics and philosophy of technology. We introduce a hypothetical clinical scenario in occupational physical therapy to reflect on biomedical ethical principles: respect for autonomy, beneficence, non-maleficence and justice. The reflection was guided by the Product Impact Tool.
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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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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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Poster KIM voor de ECR is nu online te zien via EPOS: https://epos.myesr.org/poster/esr/ecr2022/C-16092 posternummer: C-16092, ECR 2022 Purpose Artificial Intelligence (AI) has developed at high speed the last few years and will substantially change various disciplines (1,2). These changes are also noticeable in the field of radiology, nuclear medicine and radiotherapy. However, the focus of attention has mainly been on the radiologist profession, whereas the role of the radiographer has been largely ignored (3). As long as AI for radiology was focused on image recognition and diagnosis, the little attention for the radiographer might be justifiable. But with AI becoming more and more a part of the workflow management, treatment planning and image reconstruction for example, the work of the radiographer will change. However, their training (courses Medical Imaging and Radiotherapeutic Techniques) hardly contain any AI education. Radiographers in the Netherlands are therefore not prepared for changes that will come with the introduction of AI into everyday work.
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