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Editorial: Leveraging artificial intelligence and open science for toxicological risk assessment

Editorial on the Research Topic "Leveraging artificial intelligence and open science for toxicological risk assessment"

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Lives of data

Lives of Data maps the historical and emergent dynamics of big data, computing, and society in India. Data infrastructures are now more global than ever before. In much of the world, new sociotechnical possibilities of big data and artificial intelligence are unfolding under the long shadows cast by infra/structural inequalities, colonialism, modernization, and national sovereignty. This book offers critical vantage points for looking at big data and its shadows, as they play out in uneven encounters of machinic and cultural relationalities of data in India’s socio-politically disparate and diverse contexts.Lives of Data emerged from research projects and workshops at the Sarai programme, Centre for the Study of Developing Societies. It brings together fifteen interdisciplinary scholars and practitioners to set up a collaborative research agenda on computational cultures. The essays offer wide-ranging analyses of media and techno-scientific trajectories of data analytics, disruptive formations of digital economy, and the grounded practices of data-driven governance in India. Encompassing history, anthropology, science and technology studies (STS), media studies, civic technology, data science, digital humanities, and journalism, the essays open up possibilities for a truly situated global and sociotechnically specific understanding of the many lives of data.

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Access to Justice for Communications Surveillance and Interception

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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Access to Justice for Communications Surveillance and Interception

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Emotional intelligence of mental health nurses

Aims. The aim of this study is to gain insight into the level of emotional intelligence of mental health nurses in the Netherlands. Background. The focus in research on emotional intelligence to date has been on a variety of professionals. However, little is known about emotional intelligence in mental health nurses. Method. The emotional intelligence of 98 Dutch nurses caring for psychiatric patients is reported. Data were collected with the Bar-On Emotional Quotient Inventory within a cross-sectional research design. Results. The mean level of emotional intelligence of this sample of professionals is statistically significant higher than the emotional intelligence of the general population. Female nurses score significantly higher than men on the subscales Empathy, Social Responsibility, Interpersonal Relationship, Emotional Self-awareness, Self-Actualisation and Assertiveness. No correlations are found between years of experience and age on the one hand and emotional intelligence on the other hand. Conclusions. The results of this study show that nurses in psychiatric care indeed score above average in the emotional intelligence required to cope with the amount of emotional labour involved in daily mental health practice. Relevance to clinical practice. The ascertained large range in emotional intelligence scores among the mental health nurses challenges us to investigate possible implications which higher or lower emotional intelligence levels may have on the quality of care. For instance, a possible relation between the level of emotional intelligence and the quality of the therapeutic nurse–patient relationship or the relation between the level of emotional intelligence and the manner of coping with situations characterised by a great amount of emotional labour (such as caring for patients who self-harm or are suicidal).

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Future skills of journalists and artificial intelligence in education

Information about a research study on how data science and artificial intelligence can contribute to modern education aimed at identifying and developing talents of students. De presentatie is gepubliceerd onder de titel: Future skills : and whre to find them?

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Future skills of journalists and artificial intelligence in education

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Artificial Intelligence for Radiographers

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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Solving domain-specific problems with computational thinking

Computational thinking (CT) skills are crucial for every modern profession in which large amounts of data are processed. In K-12 curricula, CT skills are often taught in separate programming courses. However, without specific instructions, CT skills are not automatically transferred to other domains in the curriculum when they are developed while learning to program in a separate programming course. In modern professions, CT is often applied in the context of a specific domain. Therefore, learning CT skills in other domains, as opposed to computer science, could be of great value. CT and domain-specific subjects can be combined in different ways. In the CT literature, a distinction can be made among CT applications that substitute, augment, modify or redefine the original subject. On the substitute level, CT replaces exercises but CT is not necessary for reaching the learning outcomes. On the redefining level, CT changes the questions that can be posed within the subject, and learning objectives and assessment are integrated. In this short paper, we present examples of how CT and history, mathematics, biology and language subjects can be combined at all four levels. These examples and the framework on which they are based provide a guideline for design-based research on CT and subject integration.

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Solving domain-specific problems with computational thinking

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Developing Team Design Patterns for Hybrid Intelligence Systems

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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Developing Team Design Patterns for Hybrid Intelligence Systems

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Requirements and challenges for hybrid intelligence

The potential for Artificial Intelligence is widely proclaimed. Yet, in everyday educational settings the use of this technology is limited. Particularly, if we consider smart systems that actually interact with learners in a knowledgeable way and as such support the learning process. It illustrates the fact that teaching professionally is a complex challenge that is beyond the capabilities of current autonomous robots. On the other hand, dedicated forms of Artificial Intelligence can be very good at certain things. For example, computers are excellent chess players and automated route planners easily outperform humans. To deploy this potential, experts argue for a hybrid approach in which humans and smart systems collaboratively accomplish goals. How to realize this for education? What does it entail in practice? In this contribution, we investigate the idea of a hybrid approach in secondary education. As a case-study, we focus on learners acquiring systems thinking skills and our recently for this purpose developed pedagogical approach. Particularly, we discuss the kind of Artificial Intelligence that is needed in this situation, as well as which tasks the software can perform well and which tasks are better, or necessarily, left with the teacher.

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Producten 1.117

Editorial: Leveraging artificial intelligence and open science for toxicological risk assessment

Lives of data

Access to Justice for Communications Surveillance and Interception

Emotional intelligence of mental health nurses

Future skills of journalists and artificial intelligence in education

Artificial Intelligence for Radiographers

Solving domain-specific problems with computational thinking

Developing Team Design Patterns for Hybrid Intelligence Systems

Requirements and challenges for hybrid intelligence

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Producten 1.117

Editorial: Leveraging artificial intelligence and open science for toxicological risk assessment

Lives of data

Access to Justice for Communications Surveillance and Interception

Emotional intelligence of mental health nurses

Future skills of journalists and artificial intelligence in education

Artificial Intelligence for Radiographers

Solving domain-specific problems with computational thinking

Developing Team Design Patterns for Hybrid Intelligence Systems

Requirements and challenges for hybrid intelligence