AI ethics in January 2019

Advancement in automated driving technology has created opportunities for smart urban mobility. Automated vehicles are now a popular topic with the rise of the smart city agenda. However, legislators, urban administrators, policymakers, and planners are unprepared to deal with the possible disruption of autonomous vehicles, which potentially could replace conventional transport. There is a lack of knowledge on how the new capabilities will disrupt and which policy strategies are needed to addres

The last few years have seen a proliferation of principles for AI ethics. There is substantial overlap between different sets of principles, with widespread agreement that AI should be used for the common good, should not be used to harm people or undermine their rights, and should respect widely held values such as fairness, privacy, and autonomy. While articulating and agreeing on principles is important, it is only a starting point. Drawing on comparisons with the field of bioethics, we highl

Image features need to be robust against differences in positioning, acquisition and segmentation to ensure reproducibility. Radiomic models that only include robust features can be used to analyse new images, whereas models with non-robust features may fail to predict the outcome of interest accurately. Test-retest imaging is recommended to assess robustness, but may not be available for the phenotype of interest. We therefore investigated 18 combinations of image perturbations to determine fea

There is a long and varied history associated with the evolution of the concept of Corporate Social Responsibility (CSR). However, a historical review is missing in the academic literature that portrays the evolution of the academic understanding of the concept alongside with the public and international events that influenced the social expectations with regards to corporate behavior. The aim of this paper is to provide a distinctive historical perspective on the evolution of CSR as a conceptua

BACKGROUND: 'Big data' has great potential to help address the global health challenge of obesity. However, lack of clarity with regard to the definition of big data and frameworks for effectively using big data in the context of obesity research may be hindering progress. The aim of this study was to establish agreed approaches for the use of big data in obesity-related research. METHODS: A Delphi method of consensus development was used, comprising three survey rounds. In Round 1, participants

The concept of “Industry 4.0” is expected to bring a multitude of benefits for industrial value creation. However, the associated risks hamper its implementation and lack a comprehensive overview. In response, the paper proposes a framework of risks in the context of Industry 4.0 that is related to the Triple Bottom Line of sustainability. The framework is developed from a literature review, as well as from 14 in-depth expert interviews. With respect to economic risks, the risks that are associa

Evolutionary fuzzy systems are one of the greatest advances within the area of computational intelligence. They consist of evolutionary algorithms applied to the design of fuzzy systems. Thanks to this hybridization, superb abilities are provided to fuzzy modeling in many different data science scenarios. This contribution is intended to comprise a position paper developing a comprehensive analysis of the evolutionary fuzzy systems research field. To this end, the "4 W" questions are posed and a

Park managers call for cost-effective and innovative solutions to handle a wide variety of environmental problems that threaten biodiversity in protected areas. Recently, drones have been called upon to revolutionize conservation and hold great potential to evolve and raise better-informed decisions to assist management. Despite great expectations, the benefits that drones could bring to foster effectiveness remain fundamentally unexplored. To address this gap, we performed a literature review a

Formulating data science problems is an uncertain and difficult process. It requires various forms of discretionary work to translate high-level objectives or strategic goals into tractable problems, necessitating, among other things, the identification of appropriate target variables and proxies. While these choices are rarely self-evident, normative assessments of data science projects often take them for granted, even though different translations can raise profoundly different ethical concer

BACKGROUND: Automatic clinical text classification is a natural language processing (NLP) technology that unlocks information embedded in clinical narratives. Machine learning approaches have been shown to be effective for clinical text classification tasks. However, a successful machine learning model usually requires extensive human efforts to create labeled training data and conduct feature engineering. In this study, we propose a clinical text classification paradigm using weak supervision a

BACKGROUND: Physical and functional losses due to aging and diseases decrease human mobility, independence, and quality of life. This study is aimed at summarizing and quantifying these losses in order to motivate solutions to overcome them with a special focus on the possibilities by using lower limb exoskeletons. METHODS: A narrative literature review was performed to determine a broad range of mobility-related physical and functional measures that are affected by aging and selected cardiovasc

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universitie

IntroductionIn recent years, fake news has become an issue that is a threat to public discourse, human society, and democracy (Borges et al., 2018; Qayyum et al., 2019). Fake news refers to fictitious news style content that is fabricated to deceive the public (Aldwairi & Alwahedi, 2018; Jang & Kim, 2018). False information spreads quickly through social media, where it can

Artificial Intelligence is a booming technological domain capable of altering every aspect of our social interactions. In education, AI has begun producing new teaching and learning solutions that are now undergoing testing in different contexts. AI requires advanced infrastructures and an ecosystem of thriving innovators, but what about the urgencies of developing countries? Will they have to wait for the “luxury” of AI? Or should AI be a priority to tackle as soon as possible to reduce the dig

Background Artificial intelligence (AI) is increasingly being used in healthcare. Here, AI-based chatbot systems can act as automated conversational agents, capable of promoting health, providing education, and potentially prompting behaviour change. Exploring the motivation to use health chatbots is required to predict uptake; however, few studies to date have explored their acceptability. This research aimed to explore participants’ willingness to engage with AI-led health chatbots. Methods Th

Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a v

Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, Nanyun Peng. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

This paper uses frame analysis to examine recent high-profile values statements endorsing ethical design for artificial intelligence and machine learning (AI/ML). Guided by insights from values in design and the sociology of business ethics, we uncover the grounding assumptions and terms of debate that make some conversations about ethical design possible while forestalling alternative visions. Vision statements for ethical AI/ML co-opt the language of some critics, folding them into a limited,

Smartphones and smartwatches, which include powerful sensors, provide a readily available platform for implementing and deploying mobile motion-based behavioral biometrics. However, the few studies that utilize these commercial devices for motion-based biometrics are quite limited in terms of the sensors and physical activities that they evaluate. In many such studies, only the smartwatch accelerometer is utilized and only one physical activity, walking, is investigated. In this study we conside

Contextual word embeddings such as BERT have achieved state of the art performance in numerous NLP tasks. Since they are optimized to capture the statistical properties of training data, they tend to pick up on and amplify social stereotypes present in the data as well. In this study, we (1) propose a template-based method to quantify bias in BERT; (2) show that this method obtains more consistent results in capturing social biases than the traditional cosine based method; and (3) conduct a case

In this paper, we consider the use of a team of multiple unmanned aerial vehicles (UAVs) to accomplish a search and rescue (SAR) mission in the minimum time possible while saving the maximum number of people. A novel technique for the SAR problem is proposed and referred to as the layered search and rescue (LSAR) algorithm. The novelty of LSAR involves simulating real disasters to distribute SAR tasks among UAVs. The performance of LSAR is compared, in terms of percentage of rescued survivors an

The smart grid (SG) paradigm is the next technological leap of the conventional electrical grid, contributing to the protection of the physical environment and providing multiple advantages such as increased reliability, better service quality, and the efficient utilization of the existing infrastructure and the renewable energy resources. However, despite the fact that it brings beneficial environmental, economic, and social changes, the existence of such a system possesses important security a