AI ethics in December 2017

The production, reception and discussion of fanfiction is a major aspect of contemporary global media. Thus far, however, the genre has been subject to relatively little rigorous qualitative or quantitative study-a problem that Judith M. Fathallah remedies here through close analysis of fanfiction related to Sherlock, Supernatural, and Game of Thrones. Her large-scale study of the sites, reception, and fan rejections of fanfic demonstrate how the genre works to legitimate itself through traditio

Artificial intelligence (AI) generally and machine learning (ML) specifically demonstrate impressive practical success in many different application domains, e.g. in autonomous driving, speech recognition, or recommender systems. Deep learning approaches, trained on extremely large data sets or using reinforcement learning methods have even exceeded human performance in visual tasks, particularly on playing games such as Atari, or mastering the game of Go. Even in the medical domain there are re

OBJECTIVES: We undertook a cluster-randomised controlled trial exploring the effect of a therapeutic companion robot (PARO) compared to a look-alike plush toy and usual care on dementia symptoms of long-term care residents. Complementing the reported quantitative outcomes , this paper provides critical reflection and commentary on individual participant responses to PARO, observed through video recordings , with a view to informing clinical practice and research. METHOD: A descriptive, qualitati

Randomized Controlled Trials (RCTs) are increasingly popular in the social sciences, not only in medicine. We argue that the lay public, and sometimes researchers, put too much trust in RCTs over other methods of investigation. Contrary to frequent claims in the applied literature, randomization does not equalize everything other than the treatment in the treatment and control groups, it does not automatically deliver a precise estimate of the average treatment effect (ATE), and it does not reli

Since an ever-increasing part of the population makes use of social media in their day-to-day lives, social media data is being analysed in many different disciplines. The social media analytics process involves four distinct steps, data discovery, collection, preparation, and analysis. While there is a great deal of literature on the challenges and difficulties involving specific data analysis methods, there hardly exists research on the stages of data discovery, collection, and preparation. To

In a time when conservative politicians challenge the irrefutability of scientific findings such as climate change, it is more important than ever to understand the conflict at the heart of the “religion vs. science” debates unfolding in the public sphere. In this groundbreaking work, John H. Evans reveals that, with a few limited exceptions, even the most conservative religious Americans accept science’s ability to make factual claims about the world. However, many religious people take issue w

Recent developments in the field of artificial intelligence and data analytics are facilitating the automation of some consumer chores (e.g., in smart homes and in self-driving cars) and allow the emergence of big-data-driven, micro-targeting marketing practices (e.g., personalized content recommendation algorithms). We contend that those developments can generate a tension for marketers, consumers, and policy makers: They can, on the one hand, contribute to consumer well-being by making consume

Commercial mobile apps for health behavior change are flourishing in the marketplace, but little evidence exists to support their use. This paper summarizes methods for evaluating the content, usability, and efficacy of commercially available health apps. Content analyses can be used to compare app features with clinical guidelines, evidence-based protocols, and behavior change techniques. Usability testing can establish how well an app functions and serves its intended purpose for a target popu

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activit

Driver fatigue is an important contributor to road accidents, and fatigue detection has major implications for transportation safety. The aim of this research is to analyze the multiple entropy fusion method and evaluate several channel regions to effectively detect a driver's fatigue state based on electroencephalogram (EEG) records. First, we fused multiple entropies, i.e., spectral entropy, approximate entropy, sample entropy and fuzzy entropy, as features compared with autoregressive (AR) mo

We describe a form of moral artificial intelligence that could be used to improve human moral decision-making. We call it the “artificial moral advisor” (AMA). The AMA would implement a quasi-relativistic version of the “ideal observer” famously described by Roderick Firth. We describe similarities and differences between the AMA and Firth’s ideal observer. Like Firth’s ideal observer, the AMA is disinterested, dispassionate, and consistent in its judgments. Unlike Firth’s observer, the AMA is n

Ultrasonography is the best available tool for the initial work-up of thyroid nodules. Substantial interobserver variability has been documented in the recognition and reporting of some of the lesion characteristics. A number of classification systems have been developed to estimate the likelihood of malignancy: several of them have been endorsed by scientific societies, but their reproducibility is yet to be assessed. We evaluated the interobserver variability of the AACE/ACE/AME, ACR, ATA, EU-

BACKGROUND: Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. METHODS: A systematic search of the bibliographic databases PubMed,

BACKGROUND: Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. METHODS: In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels f

The adoption of digital communications, facilitated by Internet technology, has been among the most significant international business developments of the past 25 years. This article investigates the effect of these new technologies and the changing global business environment to understand how relational approaches to international market entry (IME) are changing in light of macro developments. Despite substantial resources in business practice dedicated to combining relational strategies in di