AI ethics in March 2018

BACKGROUND: Natural language processing applied to clinical text or aimed at a clinical outcome has been thriving in recent years. This paper offers the first broad overview of clinical Natural Language Processing (NLP) for languages other than English. Recent studies are summarized to offer insights and outline opportunities in this area. MAIN BODY: We envision three groups of intended readers: (1) NLP researchers leveraging experience gained in other languages, (2) NLP researchers faced with e

Social robotics entertains a particular relationship with anthropomorphism, which it neither sees as a cognitive error, nor as a sign of immaturity. Rather it considers that this common human tendency, which is hypothesized to have evolved because it favoured cooperation among early humans, can be used today to facilitate social interactions between humans and a new type of cooperative and interactive agents – social robots. This approach leads social robotics to focus research on the engineerin

In this paper we discuss the social and ethical issues that arise as a result of digitization based on six dominant technologies: Internet of Things, robotics, biometrics, persuasive technology, virtual & augmented reality, and digital platforms. We highlight the many developments in the digitizing society that appear to be at odds with six recurring themes revealing from our analysis of the scientific literature on the dominant technologies: privacy, autonomy, security, human dignity, justice,

Purpose The purpose of this paper is to investigate the potential roles for service robots (i.e. socially assistive robots) in value networks of elderly care. Taking an elderly person’s perspective, it defines robot roles according to their value co-creating/destroying potential for the elderly user (i.e. focal actor), while acknowledging consequences for a network of users around the elderly (i.e. network actors). Design/methodology/approach This qualitative, interpretative study employs in-dep

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research a

How does education affect cortical organization? All literate adults possess a region specialized for letter strings, the visual word form area (VWFA), within the mosaic of ventral regions involved in processing other visual categories such as objects, places, faces, or body parts. Therefore, the acquisition of literacy may induce a reorientation of cortical maps towards letters at the expense of other categories such as faces. To test this cortical recycling hypothesis, we studied how the visua

The purpose of this study is to evaluate the feasibility and patient acceptability of a novel artificial intelligence (AI)-based diabetic retinopathy (DR) screening model within endocrinology outpatient settings. Adults with diabetes were recruited from two urban endocrinology outpatient clinics and single-field, non-mydriatic fundus photographs were taken and graded for referable DR ( ≥ pre-proliferative DR). Each participant underwent; (1) automated screening model; where a deep learning algor

As virtual reality (VR) technology and systems become more commercially available and accessible, more and more psychologists are starting to integrate VR as part of their methods. This approach offers major advantages in experimental control, reproducibility, and ecological validity, but also has limitations and hidden pitfalls which may distract the novice user. This study aimed to guide the psychologist into the novel world of VR, reviewing available instrumentation and mapping the landscape

PURPOSE: The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands. MATERIAL AND METHODS: analysis. RESULTS: NTCP models based on the parotid mean dose failed to predict xerostomia (AUCs < 0.60). The most informative predictors were found for late and long-term xerostomia. Late

Blockchain technology provides decentralized consensus and potentially enlarges the contracting space using smart contracts with tamper-proofness and algorithmic executions. Meanwhile, generating decentralized consensus entails distributing information which necessarily alters the informational environment. We analyze how decentralization affects consensus effectiveness, and how the quintessential features of blockchain reshape industrial organization and the landscape of competition. Smart cont

Abstract Organizations often employ data-driven models to inform decisions that can have a significant impact on people's lives (e.g., university admissions, hiring). In order to protect people's privacy and prevent discrimination, these decision-makers may choose to delete or avoid collecting social category data, like sex and race. In this article, we argue that such censoring can exacerbate discrimination by making biases more difficult to detect. We begin by detailing how computerized decisi

BACKGROUND: Tuberculosis (TB) is a global issue that seriously endangers public health. Pathology is one of the most important means for diagnosing TB in clinical practice. To confirm TB as the diagnosis, finding specially stained TB bacilli under a microscope is critical. Because of the very small size and number of bacilli, it is a time-consuming and strenuous work even for experienced pathologists, and this strenuosity often leads to low detection rate and false diagnoses. We investigated the