AI ethics in June 2017

The 21st century has ushered in the age of big data and data economy, in which data DNA , which carries important knowledge, insights, and potential, has become an intrinsic constituent of all data-based organisms. An appropriate understanding of data DNA and its organisms relies on the new field of data science and its keystone, analytics . Although it is widely debated whether big data is only hype and buzz, and data science is still in a very early phase, significant challenges and opportunit

BACKGROUND: Mental illness is quickly becoming one of the most prevalent public health problems worldwide. Social network platforms, where users can express their emotions, feelings, and thoughts, are a valuable source of data for researching mental health, and techniques based on machine learning are increasingly used for this purpose. OBJECTIVE: The objective of this review was to explore the scope and limits of cutting-edge techniques that researchers are using for predictive analytics in men

To overcome the individual differences, an accurate electroencephalogram (EEG)-based emotion-classification system requires a considerable amount of ecological calibration data for each individual, which is labor-intensive and time-consuming. Transfer learning (TL) has drawn increasing attention in the field of EEG signal mining in recent years. The TL leverages existing data collected from other people to build a model for a new individual with little calibration data. However, brute-force tran

BACKGROUND: Autism spectrum disorder (ASD) is a childhood-onset neurodevelopmental disorder with a rapidly rising prevalence, currently affecting 1 in 68 children, and over 3.5 million people in the United States. Current ASD interventions are primarily based on in-person behavioral therapies that are both costly and difficult to access. These interventions aim to address some of the fundamental deficits that clinically characterize ASD, including deficits in social communication, and the presen

Insights Through a combination of factors, AI has recently made significant progress and is now integrated in many successful products. In the future, AI will become available as a resource to use by non-expertsintelligence on tap. Interaction designers need to consider AI as a new design material, with its own unique opportunities and limitations.

In this paper, we present a profound literature review of the Artificial Intelligence (AI). After defining it, we briefly cover its history and enumerate its principal fields of application. We name for example information system, commerce, image processing, human-computer interaction, data compression, robotics, route planning, etc. Moreover, the test that defines an artificially intelligent system, called The Turing test, is also defined and detailed. Afterwards, we describe some AI tools such

BACKGROUND: Because of ageing populations, the growth in the number of people with multi-morbidity and greater compliance with disease-specific guidelines, polypharmacy is becoming increasingly common. Although the correct drug treatment in patients with complex medical problems can improve clinical outcomes, quality of life and life expectancy, polypharmacy is also associated with an increased risk of adverse drug events, some severe enough to result in hospital admission and even death. Hence,

Hip Osteoarthritis (OA) is a common disease among the middle-aged and elderly people. Conventionally, hip OA is diagnosed by manually assessing X-ray images. This study took the hip joint as the object of observation and explored the diagnostic value of deep learning in hip osteoarthritis. A deep convolutional neural network (CNN) was trained and tested on 420 hip X-ray images to automatically diagnose hip OA. This CNN model achieved a balance of high sensitivity of 95.0% and high specificity of

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environme

The recent surge in interest in ethics in artificial intelligence (AI) may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be AI practitioners, but also to understand the moral, ethical, and philosophical impacts that AI will have on society. In this article we provide practical case studies and links to resources for use by AI educators. We also provide con