AI ethics in January 2017

The digital revolution in medicine not only offers exciting new directions for the treatment of mental illness, but also presents challenges to patient privacy and security. Changes in medicine are part of the complex digital economy based on creating value from analysis of behavioral data acquired by the tracking of daily digital activities. Without an understanding of the digital economy, recommending the use of technology to patients with mental illness can inadvertently lead to harm. Behavio

Abstract Natural language processing (NLP) techniques can be used to make inferences about peoples’ mental states from what they write on Facebook, Twitter and other social media. These inferences can then be used to create online pathways to direct people to health information and assistance and also to generate personalized interventions. Regrettably, the computational methods used to collect, process and utilize online writing data, as well as the evaluations of these techniques, are still di

In this paper, we document basic facts regarding public debates about controversial political issues on Chinese social media. Our documentation is based on a dataset of 13.2 billion blog posts published on Sina Weibo—the most prominent Chinese microblogging platform—during the 2009–2013 period. Our primary finding is that a shockingly large number of posts on highly sensitive topics were published and circulated on social media. For instance, we find millions of posts discussing protests, and th

OBJECTIVES: Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer's disease (AD) and dementia portrayal on Twitter to demonstrate its use. The approach improves feasibility of examining large publicly available datasets. METHOD: Machine learning techniques modeled stigmatization expressed in 31,150 AD-related twee

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural netw

Since industrial trade fair Hannover Messe 2011, the term "Industrie 4.0" has ignited a vision of a new Industrial Revolution and has been inspiring a lively, ongoing debate among the German public about the future of work, and hence society, ever since. The discourse around this vision of the future eventually spread to other countries, with public awareness reaching a temporary peak in 2016 when the World Economic Forum's meeting in Davos was held with the motto "Mastering the Fourth Industria

The popularity of social media and computer-mediated communication has resulted in high-volume and highly semantic data about digital social interactions. This constantly accumulating data has been termed as Big Social Data or Social Big Data, and various visions about how to utilize that have been presented. However, as relatively new concepts, there are no solid and commonly agreed definitions of them. We argue that the emerging research field around these concepts would benefit from understan

Abstract Futurists predict that a third of jobs that exist today could be taken by Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA) by 2025. However, very little is known about how employees perceive these technological advancements in regards to their own jobs and careers, and how they are preparing for these potential changes. A new measure (STARA awareness) was created for this study that captures the extent to which employees feel their job could be replaced by the

BACKGROUND: Biclustering techniques are capable of simultaneously clustering rows and columns of a data matrix. These techniques became very popular for the analysis of gene expression data, since a gene can take part of multiple biological pathways which in turn can be active only under specific experimental conditions. Several biclustering algorithms have been developed in the past recent years. In order to provide guidance regarding their choice, a few comparative studies were conducted and r

BACKGROUND: The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and theref

A casual comment by a student alerted the authors to the existence and prevalence of Internet-based paraphrasing tools. A subsequent quick Google search highlighted the broad range and availability of online paraphrasing tools which offer free ‘services’ to paraphrase large sections of text ranging from sentences, paragraphs, whole articles, book chapters or previously written assignments. The ease of access to online paraphrasing tools provides the potential for students to submit work they hav

BACKGROUND: With the expected increase in the numbers of persons with dementia, providing timely, adequate, and affordable care and support is challenging. Assistive and health technologies may be a valuable contribution in dementia care, but new challenges may emerge. OBJECTIVE: The aim of our study was to review the state of the art of technologies for persons with dementia regarding issues on development, usability, effectiveness and cost-effectiveness, deployment, and ethics in 3 fields of a

BACKGROUND: The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from verbal utterances could aid diagnosis of patients with probable AD from a large population. For this p

Software-generated news, sometimes called “robot journalism,” has recently given rise to concerns that the automation of news will make journalists redundant. These arguments follow a deterministic line of thinking. Algorithms choose information for users but are also the construct of social process and practice. The aim of this essay is to explore “the algorithmic turn” (Napoli, 2014) in news production. Based on case studies from three separate news outlets it is found that the impact of autom

BACKGROUND: The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models. METHODS AND FINDING: We conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of morta

Domestic chickens are members of an order, Aves, which has been the focus of a revolution in our understanding of neuroanatomical, cognitive, and social complexity. At least some birds are now known to be on par with many mammals in terms of their level of intelligence, emotional sophistication, and social interaction. Yet, views of chickens have largely remained unrevised by this new evidence. In this paper, I examine the peer-reviewed scientific data on the leading edge of cognition, emotions,

Robots are slowly, but certainly, entering people’s professional and private lives. They require the attention of regulators due to the challenges they present to existing legal frameworks and the new legal and ethical questions they raise. This paper discusses four major regulatory dilemmas in the field of robotics: how to keep up with technological advances; how to strike a balance between stimulating innovation and the protection of fundamental rights and values; whether to affirm prevalent s

Language is increasingly being used to define rich visual recognition problems with supporting image collections sourced from the web. Structured prediction models are used in these tasks to take advantage of correlations between co-occurring labels and visual input but risk inadvertently encoding social biases found in web corpora.

The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly relies on nodule size and nodule type. In this paper, we present a deep learning system based on multi-stream multi-scale convolutional networks, which automatically classifies all nodule types relevan

We have now moved from the early days of the Internet to the Algorithmic Society. The Algorithmic Society features the use of algorithms, artificial intelligence agents, and Big Data to govern populations. It also features digital infrastructure companies, large multi-national social media platforms, and search engines that sit between traditional nation states and ordinary individuals, and serve as special-purpose governors of speech.

Profound global challenges to individual and population health, alongside the opportunities to benefit from digital technology, have spawned the concept of the Learning Health System. Learning Health Systems (LHSs)--which can function at organizational, network, regional, and national levels of scale--have the capability of continuous data-driven self-study that promotes change and improvement. The LHS concept, which originated in the U.S. in 2007, is rapidly gaining attention around the world.

The global seaports are of pivotal importance for the world economy. Since 1990, global container traffic has grown by an average of 10% annually. Equally, the steady growth of ship sizes poses major logistical and technical problems worldwide. Given these facts, shipping and maritime logistics would largely benefit from Big Data as well as the emerging digital technologies. Apart from the many positive effects of digitization in maritime logistics with respect to efficiency, safety and energy s

Henning Wachsmuth, Nona Naderi, Yufang Hou, Yonatan Bilu, Vinodkumar Prabhakaran, Tim Alberdingk Thijm, Graeme Hirst, Benno Stein. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. 2017.

The proliferation of head-mounted displays (HMD) in the market means that cinematic virtual reality (CVR) is an increasingly popular format. We explore several metrics that may indicate advantages and disadvantages of CVR compared to traditional viewing formats such as TV. We explored the consumption of panoramic videos in three different display systems: a HMD, a SurroundVideo+ (SV+), and a standard 16:9 TV. The SV+ display features a TV with projected peripheral content. A between-groups exper

Virtual Reality (VR) technology has been used widely today in Science, Technology, Engineering and Mathematics (STEM) fields. The VR is emerging computer interface distinguished by high degrees of immersion, trustworthy, and interaction. The goal of VR is making the user believe, as much as possible, that he is within the computer-generated environment. The VR has become one of the important technologies to be discussed regarding its applications, usage, and its different types that can achieve

THE USE OF robots in healthcare represents an exciting opportunity to help a large number of people.Robots can be used to enable people with cognitive, sensory, and motor impairments, help people who are ill or injured, support caregivers, and aid the clinical workforce.This article highlights several recent advancements on these fronts, and discusses their impact on stakeholders.It also outlines several key technological, logistical, and design challenges faced in healthcare robot adoption, and