AI ethics in November 2018

Now that high-end consumer phones can support immersive virtual reality, we ask whether social virtual reality is a promising medium for supporting distributed groups of users. We undertook an exploratory in-the-wild study using Samsung Gear VR headsets to see how existing social groups that had become geographically dispersed could use VR for collaborative activities. The study showed a strong propensity for users to feel present and engaged with group members. Users were able to bring group be

BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access to therapy. We hypothesize that the use of machine learning analysis on home video can speed the diagnosis without compromising accuracy. We have analyzed item-level records from 2 standard diagnostic instruments to construct machine learning classi

Ecological Psychology is an embodied, situated, and non-representational approach pioneered by J. J. Gibson and E. J. Gibson. This theory aims to offer a third way beyond cognitivism and behaviorism for understanding cognition. The theory started with the rejection of the premise of the poverty of the stimulus, the physicalist conception of the stimulus, and the passive character of the perceiver of mainstream theories of perception. On the contrary, the main principles of ecological psychology

This article reports the findings of AI4People, an Atomium-EISMD initiative designed to lay the foundations for a "Good AI Society". We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations-to assess, to develop, to incentivise, and to support good AI-which in some cases may be undertaken directly by national or supranational policy makers, while in oth

Society is increasingly digitalised and connected, with computers and algorithms mediating much of people’s daily activity in one way or another. The degree of digitalisation and its consequences are challenging to understand because most people lack first-hand experience of what digitalisation actually feels like. Digitalisation is abstract and difficult to grasp, which leads to a detached sense of the digital surroundings. In this paper, we argue that in order to grasp the nature and future of

Purpose The last few years have seen a surge of interest in artificial intelligence (AI). The purpose of this paper is to capture a snapshot of perceptions of the potential impact of AI on academic libraries and to reflect on its implications for library work. Design/methodology/approach The data for the study were interviews with 33 library directors, library commentators and experts in education and publishing. Findings Interviewees identified impacts of AI on search and resource discovery, on

This article critically examines how fears of audience gullibility, ignorance, and exploitation impede media studies’ response to the pressing challenges posed by the growing power of social media platforms and their innovative datafication practices. I revisit the history of audience research to show how empirical findings contested the pejorative conception of the audience problematically yet persistently imagined by theorists of media power during the twentieth century. As media studies joins

"Awe" is a category of emotion within the spectrum of self-transcendent experiences. Awe has wellness benefits, with feelings of social interconnectivity and increased life satisfaction. However, awe experiences remain rare in our everyday lives, and rarer in lab environments. We posit that Virtual Reality (VR) may help to make self-transcendent and potentially transformative experiences of awe more accessible to individuals. Here, we investigated how interactive VR as a positive technology may

Abstract Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional

A recent United Kingdom survey reports that 63% of the adult population is uncomfortable with allowing personal data to be used to improve healthcare and is unfavorable to artificial intelligence (AI) systems replacing doctors and nurses in tasks they usually perform Another study, conducted in Germany, found that medical students-the doctors of tomorrow-overwhelmingly buy into the promise of AI to improve medicine (83%) but are more skeptical that it will establish conclusive diagnoses in, for

BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). METHODS: We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical techno

World Economic Forum Founder and Executive Chairman Klaus Schwab offers a practical companion and field guide to his previous book, The Fourth Industrial Revolution. Today, technology is changing everything--how we relate to one another, the way we work, how our economies and goverments function, and even what it means to be human. One need not look hard to see how the incredible advances in artificial intelligence, cryptocurrencies, biotechnologies, and the internet of things are transfor

Since the 1950s, artificial intelligence (AI) has been a recurring topic in research. However, this field has only recently gained significant momentum because of the advances in technology and algorithms, along with new AI techniques such as machine learning methods for structured data, modern deep learning, and natural language processing for unstructured data. Although companies are eager to join the fray of this new AI trend and take advantage of its potential benefits, it is unclear what im

In a majority–minority classification problem, class imbalance in the dataset(s) can dramatically skew the performance of classifiers, introducing a prediction bias for the majority class. Assuming the positive (minority) class is the group of interest and the given application domain dictates that a false negative is much costlier than a false positive, a negative (majority) class prediction bias could have adverse consequences. With big data, the mitigation of class imbalance poses an even gre