AI ethics in January 2018

Deep Learning and Big Data analytics are two focal points of data science. Deep Learning models have achieved remarkable results in speech recognition and computer vision in recent years. Big Data is important for organizations that need to collect a huge amount of data like a social network and one of the greatest assets to use Deep Learning is analyzing a massive amount of data (Big Data). This advantage makes Deep Learning as a valuable tool for Big Data. Deep Learning can be used to extract

This article synthesizes foundational knowledge from multiple scientific disciplines regarding how humans develop in context. Major constructs that define human development are integrated into a developmental system framework, this includes—epigenetics, neural malleability and plasticity, integrated complex skill development and learning, human variability, relationships and attachment, self-regulation, science of learning, and dynamics of stress, adversity and resilience. Specific attention is

The implementation of Industry 4.0 has a far-reaching impact on industrial value creation. Studies on its opportunities and challenges for companies are still scarce. However, the high practical and theoretical relevance of digital and connected manufacturing technologies implies that it is essential to understand the underlying dynamics of their implementation. Thus, this study examines the relevance of Industry 4.0-related opportunities and challenges as drivers for Industry 4.0 implementation

The present study introduces eight comic styles (i.e., fun, humor, nonsense, wit, irony, satire, sarcasm, and cynicism) and examines the validity of a set of 48 marker items for their assessment, the Comic Style Markers (CSM). These styles were originally developed to describe literary work and are used here to describe individual differences. Study 1 examines whether the eight styles can be distinguished empirically, in self- and other-reports, and in two languages. In different samples of alto

In recent years there has been increased attention on the possible impact of future robotics and AI systems. Prominent thinkers have publicly warned about the risk of a dystopian future when the complexity of these systems progresses further. These warnings stand in contrast to the current state-of-the-art of the robotics and AI-technology. This article reviews work considering both the future potential of robotics and AI systems, and ethical considerations that need to be taken in order to avoi

Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, i.e., analyzing changes in pupil size relative to a baseline period. Baseline correction is useful in experiments that investigate the effect of some experimental manipulation on pupil size. In such experiments, baseline correction improves statistical po

Abstract Data mining techniques have been concentrated for malware detection in the recent decade. The battle between security analyzers and malware scholars is everlasting as innovation grows. The proposed methodologies are not adequate while evolutionary and complex nature of malware is changing quickly and therefore turn out to be harder to recognize. This paper presents a systematic and detailed survey of the malware detection mechanisms using data mining techniques. In addition, it classifi

Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultura

Big data has fundamentally changed the way organizations manage, analyze and leverage data in any industry. One of the most promising fields where big data can be applied to make a change is healthcare. Big healthcare data has considerable potential to improve patient outcomes, predict outbreaks of epidemics, gain valuable insights, avoid preventable diseases, reduce the cost of healthcare delivery and improve the quality of life in general. However, deciding on the allowable uses of data while

BACKGROUND: Drivers of change in dairy herd health management include the significant increase in herd/farm size, quota removal (within Europe) and the increase in technologies to aid in dairy cow reproductive management. MAIN BODY: There are a number of key areas for improving fertility management these include: i) handling of substantial volumes of data, ii) genetic selection (including improved phenotypes for use in breeding programmes), iii) nutritional management (including transition cow m

BACKGROUND: The goal of this exploratory study was to develop and assess a prediction model which can potentially be used as a biomarker of breast cancer, based on anthropometric data and parameters which can be gathered in routine blood analysis. METHODS: For each of the 166 participants several clinical features were observed or measured, including age, BMI, Glucose, Insulin, HOMA, Leptin, Adiponectin, Resistin and MCP-1. Machine learning algorithms (logistic regression, random forests, suppor

Harmful lies are nothing new. But the ability to distort reality has taken an exponential leap forward with “deep fake” technology. This capability makes it possible to create audio and video of real people saying and doing things they never said or did. Machine learning techniques are escalating the technology’s sophistication, making deep fakes ever more realistic and increasingly resistant to detection. Deep-fake technology has characteristics that enable rapid and widespread diffusion, putti

Driverless cars with artificial intelligence (AI) and automated supermarkets run by collaborative robots (cobots) working without human supervision have sparked off new debates: what will be the impacts of extreme automation, turbocharged by the Internet of Things (IoT), AI, and the Industry 4.0, on Big Data and omics implementation science? The IoT builds on (1) broadband wireless internet connectivity, (2) miniaturized sensors embedded in animate and inanimate objects ranging from the house ca

Greenhouse cultivation has evolved from simple covered rows of open-fields crops to highly sophisticated controlled environment agriculture (CEA) facilities that projected the image of plant factories for urban agriculture. The advances and improvements in CEA have promoted the scientific solutions for the efficient production of plants in populated cities and multi-story buildings. Successful deployment of CEA for urban agriculture requires many components and subsystems, as well as the underst

This collection examines how higher education responds to the demands of the automation economy and the fourth industrial revolution.

Automatic machine learning systems can inadvertently accentuate and perpetuate inappropriate human biases. Past work on examining inappropriate biases has largely focused on just individual systems. Further, there is no benchmark dataset for examining inappropriate biases in systems. Here for the first time, we present the Equity Evaluation Corpus (EEC), which consists of 8,640 English sentences carefully chosen to tease out biases towards certain races and genders. We use the dataset to examine

Technological advances have resulted in organizations digitalizing many parts of their operations. The threat landscape of cyberattacks is rapidly changing and the potential impact of such attacks is uncertain, because there is a lack of effective metrics, tools and frameworks to understand and assess the harm organizations face from cyber-attacks. In this article, we reflect on the literature on harm, and how it has been conceptualized in disciplines such as criminology and economics, and inves

In January 2018, the European Commission set up a highlevel group of experts («the HLEG») to advise on policy initiatives to counter fake news and disinformation spread online. The HLEG consisted of 39 members and was chaired by Prof. Dr. Madeleine de Cock Buning. Its members had different backgrounds, including academia and journalism, written press and broadcasting organizations, online platforms as well as civil society and fact-checking organizations. The HLEG’s tasks were to advise the Comm

Pereira, L. M., T. Hichert, M. Hamann, R. Preiser, and R. Biggs. 2018. Using futures methods to create transformative spaces: visions of a good Anthropocene in southern Africa. Ecology and Society 23(1):19. https://doi.org/10.5751/ES-09907-230119

Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, Philip Resnik. Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic. 2018.

Computational models are increasingly being used to assist in developing, implementing and evaluating public policy. This paper reports on the experience of the authors in designing and using computational models of public policy ('policy models', for short). The paper considers the role of computational models in policy making, and some of the challenges that need to be overcome if policy models are to make an e ective contribution. It suggests that policy models can have an important place in

This paper summarizes a panel discussion at the 15th International Conference on Business Process Management. The panel discussed to what extent the emergence of recent technologies including machine learning, robotic process automation, and blockchain will reduce the human factor in business process management. The panel discussion took place on 14 September, 2017, at the Universitat Politècnica de Catalunya in Barcelona, Spain. Jan Mendling served as a chair; Gero Decker, Richard Hull, Hajo Re

It has often been suggested in the popular and academic literature that the psychedelic state qualifies as a higher state of consciousness relative to the state of normal waking awareness. This article subjects this proposal to critical scrutiny, focusing on the question of what it would mean for a state of consciousness to be 'higher'. We begin by considering the contrast between conscious contents and conscious global states. We then review the changes in conscious global state associated with