AI ethics in April 2018

With widespread use of machine learning methods in numerous domains involving humans, several studies have raised questions about the potential for unfairness towards certain individuals or groups. A number of recent works have proposed methods to measure and eliminate unfairness from machine learning models. However, most of this work has focused on only one dimension of fair decision making: distributive fairness, i.e., the fairness of the decision outcomes. In this work, we leverage the rich

This paper focuses on the ethical challenges presented by direct-to-consumer (DTC) digital psychotherapy services that do not involve oversight by a professional mental health provider. DTC digital psychotherapy services can potentially assist in improving access to mental health care for the many people who would otherwise not have the resources or ability to connect with a therapist. However, the lack of adequate regulation in this area exacerbates concerns over how safety, privacy, accountabi

Calls for heightened consideration of fairness and accountability in algorithmically-informed public decisions-like taxation, justice, and child protection-are now commonplace. How might designers support such human values? We interviewed 27 public sector machine learning practitioners across 5 OECD countries regarding challenges understanding and imbuing public values into their work. The results suggest a disconnect between organisational and institutional realities, constraints and needs, and

Shape-changing interfaces have emerged as a new method for interacting with computers, using dynamic changes in a device's physical shape for input and output. With the advances of research into shape-changing interfaces, we see a need to synthesize the main, open research questions. The purpose of this synthesis is to formulate common challenges across the diverse fields engaged in shape-change research, to facilitate progression from single prototypes and individual design explorations to gran

Algorithmic systems increasingly shape information people are exposed to as well as influence decisions about employment, finances, and other opportunities. In some cases, algorithmic systems may be more or less favorable to certain groups or individuals, sparking substantial discussion of algorithmic fairness in public policy circles, academia, and the press. We broaden this discussion by exploring how members of potentially affected communities feel about algorithmic fairness. We conducted wor

Given recent technological developments in robotics, artificial intelligence, and virtual reality, it is perhaps unsurprising that the arrival of emotionally expressive and reactive artificial agents is imminent. However, if such agents are to become integrated into our social milieu, it is imperative to establish an understanding of whether and how humans perceive emotion in artificial agents. In this review, we incorporate recent findings from social robotics, virtual reality, psychology, and

A new emerging frontier in the evolution of the digitalisation and the 4 th industrial revolution (Industry 4.0) is considered to be that of "Biologicalisation in Manufacturing". This has been defined by the authors to be "The use and integration of biological and bio-inspired principles, materials, functions, structures and resources for intelligent and sustainable manufacturing technologies and systems with the aim of achieving their full potential." In this White Paper, detailed consideration

The adenoma detection rate is an established quality indicator for colonoscopy. For instance, a 1% increase in the adenoma detection rate was associated with a 3% decrease in interval colorectal cancer incidence.1Corley D.A. Jensen C.D. Marks A.R. et al.Adenoma detection rate and risk of colorectal cancer and death.N Engl J Med. 2014; 370: 1298-1306Crossref PubMed Scopus (1166) Google Scholar However, a previous meta-analysis showed that approximately 26% of neoplastic diminutive polyps were mis

As is common across the public sector, the UK police service is under pressure to do more with less, to target resources more efficiently and take steps to identify threats proactively; for example under risk-assessment schemes such as ‘Clare’s Law’ and ‘Sarah’s Law’. Algorithmic tools promise to improve a police force’s decision-making and prediction abilities by making better use of data (including intelligence), both from inside and outside the force. This article uses Durham Constabulary’s H

While much is known about how Black students negotiate and navigate undergraduate studies, there is a dearth of research on what happens when these students enter graduate school. This article presents the results of a study of 21 Black male graduate students in engineering from one highly ranked research-intensive institution. This article provides evidence of structurally racialized policies within the engineering college (e.g., admissions) and racialized and gendered interactions with peers a

Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the