Chasing the Chatbots: Directions for Interaction and Design Research

Big tech-players have been successful in pushing the chatbots forward. Investments in the technology are growing fast, as well as the number of users and applications available. Instead of driving investments towards a successful diffusion of the technology, user-centred studies are currently chasing the popularity of chatbots. A literature analysis evidences how recent this research topic is, and the predominance of technical challenges rather than understanding users’ perceptions, expectations and contexts of use. Looking for answers to interaction and design questions raised in 2007, when the presence of clever computers in everyday life had been predicted for the year 2020, this paper presents a panorama of the recent literature, revealing gaps and pointing directions for further user-centred research

Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking

© IFIP International Federation for Information Processing 2019. Trustworthy Machine Learning (ML) is one of significant challenges of “black-box” ML for its wide impact on practical applications. This paper investigates the effects of presentation of influence of training data points on machine learning predictions to boost user trust. A framework of fact-checking for boosting user trust is proposed in a predictive decision making scenario to allow users to interactively check the training data points with different influences on the prediction by using parallel coordinates based visualization. This work also investigates the feasibility of physiological signals such as Galvanic Skin Response (GSR) and Blood Volume Pulse (BVP) as indicators for user trust in predictive decision making. A user study found that the presentation of influences of training data points significantly increases the user trust in predictions, but only for training data points with higher influence values under the high model performance condition, where users can justify their actions with more similar facts to the testing data point. The physiological signal analysis showed that GSR and BVP features correlate to user trust under different influence and model performance conditions. These findings suggest that physiological indicators can be integrated into the user interface of AI applications to automatically communicate user trust variations in predictive decision making

To respond or not to respond - a personal perspective of intestinal tolerance

For many years, the intestine was one of the poor relations of the immunology world, being a realm inhabited mostly by specialists and those interested in unusual phenomena. However, this has changed dramatically in recent years with the realization of how important the microbiota is in shaping immune function throughout the body, and almost every major immunology institution now includes the intestine as an area of interest. One of the most important aspects of the intestinal immune system is how it discriminates carefully between harmless and harmful antigens, in particular, its ability to generate active tolerance to materials such as commensal bacteria and food proteins. This phenomenon has been recognized for more than 100 years, and it is essential for preventing inflammatory disease in the intestine, but its basis remains enigmatic. Here, I discuss the progress that has been made in understanding oral tolerance during my 40 years in the field and highlight the topics that will be the focus of future research

Gender differences in the associations between age trends of social media interaction and well-being among 10-15 year olds in the UK

Background Adolescents are among the highest consumers of social media while research has shown that their well-being decreases with age. The temporal relationship between social media interaction and well-being is not well established. The aim of this study was to examine whether the changes in social media interaction and two well-being measures are related across ages using parallel growth models. Methods Data come from five waves of the youth questionnaire, 10-15 years, of the Understanding Society, the UK Household Longitudinal Study (pooled n =9859). Social media interaction was assessed through daily frequency of chatting on social websites. Well-being was measured by happiness with six domains of life and the Strengths and Difficulties Questionnaire. Results Findings suggest gender differences in the relationship between interacting on social media and well-being. There were significant correlations between interacting on social media and well-being intercepts and between social media interaction and well-being slopes among females. Additionally higher social media interaction at age 10 was associated with declines in well-being thereafter for females, but not for males. Results were similar for both measures of well-being. Conclusions High levels of social media interaction in early adolescence have implications for well-being in later adolescence, particularly for females. The lack of an association among males suggests other factors might be associated with their reduction in well-being with age. These findings contribute to the debate on causality and may inform future policy and interventions

The Role of Purported Mucoprotectants in Dealing with Irritable Bowel Syndrome, Functional Diarrhea, and Other Chronic Diarrheal Disorders in Adults

Chronic diarrhea is a frequent presenting symptom, both in primary care medicine and in specialized gastroenterology units. It is estimated that more than 5% of the global population suffers from chronic diarrhea. and that about 40% of these subjects are older than 60 years. The clinician is frequently faced with the need to decide which is the best therapeutic approach for these patients. While the origin of chronic diarrhea is diverse, impairment of intestinal barrier function, dysbiosis. and mucosal micro-inflammation are being increasingly recognized as underlying phenomena characterizing a variety of chronic diarrheal diseases. In addition to current pharmacological therapies, there is growing interest in alternative products such as mucoprotectants, which form a mucoadhesive film over the epithelium to reduce and protect against the development of altered intestinal permeability, dysbiosis, and mucosal micro-inflammation. This manuscript focuses on chronic diarrhea in adults, and we will review recent evidence on the ability of these natural compounds to improve symptoms associated with chronic diarrhea and to exert protective effects for the intestinal barrier

Why People Use Chatbots

There is a growing interest in chatbots, which are machine agents serving as natural language user interfaces for data and service providers. However, no studies have empirically investigated people’s motivations for using chatbots. In this study, an online questionnaire asked chatbot users (N = 146, aged 16–55 years) from the US to report their reasons for using chatbots. The study identifies key motivational factors driving chatbot use. The most frequently reported motivational factor is “productivity”; chatbots help users to obtain timely and efficient assistance or information. Chatbot users also reported motivations pertaining to entertainment, social and relational factors, and curiosity about what they view as a novel phenomenon. The findings are discussed in terms of the uses and gratifications theory, and they provide insight into why people choose to interact with automated agents online. The findings can help developers facilitate better human–chatbot interaction experiences in the future. Possible design guidelines are suggested, reflecting different chatbot user motivations.acceptedVersio

Different Chatbots for Different Purposes: Towards a Typology of Chatbots to Understand Interaction Design

Chatbots are emerging as interactive systems. However, we lack knowledge on how to classify chatbots and how such classification can be brought to bear in analysis of chatbot interaction design. In this workshop paper, we propose a typology of chatbots to support such classification and analysis. The typology dimensions address key characteristics that differentiate current chatbots: the duration of the user's relation with the chatbot (short-term and long-term), and the locus of control for user's interaction with the chatbot (user-driven and chatbot-driven). To explore the usefulness of the typology, we present four example chatbot purposes for which the typology may support analysis of high-level chatbot interaction design. Furthermore, we analyse a sample of 57 chatbots according to the typology dimensions. The relevance and application of the typology for developers and service providers are discussed

Adapting a Conversational Text Generator for Online Chatbot Messaging

Conversational interfaces and chatbots have a long history, but have only recently been hyped as a disruptive technology ready to replace mobile apps and Web sites. Many online messaging platforms have introduced support to third-party chatbots, which can be procedurally programmed, but usually rely on a retrieval-based specification language (such as AIML), natural language processing to detect the user's intent, or on machine learning. In this work we present a work-in-progress integration of a widely-used system for story generation, the Tracery grammar, a conversational agent design tool, the Bottery system, and online messaging platforms. The proposed system provides a complete and easy-to-use system that allows the creation of chatbots with a graph-based dialogue structure, a contextual memory, pattern-based text matching, and advanced text generation capabilities, that aims for being well-suited for experts and technically unskilled authors alike. Features of the system and future additions are discussed and compared to existing solutions

All Citizens are the Same, Aren’t They? – Developing an E-government User Typology

Part 6: Open GovernmentInternational audienceTaking a closer look at current research on e-government diffusion shows that most studies or conceptual works deal with citizens as one broad mass that is not further described or divided into smaller subgroups. Such efforts are mainly limited to the digital divide discourse and distinguish at most between haves and have-nots or younger and older parts of the population. Understanding why and how citizens use public online services also requires an understanding of how different segments of the population react to IT in general as well as to e-government in particular. To date, no meaningful attempts to develop such an e-government user typology have been undertaken. Therefore, the study at hand aims at developing a user typology for the e-government context. To this end, we chose an explorative design and conducted a qualitative interview study in Germany in 2016 with 18 respondents from all age groups. We qualitatively analyzed the sample regarding usage behavior, variety of use, and e-government specific uses and perceptions. Our research reveals six user types differing in quality and quantity of use with regard to internet-based technologies in general and e-government services in particular. Understanding how different populations perceive e-government and contextualizing their behavior can help explaining why some citizens are making advanced use of e-government while others widely ignore these services