Resolving the Chatbot Disclosure Dilemma: Leveraging Selective Self-Presentation to Mitigate the Negative Effect of Chatbot Disclosure

Chatbots are increasingly able to pose as humans. However, this does not hold true if their identity is explicitly disclosed to users—a practice that will become a legal obligation for many service providers in the imminent future. Previous studies hint at a chatbot disclosure dilemma in that disclosing the non-human identity of chatbots comes at the cost of negative user responses. As these responses are commonly attributed to reduced trust in algorithms, this research examines how the detrimental impact of chatbot disclosure on trust can be buffered. Based on computer-mediated communication theory, the authors demonstrate that the chatbot disclosure dilemma can be resolved if disclosure is paired with selective presentation of the chatbot’s capabilities. Study results show that while merely disclosing (vs. not disclosing) chatbot identity does reduce trust, pairing chatbot disclosure with selectively presented information on the chatbot’s expertise or weaknesses is able to mitigate this negative effect

Internet Science: 5th International Conference, INSCI 2018, St. Petersburg, Russia, October 24–26, 2018, Proceedings

We propose a method for modifying hateful online comments to non-hateful comments without losing the understandability and original meaning of the comments. To accomplish this, we retrieve and classify 301,153 hateful and 1,041,490 non-hateful comments from Facebook and YouTube channels of a large international media organization that is a target of considerable online hate. We supplement this dataset by 10,000 Reddit comments manually labeled for hatefulness. Using these two datasets, we train a neural network to distinguish linguistic patterns. The model we develop, Neural Network Hate Deletion (NNHD), computes how hateful the sentences of a social media comment are and if they are above a given threshold, it deletes them using a language dependency tree. We evaluate the results by comparing crowd workers’ perceptions of hatefulness and understandability before and after transformation and find that our method reduces hatefulness without resulting in a significant loss of understandability. In some cases, removing hateful elements improves understandability by reducing the linguistic complexity of the comment. In addition, we find that NNHD can satisfactorily retain the original meaning on average but is not perfect in this regard. In terms of practical implications, NNHD could be used in social media platforms to suggest more neutral use of language to agitated online users.</p

Internet Science: 5th International Conference, INSCI 2018, St. Petersburg, Russia, October 24–26, 2018, Proceedings

Social media channels with audiences in the millions are increasingly common. Efforts at segmenting audiences for populations of these sizes can result in hundreds of audience segments, as the compositions of the overall audiences tend to be complex. Although understanding audience segments is important for strategic planning, tactical decision making, and content creation, it is unrealistic for human decision makers to effectively utilize hundreds of audience segments in these tasks. In this research, we present efforts at simplifying the segmentation of audience populations to increase their practical utility. Using millions of interactions with hundreds of thousands of viewers with an organization’s online content collection, we first isolate the maximum number of audience segments, based on behavioral profiling, and then demonstrate a computational approach of using non-negative matrix factorization to reduce this number to 42 segments that are both impactful and representative segments of the overall population. Initial results are promising, and we present avenues for future research leveraging our approach.</p

Anthropomorphized chatbots in mental health applications

The number of people suffering from mental health disorders is steadily rising as a result of growing social and economic inequality, ongoing political conflict, and, not least, the COVID 19 pandemic. The rapid progress of artificial intelligence, and within it chatbots, presents an opportunity to address these deficiencies by reducing treatment barriers and providing economic benefits to service providers and consumers. To assure the effectiveness of chatbots in psychological health applications, they have to be accepted by users. A chatbot’s acceptance in mental health interventions is influenced by the benefits of intelligent machines, their expectation of nonjudgmental and unbiased support, and the effect of stigma on trust and belief in healthcare. Based on these insights, the experimental study examines whether users of psychological health apps more readily accept chatbots as opposed to physical health apps. Furthermore, the humanization of chatbots is a proven tool to enhance the quality of interaction with users. Thus, this dissertation additionally aims to investigate if a humanized chatbot entity affects their acceptance in the context of mental health apps. The results suggest that chatbots are more widely accepted in mental health applications compared to physical health applications. Moreover, the findings lead to the recommendation to implement humanized entities in chatbots within mental health applications. The results provide a rationale for conducting additional research to investigate the subject in greater depth. Due to the continuous development of AI, the utilization of chatbots in mental health care should be investigated continuously.O número de pessoas que sofrem de perturbações de saúde mental está a aumentar constantemente devido à desigualdade social e económica, conflitos políticos e da pandemia de COVID-19. O rápido progresso da inteligência artificial representa uma oportunidade para resolver estas perturbações, reduzindo os obstáculos ao tratamento e proporcionando benefícios económicos aos prestadores de serviços e aos pacientes. Para garantir a eficácia dos chatbots nas aplicações de saúde mental, estes têm de ser aceites pelos utilizadores. Esta aceitação nas intervenções de saúde mental é influenciada pelos benefícios das máquinas inteligentes, pela sua expectativa de apoio imparcial e sem juízos de valor e pelo efeito do estigma na confiança e na crença nos cuidados de saúde. Com base nestes conhecimentos, o estudo experimental examina se os chatbots são mais facilmente aceites pelos utilizadores de aplicações de saúde psicológica do que aplicações de saúde física. Além disso, a humanização dos chatbots é uma ferramenta comprovada para melhorar a qualidade da interacção com os utilizadores. Assim, esta dissertação tem como objetivo investigar se uma entidade chatbot humanizada afeta a sua aceitação no contexto de aplicações de saúde mental. Os resultados sugerem que os chatbots são melhor aceites em aplicações de saúde mental do que em aplicações de saúde física. Além disso, os resultados levam à recomendação da implementação de entidades humanizadas em chatbots dentro de aplicações de saúde mental. Devido ao desenvolvimento contínuo da IA, a utilização de chatbots nos cuidados de saúde mental deve ser investigada numa base contínua

Monimuotoinen ansiotyö

This edited volume discusses multiple job holding as part of Finnish working life. The articles in this book examine this little researched phenomenon through a wide range of empirical data. Based on Statistics Finland's register data, different ways of combining jobs are classified. Interview material sheds light on the conditions for holding multible jobs. A new perspective is provided by the chaos theory of careers. According to the results of the study, very different paths lead to becoming a multiple job holder. The combination of jobs is influenced by the life path and interests of the individual, as well as by constraints and opportunities available. Motives can also be linked to professional networks, decisions made by immediate family, coincidences or whims. This book helps to understand the diversity of ways of working. At the same time, it illustrates the challenges faced by those who work multiple jobs as they try to operate within simpler models and categorisations of labour. It is essential reading for anyone interested in the changing nature of work, especially researchers, students and policy-makers

Monimuotoinen ansiotyö : Näkökulmia monista lähteistä ansaintaan

Tässä kokoomateoksessa käsitellään monimuotoista ansiotyötä osana suomalaista työelämää. Teoksen artikkeleissa tätä vähän tutkittua ilmiötä tarkastellaan monipuolisten empiiristen aineistojen kautta. Tilastokeskuksen rekisteriaineiston pohjalta luokitellaan erilaisia tapoja yhdistää työtä. Haastatteluaineistot puolestaan valottavat yhdistelmätyön tekemisen ehtoja. Uudenlaista näkökulmaa edustaa työurien kaaosteoria. Tutkimustulosten mukaan usean työn tekijäksi päädytään hyvin erilaisia polkuja pitkin. Tehtäväyhdistelmien syntyyn vaikuttavat niin ihmisen elämänkulku ja kiinnostuksen kohteet kuin pakot ja tarjolla olevat mahdollisuudet. Motiivit voivat paikantua myös ammatillisiin verkostoihin, lähipiirin tekemiin ratkaisuihin, suoranaisiin sattumiin tai mielijohteisiin. Teos auttaa ymmärtämään monimuotoisia työnteon tapoja. Samalla se kertoo niistä haasteista, joita useaa työtä tekevät kokevat yrittäessään toimia yksinkertaisempiin työnteon malleihin ja kategorisointeihin perustuvissa kehyksissä. Se on tärkeää luettavaa kaikille työn muutoksesta kiinnostuneille, erityisesti alan tutkijoille, opiskelijoille sekä päätöksentekijöille. Sisällys 1 Mitä tarkoittaa ansainnan koostaminen useasta lähteestä? / Arja Haapakorpi, Anu Järvensivu, Merja Kauhanen ja Harri Melin 2 Työn muuttuvat maailmat / Harri Melin 3 Monimuotoisen ansiotyön tekeminen rekisteriaineistojen valossa / Merja Kauhanen 4 Jälkiteollinen yhteiskunta ja monista lähteistä ansainta: Tehtäväyhdistelmät ja tausta erilaisissa ammattiryhmissä / Arja Haapakorpi 5 Kaaosteoreettinen kuva usean työn tekemisestä / Anu Järvensivu 6 Monista lähteistä ansainta, muuttuva työelämä ja yhteiskuntapolitiikan haasteet / Arja Haapakorpi, Anu Järvensivu, Merja Kauhanen ja Harri Melin Liite: Chattibotti tutkimushaastattelijana / Anu JärvensivuThis edited collection discusses multiple job holding as part of Finnish working life. The articles in this book examine this little researched phenomenon through a wide range of empirical data. Based on Statistics Finland's register data, different ways of combining jobs are classified. Interview material sheds light on the conditions for holding multible jobs. A new perspective is provided by the chaos theory of careers. According to the results of the study, very different paths lead to becoming a multiple job holder. The combination of jobs is influenced by the life path and interests of the individual, as well as by constraints and opportunities available. Motives can also be linked to professional networks, decisions made by immediate family, coincidences or whims. This book helps to understand the diversity of ways of working. At the same time, it illustrates the challenges faced by those who work multiple jobs as they try to operate within simpler models and categorisations of labour. It is essential reading for anyone interested in the changing nature of work, especially researchers, students and policy-makers

Monimuotoinen ansiotyö

This edited volume discusses multiple job holding as part of Finnish working life. The articles in this book examine this little researched phenomenon through a wide range of empirical data. Based on Statistics Finland's register data, different ways of combining jobs are classified. Interview material sheds light on the conditions for holding multible jobs. A new perspective is provided by the chaos theory of careers. According to the results of the study, very different paths lead to becoming a multiple job holder. The combination of jobs is influenced by the life path and interests of the individual, as well as by constraints and opportunities available. Motives can also be linked to professional networks, decisions made by immediate family, coincidences or whims. This book helps to understand the diversity of ways of working. At the same time, it illustrates the challenges faced by those who work multiple jobs as they try to operate within simpler models and categorisations of labour. It is essential reading for anyone interested in the changing nature of work, especially researchers, students and policy-makers