340 research outputs found
In private, secure, conversational FinBots we trust
In the past decade, the financial industry has experienced a technology
revolution. While we witness a rapid introduction of conversational bots for
financial services, there is a lack of understanding of conversational user
interfaces (CUI) features in this domain. The finance industry also deals with
highly sensitive information and monetary transactions, presenting a challenge
for developers and financial providers. Through a study on how to design
text-based conversational financial interfaces with N=410 participants, we
outline user requirements of trustworthy CUI design for financial bots. We
posit that, in the context of Finance, bot privacy and security assurances
outweigh conversational capability and postulate implications of these
findings. This work acts as a resource on how to design trustworthy FinBots and
demonstrates how automated financial advisors can be transformed into trusted
everyday devices, capable of supporting users' daily financial activities.Comment: Proceedings of the CHI 2021 Workshop on Let's Talk About CUIs:
Putting Conversational User Interface Design into Practice, May 8, 2021 in
Yokohama, Japa
Multi-Purpose NLP Chatbot : Design, Methodology & Conclusion
With a major focus on its history, difficulties, and promise, this research
paper provides a thorough analysis of the chatbot technology environment as it
exists today. It provides a very flexible chatbot system that makes use of
reinforcement learning strategies to improve user interactions and
conversational experiences. Additionally, this system makes use of sentiment
analysis and natural language processing to determine user moods. The chatbot
is a valuable tool across many fields thanks to its amazing characteristics,
which include voice-to-voice conversation, multilingual support [12], advising
skills, offline functioning, and quick help features. The complexity of chatbot
technology development is also explored in this study, along with the causes
that have propelled these developments and their far-reaching effects on a
range of sectors. According to the study, three crucial elements are crucial:
1) Even without explicit profile information, the chatbot system is built to
adeptly understand unique consumer preferences and fluctuating satisfaction
levels. With the use of this capacity, user interactions are made to meet their
wants and preferences. 2) Using a complex method that interlaces Multiview
voice chat information, the chatbot may precisely simulate users' actual
experiences. This aids in developing more genuine and interesting discussions.
3) The study presents an original method for improving the black-box deep
learning models' capacity for prediction. This improvement is made possible by
introducing dynamic satisfaction measurements that are theory-driven, which
leads to more precise forecasts of consumer reaction.Comment: Multilingual , Voice Conversion , Emotion Recognition , Offline
Service , Financial Advisor , Product Preference , Customer Reaction
Predictio
Trust in Digital Humans
With technology advances, the interaction between organisations and consumers is evolving gradually from ‘human-to-human’ to ‘human-to-machine’, due, in part, to improvements in Artificial Intelligence (AI). One such technology, the AI-enabled digital human is unique in its combining of technology and humanness and is being adopted by firms to support customer services and other business processes. However, a number of questions arise with this new way of interacting, among which is whether people will trust a digital human in the same way that they trust people. To address this question, this study draws on technology trust theory, and examines the roles of social presence, anthropomorphism, and privacy to understand trust and people’s readiness to engage with digital humans. The results aim to benefit organisations wanting to implement AI-enabled digital-humans in the workplace
Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions
Chatbots are capable of remembering and referencing previous conversations,
but does this enhance user engagement or infringe on privacy? To explore this
trade-off, we investigated the format of how a chatbot references previous
conversations with a user and its effects on a user's perceptions and privacy
concerns. In a three-week longitudinal between-subjects study, 169 participants
talked about their dental flossing habits to a chatbot that either, (1-None):
did not explicitly reference previous user utterances, (2-Verbatim): referenced
previous utterances verbatim, or (3-Paraphrase): used paraphrases to reference
previous utterances. Participants perceived Verbatim and Paraphrase chatbots as
more intelligent and engaging. However, the Verbatim chatbot also raised
privacy concerns with participants. To gain insights as to why people prefer
certain conditions or had privacy concerns, we conducted semi-structured
interviews with 15 participants. We discuss implications from our findings that
can help designers choose an appropriate format to reference previous user
utterances and inform in the design of longitudinal dialogue scripting.Comment: 10 pages, 3 figures, to be published in Proceedings of the 11th
International Conference on Human-Agent Interaction (ACM HAI'23
Investigating the factors of customer experiences using real-life text-based banking chatbot: a qualitative study in Norway
In recent times, banks have increasingly started using chatbots to offer round-the-clock customer service. However, customers experience with this type of technology is not well understood. The aim of this study was to get an in-depth understanding of factors affecting customer experience with a banking chatbot. Eight participants interacted with a real-life banking chatbot to complete a simple task (order a credit/debit card) and a complex task (apply for a housing loan). Semi-structured interviews were then conducted to examine chatbot-related factors (ease of use, miscommunication errors and human-likeness) and user-related factors (perceptions, future behaviors). The findings indicate that the human-like factors like a human personality, use of emojis, willingness to help, and polite communication style, have a positive impact of customer experience with banking chatbots. The chatbot's ability to understand questions was a critical factor. Miscommunication errors have negative impact, especially when the task is a simple one. Takeaway from this study is that banks should inform customers about the limits of the chatbot's abilities. In addition, they should communicate that the chatbot is safe to use for complex tasks. Successful development and implementation of chatbots for customer service require a customer centric approach from banks.publishedVersio
Using and Interacting with AI-Based Intelligent Technologies: Practical Applications on Autonomous Cars and Chatbots
L'intelligence artificielle (IA) est souvent considérée comme l'une des innovations les plus prometteuses et perturbatrices de notre époque. Malgré son développement rapide, il existe encore un haut niveau d'incertitude quant à la manière dont les consommateurs vont adopter l'IA. Dans ce contexte, cette thèse de quatre articles vise à comprendre comment les consommateurs utilisent et interagissent avec les technologies intelligentes, en se concentrant en particulier sur deux applications: les chatbots et les véhicules autonomes (VA). Dans un premier temps, nous effectuons une analyse approfondie de la littérature marketing existante en adoptant les approches scientométriques et la méthode Theory-Context-Characteristics-Methodology. Ainsi, nous définissons nos questions de recherche concernant 1) les réactions cognitives et émotionnelles des consommateurs lorsqu'ils interagissent avec des technologies basées sur l'IA capables de simuler des conversations de type humain ; 2) les facteurs affectant l'intention des consommateurs d'utiliser des technologies basées sur l'IA, et leur évolution à travers les niveaux d'automatisation ; 3) les préoccupations éthiques des consommateurs envers les produits IA et leur effet sur la confiance et les intentions d'utilisation. En mettant en œuvre trois plans expérimentaux inter-sujets, nous répondons à notre première question de recherche en comparant les interactions humain-humain et humain-chatbot et les interactions avec des chatbots hautement anthropomorphes et faiblement anthropomorphes. Nous nous appuyons principalement sur la Théorie de l'Evaluation Cognitive des Emotions (Roseman et al. 1990), la Théorie de l'Attribution (Weiner 2000) et la Théorie de l'Anthropomorphisme (Aggarwal and McGill 2007 ; Epley et al. 2018), en montrant que les réponses des consommateurs diffèrent lorsqu'ils interagissent avec un humain et un chatbot, en fonction des différentes attributions de responsabilité et des différents niveaux d'anthropomorphisme. Ensuite, nous étudions la manière dont l'expérience des consommateurs avec différents niveaux d'automatisation affecte les perceptions des technologies basées sur l'IA. Nous utilisons les VA comme unité d'analyse, en intégrant le cadre UTAUT avec la Théorie de la Confiance (Mcknight et al. 2011), la Théorie du Calcul de la Vie Privée (Dinev et Hart 2006) et la Théorie du Bien-être (Diener 1999). Après la mise en œuvre d'un design intra-sujet avec des études sur le terrain et sur simulateur, les résultats suggèrent que la différenciation entre les différents niveaux d'automatisation joue un rôle clé pour mieux comprendre les facteurs d’adoption ainsi que les réactions cognitives lors de l'utilisation d'applications intelligentes. Enfin, nous étudions les préoccupations éthiques des consommateurs concernant les chatbots et les VA. Nous utilisons une approche mixte, en utilisant la modélisation thématique et la modélisation par équation structurelle. Nous montrons que pour les chatbots, la composante interactionnelle et émotionnelle de la technologie est prédominante, les consommateurs soulignant, entre autres, le design émotionnel et le manque d'adaptabilité comme principaux soucis éthiques. En revanche, pour les VA, les préoccupations éthiques concernent plutôt des perceptions cognitives liées à la transparence des algorithmes, à la sécurité de la technologie et à l'accessibilité. Notre recherche offre des contributions à la littérature émergente sur les comportements des consommateurs liés aux produits intelligents en soulignant la nécessité de prendre en compte la complexité des technologies d'IA à travers leurs différents niveaux d'automatisation et en fonction de leurs caractéristiques. Nous offrons également des contributions méthodologiques grâce à la mise en œuvre de plans de recherche expérimentaux innovants, utilisant des outils avancés et combinant des approches qualitatives et quantitatives. […]Artificial Intelligence (AI) is often considered as one of the most promising and disruptive innovation of our times. Despite its rapid development, there is still a high level of uncertainty about how consumers are going to adopt AI. In this context, this four-article dissertation aims to comprehend how consumers use and interact with intelligent technologies, in particular focusing on two current applications: chatbots and autonomous vehicles (AVs). First, we conduct an in-depth analysis of the existing marketing literature adopting Scientometric and Theory-Context-Characteristics-Methodology approaches. Thus, we define our research questions related to 1) consumers ‘cognitive and emotional reactions when interacting with AI-based technologies that are able to simulate human-like conversations; 2) factors affecting consumers ‘intention to use AI-based technologies able to make decision in critical situations, and their evolution across levels of automation; 3) consumers ethical concerns towards AI products and their effect on trust and usage intentions. By applying three between-subject experimental designs, we answer our first research question comparing human–human versus human–chatbot interactions and highly anthropomorphic versus lowly anthropomorphic chatbots. We leverage insights mainly from Cognitive Appraisal Theory of Emotions (Roseman et al. 1990), Attribution Theory (Weiner 2000) and Theory of Anthropomorphism (Aggarwal and McGill 2007; Epley et al. 2018), showing that consumers’ responses differ when interacting with a human and a chatbot, according to the different attributions of responsibility and the different levels of anthropomorphism of the service agent. Next, we investigate the way consumers’ experience with different levels of automation affect perceptions of AI-based technologies. We use AVs as unit of analysis, integrating the UTAUT framework with Trust Theory (Mcknight et al. 2011), Privacy Calculus Theory (Dinev and Hart 2006) and Theory of Well-being (Diener 1999; Diener and Chan 2011). After implementing a within subject-design with field and simulator studies, results suggest that differentiating between the different automation levels play a key role to better understand the potential drivers of adoption as well as the cognitive reactions when using intelligent applications. Finally, we investigate consumers’ ethical concerns surrounding chatbots and AVs. We employ a mixed methods approach, using topic modeling and structural equation modeling. We show that for chatbots, the interactional and emotional component of the technology is predominant, as consumers highlight, between others, the emotional design and the lack of adaptability as main ethical issues. However, for autonomous cars, the ethical concerns rather involve cognitive perceptions related to the transparency of the algorithms, the ethical design, the safety of the technology and the accessibility. Our research offers contributions to the emerging literature on consumer behaviors related to intelligent products by highlighting the need to take into account the complexity of AI technologies across their different levels of automation and according to their intrinsic characteristics. We also offer methodological contributions thanks to the implementation of innovative experimental research designs, using advanced tools and combining qualitative and quantitative approaches. To conclude, we present implications for both managers and policymakers who want to implement AIbased disruptive technologies, such as chatbots and AVs
Adoption state of artificial intelligence: a saas perspective
The following thesis will focus on the general topic of Artificial Intelligence (AI). The main
purpose of this work is to investigate how generally AI is being implemented and developed in
modern times. Artificial Intelligence is critical in the SaaS industry. The study aims to get an
overview of the state of adoption of Artificial Intelligence with particular attention to how it is
in the SaaS industry and what it may indicate for the future. The author compares secondary
data analysis with interviews of SaaS experts to better understand of how the SaaS industry
differentiates from the general market
Inclusion in Virtual Reality Technology: A Scoping Review
Despite the significant growth in virtual reality applications and research,
the notion of inclusion in virtual reality is not well studied. Inclusion
refers to the active involvement of different groups of people in the adoption,
use, design, and development of VR technology and applications. In this review,
we provide a scoping analysis of existing virtual reality research literature
about inclusion. We categorize the literature based on target group into
ability, gender, and age, followed by those that study community-based design
of VR experiences. In the latter group, we focus mainly on Indigenous Peoples
as a clearer and more important example. We also briefly review the approaches
to model and consider the role of users in technology adoption and design as a
background for inclusion studies. We identify a series of generic barriers and
research gaps and some specific ones for each group, resulting in suggested
directions for future research
Open Problems in DAOs
Decentralized autonomous organizations (DAOs) are a new, rapidly-growing
class of organizations governed by smart contracts. Here we describe how
researchers can contribute to the emerging science of DAOs and other
digitally-constituted organizations. From granular privacy primitives to
mechanism designs to model laws, we identify high-impact problems in the DAO
ecosystem where existing gaps might be tackled through a new data set or by
applying tools and ideas from existing research fields such as political
science, computer science, economics, law, and organizational science. Our
recommendations encompass exciting research questions as well as promising
business opportunities. We call on the wider research community to join the
global effort to invent the next generation of organizations
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