Privacy Concerns in Chatbot Interactions

Ischen, Carolin; Araujo, Theo; Voorveld, Hilde A. M.; Noort, Guda van; Smit, Edith G.

doi:10.31235/osf.io/j4dha

Cited by 21 publications

(33 citation statements)

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“…Moreover, creepiness comes under the emotional aspect related to feelings of threat, uncertainty, or discomfort (Langer & König, 2018), possibly related to the threat of personal data being collected and misused (Jackson, 2018). In studying smart products through a resistance approach, Mani and Chouk (2017) found that privacy concerns influence perceptions of intrusiveness.…”

Section: Theoretical Background and Development Of Hypothesesmentioning

confidence: 99%

Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

Rajaobelina

Tep

Arcand

et al. 2021

Psychology and Marketing

119

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Consumers sometimes describe their experience of interacting with artificial intelligence‐based human‐like chatbots as creepy. This study investigates the antecedents of creepiness (i.e., the chatbot's usability, privacy concerns, and user variables such as technology anxiety and the need for human interaction) and its impact on consumer loyalty. Grounded in the technology paradox, it deepens the understanding of creepiness in light of the theoretical underpinnings of the privacy paradox and privacy cynicism. Presented with the task of obtaining a car insurance quote, 430 consumers participated in a simulation involving interaction with a chatbot, followed by a questionnaire. The findings show that creepiness decreases loyalty and indirectly impacts it through trust and negative emotions. While usability reduces perceptions of creepiness, privacy concerns raised by the interaction with the chatbot increase creepiness, which is positively associated with consumer traits (i.e., technology anxiety and need for human interaction). The main contribution of the research lies in its focus on creepiness, a concept under‐researched in the marketing literature, and which can be seen from the perspective of a coping mechanism for consumers’ privacy concerns. This paper provides practical implications to orient managers in the design and implementation of chatbots, as a promising touch point to build customer loyalty.

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Section: Theoretical Background and Development Of Hypothesesmentioning

confidence: 99%

Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

Rajaobelina

Tep

Arcand

et al. 2021

Psychology and Marketing

119

View full text Add to dashboard Cite

show abstract

“…Third, AI chatbot design and research are still in their infancy [14]. As technologies advance to highly interactive user interface with realistic digital representations, it is unclear how their connection to certain contextual information, such as a background story, will affect user appeal and engagement [16,[49][50][51]. Such technological advantages tend to serve privileged populations better and can implicitly embody prejudices against those who are vulnerable and marginalized [52].…”

Section: Research Gaps and Questionsmentioning

confidence: 99%

An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study

Wang¹,

Gupta²,

Singhal³

et al. 2022

J Med Internet Res

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Background Leveraging artificial intelligence (AI)–driven apps for health education and promotion can help in the accomplishment of several United Nations sustainable development goals. SnehAI, developed by the Population Foundation of India, is the first Hinglish (Hindi + English) AI chatbot, deliberately designed for social and behavioral changes in India. It provides a private, nonjudgmental, and safe space to spur conversations about taboo topics (such as safe sex and family planning) and offers accurate, relatable, and trustworthy information and resources. Objective This study aims to use the Gibson theory of affordances to examine SnehAI and offer scholarly guidance on how AI chatbots can be used to educate adolescents and young adults, promote sexual and reproductive health, and advocate for the health entitlements of women and girls in India. Methods We adopted an instrumental case study approach that allowed us to explore SnehAI from the perspectives of technology design, program implementation, and user engagement. We also used a mix of qualitative insights and quantitative analytics data to triangulate our findings. Results SnehAI demonstrated strong evidence across fifteen functional affordances: accessibility, multimodality, nonlinearity, compellability, queriosity, editability, visibility, interactivity, customizability, trackability, scalability, glocalizability, inclusivity, connectivity, and actionability. SnehAI also effectively engaged its users, especially young men, with 8.2 million messages exchanged across a 5-month period. Almost half of the incoming user messages were texts of deeply personal questions and concerns about sexual and reproductive health, as well as allied topics. Overall, SnehAI successfully presented itself as a trusted friend and mentor; the curated content was both entertaining and educational, and the natural language processing system worked effectively to personalize the chatbot response and optimize user experience. Conclusions SnehAI represents an innovative, engaging, and educational intervention that enables vulnerable and hard-to-reach population groups to talk and learn about sensitive and important issues. SnehAI is a powerful testimonial of the vital potential that lies in AI technologies for social good.

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“…This concern, according to another study, can limit consumers' willingness to use a chatbot. 49 Data protectionists criticize the way companies collect and use our data and emphasize that we need to be aware of the data we share. 50 People share a lot of information, such as their location, name and purchasing history, with a chatbot, and, interestingly, they are often unaware of this.…”

Section: Privacy Issuesmentioning

confidence: 99%

Artificial Intelligence and Customer Relationship Management

Kouroupis¹,

Vagianos²,

Totka³

2021

East European Yearbook on Human Rights

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In the new digital era as it is formed by the European digital strategy, the explosion of e-commerce and related technologies has led to the formation of tremendous volumes of customer data that could be exploited in a variety of ways. Customer relationship management (CRM) systems can now exploit these data sets to map consumers' behaviour more effectively. As social media and artificial intelligence widened their penetration, firms' interest shifted to chatbots in order to serve their customers' needs. Nowadays, CRM and bots are developed in a parallel way. With the help of these virtual personal assistants, CRM establishes a virtual relationship with consumers. However, the extended collection and use of personal data under this scope may give rise to ethical and legal issues. In this article, the term CRM is defined, followed by an analysis of the way chatbots support CRM systems. In the second part, the legal context of chatbot use will be highlighted in an attempt to investigate whether there are personal data protection issues and whether certain rights or ethical rules are somehow violated. The draft AI Regulation, in combination with the provisions of GDPR and e-Privacy Directive, offers a significant background for our study. The article concludes by demonstrating the use of chatbots as an inherent part of the new digital era and lays special emphasis on the term 'transparency', which seems to penetrate the lawfulness of their use and guarantee our privacy.

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Privacy Concerns in Chatbot Interactions

Cited by 21 publications

References 0 publications

Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

Creepiness: Its antecedents and impact on loyalty when interacting with a chatbot

An Artificial Intelligence Chatbot for Young People’s Sexual and Reproductive Health in India (SnehAI): Instrumental Case Study

Artificial Intelligence and Customer Relationship Management

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