Design Implications for Human-Machine Interactions from a Qualitative Pilot Study on Privacy

Leschanowsky, Anna; Brüggemeier, Birgit; Peters, Nils

doi:10.21437/spsc.2021-16

Cited by 4 publications

(1 citation statement)

References 4 publications

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“…Some CUI let users enter their information and other CUI ask for access to users' devices and data. In both cases, forcing the user to disclose can frustrate users and may lead to rejection of the service (Leschanowsky, Brüggemeier, & Peters, 2021). In our experiment we aim to assess user behaviour and perceptions when a chatbot asks to access data vs when a chatbot asks users to enter data.…”

Section: Example Study With Cblmentioning

confidence: 99%

Chatbot Language - crowdsource perceptions and reactions to dialogue systems to inform dialogue design decisions

2022

Self Cite

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Conversational User Interfaces (CUI) are widely used, with about 1.8 billion users worldwide in 2020. For designing and building CUI, dialogue designers have to decide on how the CUI communicates with users and what dialogue strategies to pursue (e.g. reactive vs. proactive). Dialogue strategies can be evaluated in user tests by comparing user perceptions and reactions to different dialogue strategies. Simulating CUI and running them online, for example on crowdsourcing websites, is an attractive avenue to collecting user perceptions and reactions, as they can be gathered time- and cost-effectively. However, developing and deploying a CUI on a crowd sourcing platform can be laborious and requires technical proficiency from researchers. We present Chatbot Language (CBL) as a framework to quickly develop and deploy CUI on crowd sourcing platforms, without requiring a technical background. CBL is a library with specialized CUI functionality, which is based on the high-level language JavaScript. In addition, CBL provides scripts that use the API of the crowd sourcing platform Mechanical Turk (MT) in order to (a) create MT Human Intelligence Tasks (HITs) and (b) retrieve the results of those HITs. We used CBL to run experiments on MT and present a sample workflow as well as an example experiment. CBL is freely available and we discuss how CBL can be used now and may be further developed in the future.

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Section: Example Study With Cblmentioning

confidence: 99%

Chatbot Language - crowdsource perceptions and reactions to dialogue systems to inform dialogue design decisions

2022

Self Cite

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Uncertain yet Rational - Uncertainty as an Evaluation Measure of Rational Privacy Decision-Making in Conversational AI

Leschanowsky

Popp

Peters

2023

Lecture Notes in Computer Science

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Debiasing Strategies for Conversational AI: Improving Privacy and Security Decision-Making

Leschanowsky,

Popp,

Peters

2023

DISO

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With numerous conversational AI (CAI) systems being deployed in homes, cars, and public spaces, people are faced with an increasing number of privacy and security decisions. They need to decide which personal information to disclose and how their data can be processed by providers and developers. On the other hand, designers, developers, and integrators of conversational AI systems must consider users’ privacy and security during development and make appropriate choices. However, users as well as other actors in the CAI ecosystem can suffer from cognitive biases and other mental flaws in their decision-making resulting in adverse privacy and security choices. Debiasing strategies can help to mitigate these biases and improve decision-making. In this position paper, we establish a novel framework for categorizing debiasing strategies, show how existing privacy debiasing strategies can be adapted to the context of CAI, and assign them to relevant stakeholders of the CAI ecosystem. We highlight the unique possibilities of CAI to foster debiasing, discuss limitations of the strategies, and identify research challenges.

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Design Implications for Human-Machine Interactions from a Qualitative Pilot Study on Privacy

Cited by 4 publications

References 4 publications

Chatbot Language - crowdsource perceptions and reactions to dialogue systems to inform dialogue design decisions

Chatbot Language - crowdsource perceptions and reactions to dialogue systems to inform dialogue design decisions

Uncertain yet Rational - Uncertainty as an Evaluation Measure of Rational Privacy Decision-Making in Conversational AI

Debiasing Strategies for Conversational AI: Improving Privacy and Security Decision-Making

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