An investigation into the sensitivity of personal information and implications for disclosure: a UK perspective

Date

2022-06-30

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Frontiers

Department

Type

Article

ISSN

2624-9898

Format

Citation

Belen-Saglam R, Nurse JRC, Hodges D. (2022) An investigation into the sensitivity of personal information and implications for disclosure: a UK perspective, Frontiers in Computer Science, Volume 4, June 2022, Article number 908245

Abstract

The perceived sensitivity of information is a crucial factor in both security and privacy concerns and the behaviors of individuals. Furthermore, such perceptions motivate how people disclose and share information with others. We study this topic by using an online questionnaire where a representative sample of 491 British citizens rated the sensitivity of different data items in a variety of scenarios. The sensitivity evaluations revealed in this study are compared to prior results from the US, Brazil and Germany, allowing us to examine the impact of culture. In addition to discovering similarities across cultures, we also identify new factors overlooked in the current research, including concerns about reactions from others, personal safety or mental health and finally, consequences of disclosure on others. We also highlight a difference between the regulatory perspective and the citizen perspective on information sensitivity. We then operationalized this understanding within several example use-cases exploring disclosures in the healthcare and finance industry, two areas where security is paramount. We explored the disclosures being made through two different interaction means: directly to a human or chatbot mediated (given that an increasing amount of personal data is shared with these agents in industry). We also explored the effect of anonymity in these contexts. Participants showed a significant reluctance to disclose information they considered “irrelevant” or “out of context” information disregarding other factors such as interaction means or anonymity. We also observed that chatbots proved detrimental to eliciting sensitive disclosures in the healthcare domain; however, within the finance domain, there was less effect. This article's findings provide new insights for those developing online systems intended to elicit sensitive personal information from users.

Description

Software Description

Software Language

Github

Keywords

personal information disclosure, information sensitivity, privacy, chatbots, conversational agents, artificial intelligence, personal information

DOI

Rights

Attribution 4.0 International

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