The Role of Privacy Guarantees in Voluntary Donation of Private Data for Altruistic Goals
<|reference_start|>The Role of Privacy Guarantees in Voluntary Donation of Private Data for Altruistic Goals: Voluntary donation of private information for altruistic purposes, such as advancing research, is common. However, concerns about data misuse and leakage may deter individuals from donating their information. While prior research has indicated that Privacy Enhancement Technologies (PETs) can alleviate these concerns, the extent to which these techniques influence willingness to donate data remains unclear.   This study conducts a vignette survey (N=485) to examine people's willingness to donate medical data for developing new treatments under four privacy guarantees: data expiration, anonymization, use restriction, and access control. The study explores two mechanisms for verifying these guarantees: self-auditing and expert auditing, and evaluates the impact on two types of data recipient entities: for-profit and non-profit institutions.   Our findings reveal that the type of entity collecting data strongly influences respondents' privacy expectations, which in part influence their willingness to donate data. Respondents have such high expectations of the privacy provided by non-profit entities that explicitly stating the privacy protections provided makes little adjustment to those expectations. In contrast, statements about privacy bring respondents' expectations of the privacy provided by for-profit entities nearly in-line with non-profit expectations. We highlight the risks of these respective results as well as the need for future research to better align technical community and end-user perceptions about the effectiveness of auditing PETs and to effectively set expectations about the efficacy of PETs in the face of end-user concerns about data breaches.<|reference_end|>
@article{wang2024the,
    title={The Role of Privacy Guarantees in Voluntary Donation of Private Data for
  Altruistic Goals},
    author={Ruizhe Wang, Roberta De Viti, Aarushi Dubey, Elissa M. Redmiles},
    journal={arXiv preprint arXiv:2407.03451},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.03451},
    primaryClass={cs.CR cs.HC}
}