University of Sussex
Browse
EMAC2022_AI_in_Public.pdf (129.42 kB)

AI in public: the effects of technology bias, fears of public surveillance, and moral tradeoffs on privacy concerns

Download (129.42 kB)
conference contribution
posted on 2023-06-10, 02:58 authored by Matilda Dorotic, Emanuela StagnoEmanuela Stagno
Applications of AI in public surveillance contexts fuel polemics among consumers and public policy makers alike. In two experimental studies, we explore the mechanisms that affect citizens’ attitudes towards government surveillance technologies. In Study 1, we show that the privacy and surveillance concerns are reduced when government (vs. firm) owns the data. Moreover, the fear of technology biases moderates the relationship between privacy concerns and willingness to adopt. In Study 2, we analyze the potential of anonymization of data collection to remedy the perceived privacy concerns. We find that the effect of anonymization of data collection on the willingness to support government surveillance technology goes through two parallel antecedents of privacy concerns: a reduction in perceived government intrusiveness and an increase in the perceived fairness and justice. Reduced privacy concerns ultimately increase the perceived usefulness of technological solution and increase the willingness to adopt.

History

Publication status

  • Published

File Version

  • Accepted version

Journal

Proceedings of the European Marketing Academy

Publisher

EMAC

Page range

1-11

Event name

EMAC Annual Conference 2022

Event location

Corvinus University of Budapest

Event type

conference

Event date

24-27 May 2022

Department affiliated with

  • Strategy and Marketing Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2022-03-25

First Open Access (FOA) Date

2022-03-28

First Compliant Deposit (FCD) Date

2022-03-28

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC